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Business leaders, lawmakers, academicians, scientists, and many others are looking for ways to harness the power of generative AI, which can potentially transform the way we learn and work. In the corporate world, generative AI has the power to transform the way businesses interact with customers and drive growth. The latest research from Salesforce indicates that 2 out of 3 (67%) of IT leaders are looking to deploy generative AI in their business over the next 18 months, and 1 out of 3 are calling it their topmost priority. Organizations are exploring how this disruptive technology of generative AI could impact every aspect of their business, from sales, marketing, service, commerce, engineering, HR, and others. While there is no doubt about the promise of generative AI, business leaders want a trusted and secure way for their workforce to use this technology. Almost 4 out of 5 (79%) of business leaders voiced concerns that this technology brings along the baggage of security risks and biased outcomes. At a larger level, businesses must recognize the importance of ethical, transparent, and responsible use of this technology. A company using generative AI technology to interact with customers is in an entirely different setting from individuals using it for private consumption. There is an imminent need for businesses to adhere to regulations relevant to their industry.  Irresponsible, inaccurate, or offensive outcomes of generative AI could open a pandora’s box of legal, financial, and ethical consequences. For instance, the harm caused when a generative AI tool gives incorrect steps for baking a strawberry cake is much lower than when it gives incorrect instructions to a field technician for repairing a piece of machinery. If your generative AI tool is not founded on ethical guidelines with adequate guardrails in place, generative AI can have unintended harmful consequences that could back come to haunt you. Companies need a clearly defined framework for using generative AI and to align it with their business goals including how it will help their existing employees in sales, marketing, service, commerce, and other departments that generative AI touches. In 2019, Salesforce published a set of trusted AI practices that covered transparency, accountability, and reliability, to help guide the development of ethical AI systems. These can be applied to any business looking to invest in AI. But having a rule book on best practices for AI isn’t enough; companies must commit to operationalizing them during the development and adoption of AI. A mature and ethical AI initiative puts into practice its principles via responsible AI development and deployment by combining multiple disciplines associated with new product development such as product design, data management, engineering, and copyrights, to mitigate any potential risks and maximize the benefits of AI. There are existing models for how companies can initiate, nurture, and grow these practices, which provide roadmaps for how to create a holistic infrastructure for ethical, responsible, and trusted AI development. With the emergence and accessibility of mainstream generative AI, organizations have recognized that they need specific guidelines to address the potential risks of this technology. These guidelines don’t replace core values but act as a guiding light for how they can be put into practice as companies build tools and systems that leverage this new technology. Guidelines for the development of ethical generative AI The following set of guidelines can help companies evaluate the risks associated with generative AI as these tools enter the mainstream. They cover five key areas. Accuracy Businesses should be able to train their AI models on their own data to produce results that can be verified with the right balance of accuracy, relevance, and recall (the large language model’s ability to accurately identify positive cases from a given dataset). It’s important to recognize and communicate generative AI responses in cases of uncertainty so that people can validate them. The simplest way to do this is by mentioning the sources of data which the AI model is retrieving information from to create a response, elucidating why the AI gave those responses. By highlighting uncertainty and having adequate guardrails in place ensures certain tasks cannot be fully automated. Safety Businesses need to make every possible effort to reduce output bias and toxicity by prioritizing regular and consistent bias and explainability assessments. Companies need to protect and safeguard personally identifying information (PII) present in the training dataset to prevent any potential harm. Additionally, security assessments (such as reviewing guardrails) can help companies identify potential vulnerabilities that may be exploited by AI. Honesty When aggregating training data for your AI models, data provenance must be prioritized to make sure there is clear consent to use that data. This can be done by using open-source and user-provided data, and when AI generates outputs autonomously, it’s imperative to be transparent that this is AI-generated content. For this declaration (or disclaimer), watermarks can be used in the content or by in-app messaging. Empowerment While AI can be deployed autonomously for certain basic processes which can be fully automated, in most cases AI should play the role of a supporting actor. Generative AI today is proving to be a powerful assistant. In industries, such as financial services or healthcare, where building trust is of utmost importance, it’s critical to have human involvement in decision-making. For example, AI can provide data-driven insights and humans can take action based on that to build trust and transparency. Furthermore, make sure that your AI model’s outputs are accessible to everyone (e.g., provide ALT text with images). And lastly, businesses must respect content contributors and data labelers. Sustainability Language models are classified as “large” depending on the number of values or parameters they use. Some popular large language models (LLMs) have hundreds of billions of parameters and use a lot of machine time (translating to high consumption of energy and water) to train them. To put things in perspective, GPT3 consumed 1.3 gigawatt hours of energy, which is enough energy to power 120 U.S. homes for a year and 700k liters of clean water. When investigating AI models for your business, large does not necessarily mean better. As model development becomes a mainstream activity, businesses will endeavor to minimize the size of their models while maximizing their accuracy by training them on large volumes of high-quality data. In such a scenario, less energy will be consumed at data centers because of the lesser computation required, translating to a reduced carbon footprint. Integrating generative AI Most businesses will embed third-party generative AI tools into their operations instead of building one internally from the ground up. Here are some strategic tips for safely embedding generative AI in business apps to drive results: Use zero or first-party data Businesses should train their generative AI models on zero-party data (data that customers consent to), and first-party data, which they collect directly. Reliable data provenance is critical to ensure that your AI models are accurate, reliable, and trusted. When you depend on third-party data or data acquired from external sources, it becomes difficult to train AI models to provide accurate outputs. Let’s look at an example. Data brokers may be having legacy data or data combined incorrectly from accounts that don’t belong to the same individual or they could draw inaccurate inferences from that data. In the business context, this applies to customers when the AI models are being grounded in that data. Consequently, in Marketing Cloud, if all the customer’s data in the CRM came from data brokers, the personalization may be inaccurate. Keep data fresh and labeled Data is the backbone of AI. Language models that generate replies to customer service queries will likely provide inaccurate or outdated outputs if the training is grounded in data that is old, incomplete, or inaccurate. This can lead to something referred to as “hallucinations”, where an AI tool asserts that a misrepresentation is the truth. Likewise, if training data contains bias, the AI tool will only propagate that bias. Organizations must thoroughly review all their training data that will be used to train models and eliminate any bias, toxicity, and inaccuracy. This is the key to ensuring safety and accuracy. Ensure human intervention Just because a process can be automated doesn’t mean that’s the best way to go about it. Generative AI isn’t yet capable of empathy, understanding context or emotion, or knowing when they’re wrong or hurtful. Human involvement is necessary to review outputs for accuracy, remove bias, to ensure that their AI is working as intended. At a broader level, generative AI should be seen as a means to supplement human capabilities, not replace them. Businesses have a crucial role to play in the responsible adoption of generative AI, and integrating these tools into their everyday operations in ways that enhance the experience of their employees and customers. And this goes all the way back to ensuring the responsible use of AI – maintaining accuracy, safety, transparency, sustainability, and mitigating bias, toxicity, and harmful outcomes. And the commitment to responsible and trusted AI should extend beyond business objectives and include social responsibilities and ethical AI practices. Test thoroughly Generative AI tools need constant supervision. Businesses can begin by automating the review process (partially) by collecting AI metadata and defining standard mitigation methods for specific risks. Eventually, humans must be at the helm of affairs to validate generative AI output for accuracy, bias, toxicity, and hallucinations. Organizations can look at ethical AI training for engineers and managers to assess AI tools. Get feedback Listening to all stakeholders in AI – employees, advisors, customers, and impacted communities is vital to identify risks and refine your models. Organizations must create new communication channels for employees to report concerns. In fact, incentivizing issue reporting can be effective as well. Some companies have created ethics advisory councils comprising of employees and external experts to assess AI development. Having open channels of communication with the larger community is key to preventing unintended consequences. As generative AI becomes part of the mainstream, businesses have the responsibility to ensure that this emerging technology is being used ethically. By committing themselves to ethical practices and having adequate safeguards in place, they can ensure that the AI systems they deploy are accurate, safe, and reliable and that they help everyone connected flourish. As a Salesforce Consulting Partner, we are part of an ecosystem that is leading this transformation for businesses. Generative AI is evolving at breakneck speed, so the steps you take today need to evolve over time. But adopting and committing to a strong ethical framework can help you navigate this period of rapid change.

One of the primary drivers of research in Artificial Intelligence (AI) has been to create AI systems that can build viable and powerful computer programs to tackle complex business challenges. Recent developments in this area especially the rapid strides made by Large Language Models (LLMs), have brought about this radical shift in thinking. LLMs were originally developed for comprehending natural language but now they have taken machine intelligence to another level. LLMs can now create code and text, setting a new bar for AI development. Until now, LLMs have been reasonably proficient in handling routine programming tasks. However, they often falter when confronted with complex programming challenges. One of the major stumbling blocks in their use for solving programming problems has been their tendency to generate code blocks as monolithic entities instead of breaking them down into granular, logic-based code blocks with specific functionality. Human developers on the other hand are easily able to create modular code when dealing with complex problems. They tap into their knowledge base of pre-existing modules to accelerate the development of solutions to new problems. Salesforce Research recently introduced CodeChain, a cutting-edge AI framework to bridge this gap. CodeChain leverages a series of self-revisions driven by sub-modules created in earlier iterations to streamline the process of creating modular code. At the core of CodeChain lies the methodology of enabling LLMs to approach problem-solving to create logical subtasks and reusable sub-modules. There are two iterative phases in the sequence of self-revisions in CodeChain. Sub-Module Extraction and Clustering: In this phase, sub-modules are identified by analyzing the code generated by the LLM. Next, these sub-modules are organized into clusters. From each cluster, representative sub-modules are selected which are identified to be more widely applicable and reusable. Prompt Enhancement and Re-Generation: The initial chain-of-thought prompt is further improved and regenerated by integrating the selected representative modules from the previous phase. Next, the LLM is asked to produce new modular code solutions once again. This way, the LLM can leverage the information and understanding from earlier iterations to enhance them further. CodeChain has already been shown to have a significant impact on code generation. Salesforce has indicated that by asking the LLM to enhance and reuse pre-existing sub-modules, the modularity and accuracy of generated solutions are greatly improved. Comprehensive studies have been conducted to investigate deeper into the factors that contribute to CodeChain’s success. These investigations look at aspects like prompting technique, LLM model size, and code quality. The insights from these studies reveal why CodeChain excels in improving the quality and modularity of code generated by LLMs, making it a potential game-changer for AI-powered code generation. CodeChain leverages chain-of-thought prompting to generate modular blocks of code which drives natural selection of the LLM to select parts of the generated solution for reuse and refinement. CodeChain’s release by Salesforce AI marks a key milestone in AI-powered code generation. Its ability to boost modularity and accuracy, along with significant improvements in pass rates indicates a giant leap forward. This disruptive framework is poised to transform the programming landscape, empowering businesses to quickly build and deploy effective solutions. Introducing CodeGen: Turning Prompts Into Code The Salesforce Research team recently announced the launch of CodeGen – a new LLM that leverages conversational AI to generate accurate and modular code.   With CodeGen from Salesforce, both programmers and business users can use natural language prompts to define what they want the code to do such as build an app that throws up the last customer interaction. The LLM translates those prompts into code, effectively creating an app using just written instructions. With CodeGen’s conversational AI capabilities, business and technology teams can eliminate the time and resource-intensive process of building apps from scratch. CodeGen empowers programmers to build apps quickly without much coding, freeing up more time for complex tasks that necessitate a human touch. The CodeGen Solution In simple terms – with CodeGen, all you need to do is describe what you want your code to do in natural language and the machine will write executable code for you. This is the next generational promise of conversational AI programming from CodeGen. It makes coding as easy as talking. Here’s an example to illustrate the power of CodeGen. When you want to eat a certain dish for dinner, you need to know all the ingredients required to make the dish want and then you have to cook it yourself. You need to know the serving size, the proportion of each ingredient, and the steps to follow. Now, let’s say you go to a restaurant powered by CodeGen. You just tell the server what dish you want, and they prepare it and serve it to you. Just describe the dish you want in a short sentence, and it will be served to you without any involvement from you in its creation. You don’t need to specify any ingredients or explain the steps involved in cooking it or provide any other associated instructions. You don’t even need any knowledge of any culinary terms either. The restaurant kitchen behaves like an intelligent entity, converting your plain sentence into a sequence of steps that takes all the ingredients, in the most appropriate proportion and creates the outcome (in your case the dish you asked for). Now imagine, instead of a meal you are “ordering” an app that can perform certain functions. That’s the basic idea behind CodeGen. Salesforce’s implementation of conversational AI programming highlights its commitment to an inclusive approach to software programming to bring it to the masses. AI translates natural language descriptions into fully functional and executable code empowering anyone to build apps even if one has no prior knowledge of programming. According to Salesforce, CodeGen, their LLM which powers conversational AI programming will soon be available as open source to accelerate research. The launch of CodeChain from Salesforce AI is a landmark event for innovators around the globe. With its ability to improve code modularity and accuracy, it can empower IT teams to dramatically accelerate problem-solving.  This disruptive framework is poised to transform the way we approach and solve business problems. To learn more about AI-powered code generation, contact Girikon, a Gold Salesforce Consulting Partner today.

As an IT manager, you would have handled several rollouts and migrations, streamlined legacy systems, and upgraded cybersecurity. And now AI is staring you in the face. How ready are you to build AI apps that your business needs? Do you have in-house skills to build and deploy AI apps? Whether you are building a customer service app or a marketing app, you can adopt a systematic approach to going about it. Here are 5 key steps to building effective AI apps for your organization. 1. Define exactly what you want from your app before starting to build one Businesses across industries have started to embrace the disruptive technology of AI for their everyday operations. Your competitors are likely deploying AI chatbots to provide 24/7 automated, intelligent, customer service. But before you start investing time and resources in building AI apps, you need to answer some key questions. What is the problem you’re trying to solve? Talk with your business’s leaders. Do you want to boost sales? Improve customer satisfaction score?  As a starting step, clearly define use cases. Next, define the desired end state for each use case. This will help you estimate how much effort is required, who to involve, and whether you have adequate resources. What are your competitors doing? Understand what your competitors are doing with their AI tools and for whom. And how can you innovate further on those ideas? And of course, you need to answer one important question – can you build AI apps in-house? Do you have the necessary skills and experience in your team to do this? Based on the use cases you have identified, will you require generative or predictive AI If you don’t have the skills internally like Machine Learning and Natural Language Processing, look for partners and ISVs for solutions and do a thorough comparison of their offers and capabilities. 2. Define the perimeter for ethics and security As an IT manager, security, privacy, and accuracy are not alien to you. But AI amplifies the challenges and raises many risks such as bias and toxicity. AI bias: Negative bias can be caused by algorithm error based on human prejudices or false assumptions. The consequence is an AI tool that works in unintended ways. Generative AI can propagate outputs based on errors and further amplify the problem. Toxicity: Abusive language and hurtful comments can appear in AI-generated outputs. Researchers have found that assuming certain personas can amplify the toxicity of the response. Before you start building your AI app, define trust and ethics parameters. Trusted AI should be empowering, and inclusive apart from being responsible and transparent. 3. Good data is the foundation of effective AI apps If you are building generative AI apps, your machine learning models will train on the data that is fed to them. AI machine learning models train on all kinds of data. And that data needs to be clean and free of redundancy. The more data your LLMs can be trained on, the better will be the output of your AI. 4. Choose the right technology for your AI app The technology you select for building your AI depends to a certain extent on your use case. If your app summarizes text, processes language, or a knowledge base, you will need an LLM. Over time, as the LLM learns more about your business and its data, it can make logical interpretations and draw conclusions. Building your own learning model can be expensive. You will need to hire data scientists and engineers with expertise in ML and NLP. While it is a lengthy cycle, if you do decide to take this route, once your team is ready you can take the help of libraries and toolkits and integrate them into your development. Generative AI platforms and libraries ML and DL platforms: Amazon SageMaker and Google Vertex AI have built-in libraries and tools to train your AI model and support multiple programming languages. NLP toolkits: If you are building chatbots or virtual assistants, SpaCy is a great NLP toolkit for Python enthusiasts. OpenAI allows you to customize their GPTs for your apps. Deep learning libraries: If you want to build apps for speech or image recognition, you can look at a deep learning library to find a framework for building, training, and deploying your apps. Open-source libraries such as PyTorch and MXNet can be used in combination depending on your use case. Computer vision libraries: If you want your app to analyze images or video, you can use open-source libraries such as OpenCV and TensorFlow. PyTorch is another option that can be helpful. Building AI apps with CRM data If you want to build customer-interfacing apps, you will need to leverage your customer data. And without all your data in one place, that’s hard to do. You need an enterprise-grade CRM like Salesforce to make your AI app work best for you. You can connect AI models to Salesforce Data Cloud without running into a wall. With the Model Builder (erstwhile called Einstein Studio), you can bring your own model into Salesforce. 5. Build AI apps and start deploying In a recent developers’ survey conducted by Salesforce, it was found that 70% of developers use or intend to use AI for development. The biggest benefit developers see is reduced development cycles. Try AI for code generation Whether you use AI or not for code generation, you can reduce development time with the Einstein 1 platform for Salesforce. Einstein for Developers understands natural language prompts to write code in seconds. The more precise your prompt, the better will be the quality of the code generated. Once the code is generated you can accept, revise, or reject it. Einstein for Developers uses a customized Large Language Model based on the open-source CodeGen AI model from Salesforce. Use an IDE to accelerate development A web-based integrated development environment (IDE) allows your teams to work from anywhere, anytime. You can modify and debug code and maintain source control in one place.  Code Builder, the new IDE from Salesforce is preloaded with frameworks, has built-in integration with Git, and is free for admins and developers. Salesforce also allows you to integrate other IDEs with it. Follow App Lifecycle Management and DevOps practices Building and launching great AI apps need solid processes across stages of app development, along with collaborative tools for developers, data scientists, testers, and project managers. Salesforce has inbuilt AI tools like Einstein for Developers and Prompt Builder to come to your aid. DevOps Center, available on the Einstein 1 platform, can help you to maintain version control, track changes and push your build for UAT and production. If you prefer working with your own tools for IDE, project management, and DevOps, you can bring them into the Salesforce environment. Connect with an AI expert today. With over a decade of experience as a Salesforce Consulting Partner, our experts are always available to guide you through the process and answer any questions you might have regarding the potential of AI in your business.

In today’s increasingly connected world, data is the point on which the entire business world pivots. We are generating unimaginable amounts of data every day. And locked within these humongous stores of data are the insights that businesses can use to better understand themselves and more importantly their customers. To remain competitive, businesses need to do more than just collect data. They need to be able to capture and analyse that data and convert it into actionable insights in real time to succeed. Enter Salesforce Einstein Analytics Here are 40 reasons why Einstein Analytics is the no. 1 choice when it comes to data analytics for your business. Hit the Ground Running. Work with a someone you can trust: Enjoy peace of mind knowing that you are working with the world’s no 1 CRM platform. Cust Costs: Reduce operating costs by using a pay as you use cloud-based analytics platform. Say goodbye to expensive installation or maintenance costs, and onsite hardware. Get going quickly: Leverage powerful analytics within minutes, thanks to out of the box solutions. Cut out the fluff: Pay only for the features you use. Salesforce Einstein Analytics comes with flexible usage models, so you always have the tools you need, at a price that suits your budget. Customise your solution: Salesforce Einstein Analytics is fully customisable and can be easily tailored for your business. With Einstein Analytics, you can set up the solution that works best for you. Built-in support: Salesforce Einstein Analytics comes with comprehensive guides, tutorials, videos, and multiple support options across channels. Integrate your data: No need to depend on your IT teams to upgrade your software for data analysis. Einstein Analytics seamlessly integrates analytics tools with every application and system, giving you a coherent, integrated, easy-to-use solution that gives you faster results. Connect Across Departments. Integrate seamlessly with the entire Salesforce platform: Salesforce Einstein Analytics integrates perfectly with all Salesforce products such as Sales Cloud, Service Cloud, Marketing Cloud etc giving every user easy access to unified customer data. Collaborate: Collaborate across sales, service, marketing, and other teams with cloud-based data analytics that can be accessed from anywhere across any device. Unify your goals: Give your teams a unified vision and objectives they can strive for, with data that is insightful, reliable, and actionable. Generate stunning visuals: Use built-in tools to convert data into stunning insightful reports and dashboards for presentations. Get conversational: Leverage social media technology to enhance team communication, with Chatter for Einstein Analytics. Put it in context: Get consistent views across departments with embedded reports and dashboards. Be available always: Work on your data over any device, from anywhere on the planet. Analyse Your Business. Monitor team performance: Leverage real-time reports to view team performance and identify trouble areas early and optimize. Access KPIs: Discover key performance indicators across your organisation to ensure you do not deviate from the path of success. Track call-center efficiency: See customer support trends across channels right on your dashboard and make informed decisions to enhance the customer service experience. Empower teams to self analyse: Give your teams the power to measure their own performance and set new performance benchmarks. Find the Key to Sales Success. See the big picture: Explore all data in a unified dashboard. Get a 360 degree snapshot of the health of your business. Eliminate borders: Get a unified view of your business across geographies, products, customer segments and time periods, for a true picture of how your business is performing. Predict the future: View historical trends to intelligently forecast which strategies are most likely to work and which leads are the most promising. Reduce customer churn: Get detailed insights into each and every customer, deliver personalised customer experiences and ensure customer loyalty and retention. Prioritise leads: Analyse your leads to assess the likelihood of their conversion and focus on the most promising ones. Evaluate your lead sources: Discover which sources are the most productive, so you can focus your efforts where it pays off the most. Enhance the customer experience: Resolve issues and monitor customer satisfaction directly from within Salesforce, and optimise. Market Smarter. Dive deeper: Go deep into your marketing data and get a detailed analysis of funnels, campaigns, conversion rates and more across channels. Present the right message: Create messaging to attract your target audience, and get valuable insight into that audience. Be your own data analyst: Marketing data analysis is too precious to hand over to someone else. With easy-to-use tools and visually compelling reports, become your own marketing analyst. Take instant action: Act in real time with up-to-the-minute marketing data from unified dashboards. Specialize in B2B marketing: Leverage the power of unique and effective B2B marketing tools in Salesforce to stay ahead of the competition. Understand the brand experience: Analyze data to see what your customers see, and optimize the customer experience. Optimise Service. Set your priorities: Prioritise open cases with service manager, and give your teams a clear view of customers that need their attention. Evaluate your accounts: Identify accounts with the highest number of cases and highest opportunity. Connect with your agents: Get a complete view of agents and their cases, and assign notifications based on configurable conditions. Review your service backlog: Compare data and identify service trends over time to assess how service levels compare across years. Revolutionise Analytics for Your Organization. Integrate with third-party apps: Leverage advanced integration options for any third-party application and extend your analytics beyond Salesforce. Optimise your pipelines: Leverage data-driven strategies to manage your pipelines. Automate analysis: Salesforce Einstein AI is designed to automatically analyse millions of data combinations for informed actions. Data security: Share data across devices securely using the cloud platform security services trusted by over 150,000 businesses worldwide. Push the limits: Extend your analytics abilities with custom-made apps or find the right ready-made app for your specific analytics needs on the Salesforce AppExchange. Everyday, we are producing mind-bogglingly huge amounts of data. Businesses need to use that data as a foundation for data analytics, to understand themselves and their customer better, to drive enhanced customer experiences. Girikon is a Salesforce Consulting Company and has helped businesses across the globe achieve success on the Customer 360 platform. To know more about how you can turn your data into intelligent actionable insights with Salesforce Einstein Analytics, contact us today.

Powered by an extensive Salesforce Consulting Partner network, Salesforce provides access to expertise and solutions tailored for the automotive industry with their latest offering – Automotive Cloud. Automotive Cloud is a product created specifically for automotive manufacturers, supply chain partners, dealers, automotive finance companies, and their customers. Automotive Cloud empowers businesses to deliver exceptional customer service experiences across every interaction with Driver 360, boosts top lines with better lead conversion and improved collaboration, and leverages industry best practices based automation and real-time analytics for greater productivity and RoI. The automotive industry is going through a huge transformation as it gears up to meet the demands of today’s digital first world. Salesforce research indicates that only 1% of automotive customers had a delightful car buying experience, and only 25% auto manufacturers and dealers believe their business has adapted well to online commerce. To create new revenue channels and fix the fragmented customer experience, the automotive industry must recognize new opportunities with new selling and service models, connected and intelligent vehicles, subscriptions models, partnerships, and the heaps of data these new offerings generate.  With the rise in direct to consumer models and the surge in the adoption of electric vehicles, the automotive industry is in the midst of a new digital imperative. Automakers today recognize that with disruption comes opportunity, and businesses embracing the digital-first future with a technology platform like Automotive Cloud can have a competitive edge going into the future. According to Salesforce, over 90% of automotive industry leaders recognize that first-party data can help significantly improve the customer experience across every interaction – like vehicle browsing, purchasing, financing, or service. Automotive Cloud, powered by Driver 360, and built on automated, intelligent and real-time technology, delivers a unified view of the customer and vehicle lifecycle for auto manufacturers, supply chain partners, dealers, and finance agencies. Just like Education 360 for learning and Patient 360 for healthcare, Driver 360 is built on the powerful Customer 360 platform and delivers a single source of truth for the entire automotive industry. Whether consumers are surfing for a new car, completing a purchase, looking for vehicle financing, or want to get their vehicle serviced, Automotive Cloud is poised to drive the automotive industry through this phase of unprecedented transformation by enabling real-time intelligent personalization across the entire journey of the vehicle. With Automotive Cloud, marketers can configure ranking parameters to qualify leads to share the leads most likely to convert with the customer’s local dealer. Dealer managers can track the performance of their inventory to discover how dealers are performing to improve how they manage their inventory and vehicle allocation. Service teams can configure alerts to notify them when a service is due. And IT teams can build custom workflows with just a few clicks to automatically alert customers in case of a vehicle recall of a particular model. Driver 360 empowers you to deliver best-in-class customer experiences Driver 360 comes pre-built with industry specific best practices based on out-of-the-box solutions built on verified data models for the auto industry to fast track time to value. With Driver Console, service teams can get a comprehensive view of all customer interactions and alerts across every touchpoint throughout the customer and vehicle journey, including car browsing, purchasing to vehicle servicing. With the Household Management feature, automotive businesses can aggregate their data to build a 360 degree picture of a household’s vehicle ownership and past interactions, which the dealers and other partners can use to offer personalize support and offers. With Vehicle Console, staff across automakers, dealers and finance agencies can get easy access to holistic vehicle information like odometer readings, current market value of the vehicle and real-time service and repair information.  Automotive Data Foundation, which has been built on industry standards, is the cornerstone of Automotive Cloud. It creates a trusted data foundation that allows for interoperability, compliances, data protection and data sharing. Drive revenue through better lead conversion and communication Today’s customers prefer digital first engagement. Which means automotive businesses, dealers and partners need to collaborate seamlessly to drive sales, manage inventory, and deliver enhanced customer experiences.  Automotive Lead Management encourages collaboration right across the value chain that includes automotive manufacturers and dealers. It enriches leads by providing comprehensive  customer and vehicle history, enabling users to direct the high priority leads directly to the customer’s preferred dealer coupled with comprehensive information about their preferences, needs, and interaction history. Dealership performance can be easily analysed by region and lead pipelines can be monitored better with Dealer Performance Management. This enables auto businesses to focus their efforts and facilitate better coordination across sales agreements, customer visits, partner affiliations, forecasts, incentives, and much more. Powerful AI and analytics for increased productivity and cost savings with industry-specific automation, With rising prices of raw material and parts, supply chain limitations, and huge investments in EVs, automotive businesses need smart automation, AI, intelligent analytics based on seamlessly connected data to lower costs, identify new streams of revenue and empower users to make better informed decisions. Flow for Automotive Cloud allows users to build and deploy intelligent workflow automation with just a few clicks. Flow’s integration and configuration capability makes it easy to create and deploy branded automation experiences like order status updates or delay notifications to enable users to accomplish more tasks with lesser resources, improve efficiency, and deliver enhanced customer experiences at scale. With Analytics for Automotive Cloud, automakers can get deep insights to track and improve business performance. Analytics comes with purpose-built dashboards and views that give business users a detailed snapshot of business performance, customer and vehicle lifecycle, and trends, to yield faster and better business outcomes. With Salesforce Genie, automotive businesses can unify complete customer and vehicle data across multiple channels across all interactions by aggregating vehicle, service and interaction data into a unified, real-time, customer profile. With Automotive Cloud you can deliver unified purchase and service experiences. It empowers you to automate processes, get intelligent insights. Now you can transform customer insights into real time, rich, seamless experiences. Get an enriched view of your customers, households, vehicles, and assets to enable real-time, purposeful engagements. Automate business processes easily with just a few clicks. Simplify integrations across automakers, partners and collaborators and deliver branded experiences with just a few clicks with Flow for Automotive Cloud. Get intelligent insights and make better informed decisions. Customer facing teams can use the power of AI to engage smartly with customers across every touchpoint. Drive real-time, engaging experiences. Drive sales and service. Delight customers throughout the entire sales and service journey with a solution purpose built for the automotive industry. Here’s what you get with Automotive Cloud to power customer engagement. Driver Console Get a 360-degree view of all customer interactions and easily configure custom alerts for your teams. Vehicle Console Access important information such as vehicle details, warranties, or service reports. Household Management View complete history of a household’s owners and vehicles to deliver personalised support and offers. Automotive Lead Management Forward high-priority leads directly to the customer’s preferred dealer. Partner Performance Management Easily track performance of partners and seamlessly collaborate on site visits, incentives, and more. Automotive Data Foundation Ensure data protection, compliances, and data sharing. As a  Salesforce Consultant, Girikon recognizes that Automotive Cloud comes with limitless possibilities to enable automotive companies make their business future proof. To know more about how you can leverage AI, Automation and Analytics to significantly improve decision making, drive efficiency and boost revenues for your automotive business, contact one of our experts today.

The latest Summer '23 features have been released by Salesforce.  If you are looking to upgrade your Salesforce instance, the right Salesforce Implementation Partner can help you with the implementation of these new features and training of your Salesforce admins to make your operations more efficient and productive.  Here’s a look at the top 10 features from the Latest Salesforce Summer ’23 Release 1. Integrated Analytics Services The summer ’23 release comes with a consolidated interface for Analytics and Slack. Which means you can now enjoy a seamless engagement with all your CRM Analytics, Lightning reports and dashboards, and Einstein Discovery models and forecasts. The Analytics tab now comes with powerful search capabilities and recommendations, giving you access to organized statistics that you can turn to for all your Lightning dashboards and CRM Analytics. Using the Post to Slack feature on Lightning dashboards, you can share information such as dashboards and CRM data with colleagues throughout Slack workspaces easily. 2. Unified Analytics With the new release of Analytics Home, you no longer need to deal with analytics spread over different products. This new feature unifies all your CRM analytics data in a single place, allowing you easy access to information. Now you can get access to a consolidated view of all your CRM reports and dashboards in a structured and organised way, so you can easily access all the information you need to take quick decisions. 3. Customer Data Platform reimagined as Data Cloud In the new release, Salesforce has transformed the erstwhile Customer Data Platform into Salesforce Data Cloud with all the necessary documentation and additional features. 4. Barring Unverified Emails Sent by Guest Users This feature update disallows companies from sending emails from unverified email addresses of guest users. However, Salesforce customers that have a validated company-wide email address will not be impacted by this update. In such cases, the sender’s email address always updates to the authenticated email address. With the Latest Summer ’23 release, this enforced change effectively disallows shadowy emails from being sent by a guest user using an unverified email address. 5. Upgrade to Hyperforce Using Hyperforce Assistant The latest Summer ’23 release comes with Hyperforce Assistant which streamlines the upgrade to Hyperforce. The new Hyperforce Assistant comes with the latest Hyperforce messaging authorization feature that has better in-built reference checks to support Salesforce organizations that have a large number of Apex classes. Hyperforce Assistant is available in all editions of Salesforce Lightning as well as Classic. Once admins schedule the upgrade, they will be asked to initiate the assistant. Admins can activate the assistant manually in case you are scheduled for a major migration. During Setup, you can enter “Hyperforce Assistant” in the Quick Find Box and select the appropriate option. 6. Accelerated Quote Template Creation With OmniStudio Document Generation Quote generation is now much simpler with this latest add on. With Salesforce CPQ Plus, your reps can easily create templates to generate quotes for your customers. You can generate a Microsoft Word file in the format and language of your preference, insert tokens and upload the document. Then associate the inserted tokens with relevant Salesforce fields. Your sales reps can then start utilizing the template once it is active. They can also easily convert their documents to PDFs. This Salesforce CPQ plus update is available in both Salesforce Classic and Lightning Experience. 7. Real-Time Collaboration with Partner Relationship Management for Slack App This feature improves communication and collaboration across internal teams and external partners by bringing them together in a single channel using Slack. With Slack you can automate key business processes, and update and share records easily across collaborators. Partner Relationship Management for Slack connects your Salesforce CRM with partners seamlessly, with easy access to important information through partner portals, thereby boosting productivity, and fostering better communication. This upgrade impacts the Enterprise and Unlimited editions of Salesforce. The mandatory requirement to access this feature upgrade is to be a Slack Enterprise Grid user. 8. Codeless flow of External Data into Flow Builder This new feature allows admins to use Flow Builder to automate processes that involve external data without the need for coding by developing an HTTP callout action through a web service API. Once you enter the API details, Flow Builder automatically generates a reusable callout action which admins can immediately deploy in Flow Builder and across Salesforce. This commonly used feature has witnessed several enhancements since the last update. Now it is easier to configure and edit the API responses to HTTP callouts. This allows the use of external data inflows to be simpler and more declarative. This upgrade is available across all editions of the Lightning Experience – Enterprise, Performance, Unlimited and Developer. The reason why this feature has been introduced is that APIs often go through modifications, such as the addition of a new field or updation in an existing field in an external system. Admins with the relevant permissions in Manage Flow and Customize Applications can create an HTTP callout action. Previously, admins had to modify the auto-generated API definition in JSON to modify the HTTP callout action. With the latest update, this action can be modified with just a few clicks. Instead of editing and configuring JSON to parse the API response, admins can easily select data types for fields. With this new feature, admins will also receive more lucid error messages, simplifying the troubleshooting process and prevent runtime issues. 9. Quick Create Sandbox to Enhance Productivity Quick Create Full Sandbox is another new upcoming feature of the Salesforce’s Summer 23 Release. This feature accelerates sandbox creation and refreshing. This update means no additional actions will be required from Salesforce admins as it is the default setting. This feature will be available on eligible Hyperforce instances. Salesforce will initiate a staggered release after June 10, 2023, and users with the Manage Sandbox permission can use this feature. 10. Process Builder is on its way out. Rules have changed. Process Builder does not have the capability of adding new processes anymore. However, you can still activate/deactivate existing processes or edit them. Having said that, it is recommended that for most use cases, you migrate to Flow Builder.  The upgraded flow builder can take automation of business processes to a whole new level. Summing Up With the Summer ’23 release, Salesforce endeavours to make your daily tasks simpler, more efficient, and productive. The Summer ’23 release is designed to empower organizations to improve their engagement with customers, automate businesses processes, and drive growth. At Girikon, a Gold Salesforce Consulting Partner, we recognize that staying up-to-date with these new changes in the Salesforce platform and leveraging the new capabilities are key to maximizing your Salesforce RoI.  Contact one of our experts today to know more about how you can make the most of these exciting new features of the Summer ’23 Release.

When Salesforce acquired Vlocity in 2020, it acquired the capability to sync its core platform with industry-specific solutions & processes. This tailoring of its cloud offering addresses industry specific business needs as well as legal and regulatory needs of companies. Salesforce Industries also offers enhanced data models to serve various industries such as Financial Services, Government, Health, Government, Manufacturing, FMCG, Energy & Utilities, Communications and Media & Entertainment. More often than not, architects find themselves working on a project with industry-specific requirements. And they need out-of-the-box capabilities from the Salesforce Platform. What is Salesforce OmniStudio? Salesforce OmniStudio is powerful suite of 4 core task-based components. They are: OmniScript DataRaptor Integration Procedure FlexCards These components empower architects to consolidate applications, quickly bring up new users to productivity, and lower overall costs-to-serve. Salesforce OmniStudio is available as a complete native managed package that can add additional functionality to your existing Salesforce instance. Data model Salesforce Industries comes with industry-specific data models, as a layer on top of the Salesforce object model. The data model is completely additive. It is designed to enhance standard objects and fields or allow addition of new custom objects and fields. In other words, there is no duplication of any existing entity. OmniScript Architects across the world prefer tailored solutions to simplify maintenance and operations of systems. If you wish to deliver engaging digital experiences which can seamlessly integrate into your website, then OmniScript will help you get the best out of your engagements. With OmniScript you can easily deal with industry-specific cases. OmniScript enhances interactions by offering tools that are user-friendly can be tailored to deliver additional value to end-users. Also, it offers a code-less environment since it comes with ready-made aspects which can be deployed easily across channels and devices. Functionalities of OmniScript: It allows you to easily compose interactive processes for every use case, and allows you to branch easily. OmniStudio comes with a drag-and-drop OmniScript editor feature. Architects can use this feature to proof-read their work. There are also in-built troubleshooting tools to fix the processes. Device and channel agnostic. Users can access it from anywhere – whether mobile or web. If you are using a mobile app, you can use the OmniOut function to install Lightning Web Components (LWC) OmniScripts for these systems. It allows for easy prototyping of user experiences enabling reuse without any challenges by distinguishing between the JSON metadata structure, the data, and the templates. Allows easy generation of LWCs which can then be used in the Lightning App Builder. DataRaptor DataRaptor is a user friendly mapping tool. It allows architects to efficiently extract, store, and access data. DataRaptor allows easy configuration for negotiating any data. With DataRaptor, architects can easily extract, load and transform data conveniently. There are main 3 components in DataRaptor are: DataRaptor Extract – It allows you to retrieve data from Salesforce. With DataRaptor Turbo Extract, you can restore data from a single Salesforce source DataRaptor Load – It allows you to save data DataRaptor Transform – As the name suggests, it allows you to transform data DataRaptor acts a connecting bridge between Salesforces and OmniScript/ FlexCard. It loads data from Salesforce and sends it to these sources and sends updated data from these back into Salesforce. It can auto-generate Apex REST web services to work seamlessly with external applications. Integration Procedure Integration Procedure is a declarative process that allows you to generate multiple actions with a single hit. It reads data from Salesforce and writes data back to it. With integration procedure, you can also do the same with external systems through REST calls. Integration procedure also allows you to execute Apex code without any user interaction. These are the features of Integration Procedure: Executes functions across multiple data sources such as Salesforce, external systems. Can serve as a data source for OmniScript, FlexCard, REST or Apex. Trims data that is served to the browser from the server reducing data transfer traffic. Process huge amounts of data easily. Allows you to easily load and transform data from third-party sources without any user interaction. Works with clicks not code, which allows for easy integration and configuration. Automatically creates REST endpoints to work seamlessly with external systems. Works seamlessly with Declarative Platform Cache configuration that improves performance and reduces server processing at scale. FlexCards FlexCards is an integral part of Salesforce Industries. FlexCards allows you to create industry-specific UI components catering to specific customer needs. FlexCards uses the LWC framework and allows for easy deployment options via Community Builder and App Builder. FlexCards acts as a data source for DataRaptor, Integration Procedure, REST, Apex etc. When using FlexCards,  only data that is relevant to the user is thrown up based on the configuration. The features of FlexCards are: Displays consolidated, concise, and relevant information. Allows for contextual actions to improve collaboration across business operations Can be tailored to customer preferences across channels and devices Can access and assess data from Salesforce and external applications Has an intuitive code-less declarative editor Auto-creates Lightning Web Components Advantages of Omnistudio. Accelerate innovation with declarative tools that empower you to go digital quickly. Easily deploy industry-specific processes fast to automate interactions Simplify integrations with drag-and-drop functionality with a modular, granular-service oriented approach Build tailored flexible, scalable and branded user interfaces with an intuitive code-less configuration Automate the customer service experience easily with just a few clicks Make your business agile with scalable digital engagements. Create code-less, guided user experiences Allow your users to accomplish complex tasks effortlessly with a flexible, scalable, branded user interface. Easily help them navigate through sales and service processes with quick and personalized responses. Seamlessly integrate with your Salesforce CRM and external  systems. Integrate with external data easily. Use declarative data mapping and REST interfaces to manage complex data structures fast with a drag-and-drop intuitive interface. Connect with external systems to seamlessly bring in data into the tailored, branded experiences created using OmniScript and FlexCards Empower agents with contextual information Streamline and optimize your processes by showing only the data you need, when you need it. Construct guided user interfaces with clicks, not code. Quickly get data into FlexCards from multiple sources. OmniStudio gives you the tools to accelerate value realization. Interaction Console Get easy access to dashboard components that give you a 360 degree view of the entire customer journey and offer insights to help resolve issues faster. IDX Workbench Easily migrate changes and manage cross organizational dependencies and simplify DevOps. Visualize and compare changes across versions in a desktop app. Easily switch components across source control, sandboxes, and production. Omni Analytics Visualize data to understand process performance and identify trends.  Take actions to improve core metrics and KPIs. Project Explorer Structure industry processes by organizing metadata into collections that can be accessed from anywhere in the org. Search and navigate easily across items. At Girikon, a Salesforce Implementation Partner, we recognize the promise that Salesforce Industries and OmniStudio bring for architects. And with Salesforce’s commitment to continued enhancement, it promises enduring productivity and innovation for architects.  Contact us today to learn more.