ERP

17Oct

Deploying Salesforce Einstein Copilot

Best Practices for Safely Deploying Salesforce Einstein Copilot When deploying Salesforce Einstein Copilot, following best practices ensures a secure, efficient, and effective integration of AI into your workflows. Here are the key steps to safely deploy Einstein Copilot: By adhering to these best practices, you can ensure a smooth, secure, and successful deployment of Salesforce Einstein Copilot, enhancing your team’s productivity while maintaining data integrity and security. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 17, 2024in Data, Salesforce, Salesforce Einstein

16Oct

NYT Issues Cease-and-Desist Letter to Perplexity AI

NYT Issues Cease-and-Desist Letter to Perplexity AI Over Alleged Unauthorized Content Use The New York Times (NYT) has issued a cease-and-desist letter to Perplexity AI, accusing the AI-powered search startup of using its content without permission. This move marks the second time the NYT has confronted a company for allegedly misappropriating its material. According to reports, the Times claims Perplexity is accessing and utilizing its content to generate summaries and other outputs, actions it argues infringe on copyright laws. The startup now has two weeks to respond to the accusations. A Growing Pattern of Tensions Perplexity AI is not the only publisher-facing scrutiny. In June, Forbes threatened legal action against the company, alleging “willful infringement” by using its text and images. In response, Perplexity launched the Perplexity Publishers’ Program, a revenue-sharing initiative that collaborates with publishers like Time, Fortune, and The Texas Tribune. Meanwhile, the NYT remains entangled in a separate lawsuit with OpenAI and its partner Microsoft over alleged misuse of its content. A Strategic Legal Approach The NYT’s decision to issue a cease-and-desist letter instead of pursuing an immediate lawsuit signals a calculated move. “Cease-and-desist approaches are less confrontational, less expensive, and faster,” said Sarah Kreps, a professor at Cornell University. This method also opens the door for negotiation, a pragmatic step given the uncharted legal terrain surrounding generative AI and copyright law. Michael Bennett, a responsible AI expert from Northeastern University, echoed this view, suggesting that the cease-and-desist approach positions the Times to protect its intellectual property while maintaining leverage in ongoing legal battles. If the NYT wins its case against OpenAI, Bennett added, it could compel companies like Perplexity to enter financial agreements for content use. However, if the case doesn’t favor the NYT, the publisher risks losing leverage. The letter also serves as a warning to other AI vendors, signaling the NYT’s determination to safeguard its intellectual property. Perplexity’s Defense: Facts vs. Expression Perplexity AI has countered the NYT’s claims by asserting that its methods adhere to copyright laws. “We aren’t scraping data for building foundation models but rather indexing web pages and surfacing factual content as citations,” the company stated. It emphasized that facts themselves cannot be copyrighted, drawing parallels to how search engines like Google operate. Kreps noted that Perplexity’s approach aligns closely with other AI platforms, which typically index pages to provide factual answers while citing sources. “If Perplexity is culpable, then the entire AI industry could be held accountable,” she said, contrasting Perplexity’s citation-based model with platforms like ChatGPT, which often lack transparency about data sources. The Crux of the Copyright Argument The NYT’s cease-and-desist letter centers on the distinction between facts and the creative expression of facts. While raw facts are not protected under copyright, the NYT claims that its specific interpretation and presentation of those facts are. Vincent Allen, an intellectual property attorney, explained that if Perplexity is scraping data and summarizing articles, it may involve making unauthorized copies of copyrighted content, strengthening the NYT’s claims. “This is a big deal for content providers,” Allen said, “as they want to ensure they’re compensated for their work.” Implications for the AI Industry The outcome of this dispute could set a precedent for how AI platforms handle content generated by publishers. If Perplexity’s practices are deemed infringing, it could reshape the operational models of similar AI vendors. At the heart of the debate is the balance between fostering innovation in AI and protecting intellectual property, a challenge that will likely shape the future of generative AI and its relationship with content creators. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 16, 2024in Data, Generative AI, Google, Laws

16Oct

Third Wave of AI at Salesforce

The Third Wave of AI at Salesforce: How Agentforce is Transforming the Landscape At Dreamforce 2024, Salesforce unveiled several exciting innovations, with Agentforce taking center stage. This post explores the key changes and enhancements designed to improve efficiency and elevate customer interactions. Introducing Agentforce Agentforce is a customizable AI agent builder that empowers organizations to create and manage autonomous agents for various business tasks. But what exactly is an agent? An agent is akin to a chatbot but goes beyond traditional capabilities. While typical chatbots are restricted to scripted responses and predefined questions, Agentforce agents leverage large language models (LLMs) and generative AI to comprehend customer inquiries contextually. This enables them to make independent decisions, whether processing requests or resolving issues using real-time data from your company’s customer relationship management (CRM) system. The Role of Atlas At the heart of Agentforce’s functionality lies the Atlas reasoning engine, which acts as the operational brain. Unlike standard assistive tools, Atlas is an agentic system with the autonomy to act on behalf of the user. Atlas formulates a plan based on necessary actions and can adjust that plan based on evaluations or new information. When it’s time to engage, Atlas knows which business processes to activate and connects with customers or employees via their preferred channels. This sophisticated approach allows Agentforce to significantly enhance operational efficiency. By automating routine inquiries, it frees up your team to focus on more complex tasks, delivering a smoother experience for both staff and customers. Speed to Value One of Agentforce’s standout features is its emphasis on rapid implementation. Many AI projects can be resource-intensive and take months or even years to launch. However, Agentforce enables quick deployment by leveraging existing Salesforce infrastructure, allowing organizations to implement solutions rapidly and with greater control. Salesforce also offers pre-built Agentforce agents tailored to specific business needs—such as Service Agent, Sales Development Representative Agent, Sales Coach, Personal Shopper Agent, and Campaign Agent—all customizable with the Agent Builder. Agentforce for Service and Sales will be generally available starting October 25, 2024, with certain elements of the Atlas Reasoning Engine rolling out in February 2025. Pricing begins at $2 per conversation, with volume discounts available. Transforming Customer Insights with Data Cloud and Marketing Cloud Dreamforce also highlighted enhancements to Data Cloud, Salesforce’s backbone for all cloud products. The platform now supports processing unstructured data, which constitutes up to 90% of company data often overlooked by traditional reporting systems. With new capabilities for analyzing various unstructured formats—like video, audio, sales demos, customer service calls, and voicemails—businesses can derive valuable insights and make informed decisions across Customer 360. Furthermore, Data Cloud One enables organizations to connect siloed Salesforce instances effortlessly, promoting seamless data sharing through a no-code, point-and-click setup. The newly announced Marketing Cloud Advanced edition serves as the “big sister” to Marketing Cloud Growth, equipping larger marketing teams with enhanced features like Path Experiment, which tests different content strategies across channels, and Einstein Engagement Scoring for deeper insights into customer behavior. Together, these enhancements empower companies to engage customers more meaningfully and measurably across all touchpoints. Empowering the Workforce Through Education Salesforce is committed to making AI accessible for all. They recently announced free instructor-led courses and AI certifications available through 2025, aimed at equipping the Salesforce community with essential AI and data management skills. To support this initiative, Salesforce is establishing AI centers in major cities, starting with London, to provide hands-on training and resources, fostering AI expertise. They also launched a global Agentforce World Tour to promote understanding and adoption of the new capabilities introduced at Dreamforce, featuring repackaged sessions from the conference and opportunities for specialists to answer questions. The Bottom Line What does this mean for businesses? With the rollout of Agentforce, along with enhancements to Data Cloud and Marketing Cloud, organizations can operate more efficiently and connect with customers in more meaningful ways. Coupled with a focus on education through free courses and global outreach, getting on board has never been easier. If you’d like to discuss how we can help your business maximize its potential with Salesforce through data and AI, connect with us and schedule a meeting with our team. Legacy systems can create significant gaps between operations and employee needs, slowing lead processes and resulting in siloed, out-of-sync data that hampers business efficiency. Responding to inquiries within five minutes offers a 75% chance of converting leads into customers, emphasizing the need for rapid, effective marketing responses. Salesforce aims to help customers strengthen relationships, enhance productivity, and boost margins through its premier AI CRM for sales, service, marketing, and commerce, while also achieving these goals internally. Recognizing the complexity of its decade-old processes, including lead assignment across three systems and 2 million lines of custom code, Salesforce took on the role of “customer zero,” leveraging Data Cloud to create a unified view of customers known as the “Customer 360 Truth Profile.” This consolidation of disparate data laid the groundwork for enterprise-wide AI and automation, improving marketing automation and reducing lead time by 98%. As Michael Andrew, SVP of Marketing Decision Science at Salesforce, noted, this initiative enabled the company to provide high-quality leads to its sales team with enriched data and AI scoring while accelerating time to market and enhancing data quality. Embracing Customer Zero “Almost exactly a year ago, we set out with a beginner’s mind to transform our lead automation process with a solution that would send the best leads to the right sales teams within minutes of capturing their data and support us for the next decade,” said Andrew. The initial success metric was “speed to lead,” aiming to reduce the handoff time from 20 minutes to less than one minute. The focus was also on integrating customer and lead data to develop a more comprehensive 360-degree profile for each prospect, enhancing lead assignment and sales rep productivity. Another objective was to boost business agility by cutting the average time to implement assignment changes from four weeks to mere days. Accelerating Success with

October 16, 2024in Data, Enterprise, Generative AI, Google, Google Analytics, Marketing Automation, Salesforce

15Oct

Secret ChatGPT Prompts

Only 1% of ChatGPT Users Know These Secret Prompts That 10X Response Quality Let’s be honest. Generic prompts like:“Write a 1500-word article on ‘Top 10 Foods That DESTROY Your KIDNEY’” …are not tapping into the true potential of ChatGPT. But what if such prompts could deliver incredible results with just a few tweaks? The answer lies in specialized prompts—a set of strategies that amplify the depth, clarity, and quality of ChatGPT’s output. Below is a collection of 7 powerful prompts that can instantly transform your experience with ChatGPT. These are personal favorites that have delivered game-changing results time and time again. Get ready—these are about to blow your writing out of the water. 1. “Do not start writing yet. First, explain everything I wanted you to do in this prompt in detail.” How to Use It:This prompt ensures that ChatGPT fully understands your request before generating a response. By asking for an explanation of its interpretation, you can spot misunderstandings and align its output with your expectations. Why It Works:When you review ChatGPT’s interpretation, you can fine-tune the original instructions, guaranteeing better results. 2. “I need this written in a human tone. Humans have fun when they write—robots don’t. Engagement is the highest priority. Be conversational, empathetic, and occasionally humorous. Use idioms, metaphors, anecdotes, and natural dialogue.” How to Use It:Add this to prompts for content that needs to feel authentic and engaging, such as articles or blog posts. Why It Works:ChatGPT can sometimes sound too robotic. This prompt encourages a more natural, relatable tone, making the output resonate with readers. 3. “Before you answer, ask me any missing information you need to understand my request better.” How to Use It:Follow up your prompt with this request to encourage ChatGPT to identify gaps in your instructions. Why It Works:Most prompts miss critical details, leading to subpar results. This approach ensures ChatGPT has all the context it needs to produce a tailored response. 4. “Criticize yourself.” How to Use It:After receiving a response, ask ChatGPT to critique its own work. Why It Works:ChatGPT’s self-critique often surfaces new ideas and reveals areas for improvement that you might not have considered. 5. “Why did you write what you wrote? Provide a detailed analysis and breakdown in a table. Include suggestions for improvement based on my original prompt.” How to Use It:After receiving a response, ask for an explanation of the rationale behind its choices. Why It Works:Understanding the “why” behind ChatGPT’s response gives you insights into its logic and suggestions for fine-tuning the output further. 6. “Before you answer this, highlight 20 potential risks or blind spots I might not have considered based on my request.” How to Use It:Use this prompt to anticipate potential pitfalls or overlooked details. Why It Works:ChatGPT can act as a second set of eyes, helping you identify areas that could be improved or clarified before executing your ideas. 7. “Identify areas in this article where examples, analogies, or case studies would improve understanding.” How to Use It:After generating content, ask ChatGPT to pinpoint where additional context would enhance clarity or engagement. Why It Works:Adding relatable examples and analogies strengthens your message and helps readers better connect with your content. These 7 prompts are your secret weapon to unlock ChatGPT’s full potential. By incorporating them into your workflow, you’ll create smarter, richer, and more impactful content that’s a cut above the rest. Pro Tip: Combine multiple prompts for even more refined outputs! Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 15, 2024in Salesforce

14Oct

Battle of Copilots

Salesforce is directly challenging Microsoft in the growing battle of AI copilots, which are designed to enhance customer experience (CX) across key business functions like sales and support. In this competitive landscape, Salesforce is taking on not only Microsoft but also major AI rivals such as Google Gemini, OpenAI GPT, and IBM watsonx. At the heart of this strategy is Salesforce Agentforce, a platform that leverages autonomous decision-making to meet enterprise demands for data and AI abstraction. Salesforce Dreamforce Highlights One of the most significant takeaways from last month’s Dreamforce conference in San Francisco was the unveiling of autonomous agents, bringing advanced GenAI capabilities to the app development process. CEO Marc Benioff and other Salesforce executives made it clear that Salesforce is positioning itself to compete with Microsoft’s Copilot, rebranding and advancing its own AI assistant, previously known as Einstein AI. Microsoft’s stronghold, however, lies in Copilot’s seamless integration with widely used products like Teams, Outlook, PowerPoint, and Word. Furthermore, Microsoft has established itself as a developer’s favorite, especially with GitHub Copilot and the Azure portfolio, which are integral to app modernization in many enterprises. “Salesforce faces an uphill battle in capturing market share from these established players,” says Charlotte Dunlap, Research Director at GlobalData. “Salesforce’s best chance lies in highlighting the autonomous capabilities of Agentforce—enabling businesses to automate more processes, moving beyond basic chatbot functions, and delivering a personalized customer experience.” This emphasis on autonomy is vital, given that many enterprises are still grappling with the complexities of emerging GenAI technologies. Dunlap points out that DevOps teams are struggling to find third-party expertise that understands how GenAI fits within existing IT systems, particularly around security and governance concerns. Salesforce’s focus on automation, combined with the integration prowess of MuleSoft, positions it as a key player in making GenAI tools more accessible and intuitive for businesses. Elevating AI Abstraction and Automation Salesforce has increasingly focused on the idea of abstracting data and AI, exemplified by its Data Cloud and low-level UI capabilities. Now, with models like the Atlas Reasoning Engine, Salesforce is looking to push beyond traditional AI assistants. These tools are designed to automate complex, previously human-dependent tasks, spanning functions like sales, service, and marketing. Simplifying the Developer Experience The true measure of Salesforce’s success in its GenAI strategy will emerge in the coming months. The company is well aware that its ability to simplify the developer experience is critical. Enterprises are looking for more than just AI innovation—they want thought leadership that can help secure budget and executive support for AI initiatives. Many companies report ongoing struggles in gaining that internal buy-in, further underscoring the importance of strong, strategic partnerships with technology providers like Salesforce. In its pursuit to rival Microsoft Copilot, Salesforce’s future hinges on how effectively it can build on its track record of simplifying the developer experience while promoting the unique autonomous qualities of Agentforce. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 14, 2024in AI Tools, Data, Enterprise, Google, Mulesoft, Salesforce, Salesforce Copilots, Salesforce Optimization, Technology

13Oct

AI and Legacy

In most new application builds, AI is rarely considered an active consumer. The prevailing assumption seems to be that AI is just a variation of reporting, which essentially translates to “not my problem” for application developers. In this mindset, the data platform gets treated like an afterthought, receiving the “exhaust fumes” of the application without much concern for data quality. Even when data or AI is acknowledged as important, it’s often sidelined, with data becoming one of the first things sacrificed during the development process. In the past, this was merely a “minor” problem that led to the rise of the data quality industry. AI and Legacy. But as we move forward, this will become a significant issue due to one undeniable fact: AI will be the primary consumer of applications and data. Old Thinking Creates Instant Legacy What this means is that if you’re building a new application—whether it’s a website, ERP, CRM, or anything else—and you’re not considering AI as a user, you’re actively choosing to implement a legacy system. Even if your system has an AI solution baked in, if the core application isn’t designed for a data-driven world, the best you’ll achieve is an AI sidecar—just a nice wrapper, but limited in scope. Tools like Microsoft Copilot or Salesforce Agentforce, for instance, can easily be implemented in a way that minimizes or even eliminates opportunities for AI to thrive. If you’re building applications that treat data as merely a reporting tool and assume AI is a downstream consumer, you’re engaging in legacy thinking in a world increasingly powered by AI. Don’t Build Legacy Systems Avoiding legacy systems isn’t difficult. If you believe AI and data are important, treat them as such from the outset. This boils down to one simple principle: Design for the destination. If you think AI will be a primary consumer of applications in the next one, two, or five years, you should design your applications with that challenge in mind. This means considering AI personas, figuring out how AI assistants will integrate into human workflows, and planning how AI automation bots will function within the system. It also requires embracing a crucial decision: Your design should prioritize data, and assume AI is a primary consumer. This doesn’t mean just designing a robust database schema. It means ensuring your application’s operational reality can accurately reflect the business situation for both human and AI users. It’s not about technical database design—it’s about understanding the business’s accountability for digital accuracy and establishing the mechanisms to maintain that accuracy and represent it effectively. Building Legacy Is a Choice Everyone Is Making To be clear, this isn’t about adopting some “holistic” view or designing for every possible scenario. It’s about designing from a data and digital perspective first. Instead of treating use cases or business processes as the main design focus, the primary design thread should be the ability to reflect the reality of the business. Use cases and business processes still matter at the execution level, but they should not drive application design in a data-driven, AI-enabled world. You must assume that AI will be the primary consumer of your application and design accordingly, rather than focusing solely on human users and screens. Right now, nearly every application is still built as though data is a byproduct of transactions, with the assumption that AI is merely a sidecar, not an active participant. AI and Legacy. In the words of Sir Humphrey, that is a “courageous” decision. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 13, 2024in Data, Salesforce

12Oct

Salesforce Powering EVPassport

EVPassport, a global leader in EV charging networks, announced an expanded partnership with Salesforce to enhance its customer experience through the deployment of Salesforce Service Cloud. This initiative solidifies EVPassport’s standing as a top provider in the EV charging space, recognized for customer satisfaction, loyalty, and reliability. With Salesforce Service Cloud, EVPassport can deliver more personalized, efficient service and support to its enterprise, commercial customers, and electric vehicle drivers. The platform enables deeper insights into each driver’s journey, resulting in a seamless, tailored experience. Hooman Shahidi, co-founder and CEO of EVPassport, highlighted the significance of Salesforce in driving the company’s next-generation mobility experience, stating, “As we build the mobility experience of tomorrow, having the right partners is crucial. Salesforce’s innovative solutions will help us exceed the evolving needs of our customers, sites, and communities.” By leveraging Salesforce’s AI, data, and CRM capabilities, EVPassport aims to strengthen customer connections and improve operational efficiency, ensuring a forward-thinking approach to EV charging for years to come. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 12, 2024in Data, Enterprise, Salesforce, Salesforce Service Cloud

12Oct

SingleStore Acquires BryteFlow

SingleStore Acquires BryteFlow, Paving the Way for Real-Time Analytics and Next-Gen AI Use Cases SingleStore, the world’s only database designed to transact, analyze, and search petabytes of data in milliseconds, has announced its acquisition of BryteFlow, a leading data integration platform. This move enhances SingleStore’s capabilities to ingest data from diverse sources—including SAP, Oracle, and Salesforce—while empowering users to operationalize data from their CRM and ERP systems. With the acquisition, SingleStore will integrate BryteFlow’s data integration technology into its core offering, launching a new experience called SingleConnect. This addition will complement SingleStore’s existing functionalities, enabling users to gain deeper insights from their data, accelerate real-time analytics, and support emerging generative AI (GenAI) use cases. “This acquisition marks a pivotal step in our mission to deliver unparalleled speed, scale, and simplicity,” said Raj Verma, CEO of SingleStore. “Customer demands are evolving rapidly due to shifts in big data storage formats and advancements in generative AI. We believe that data is the foundation of all intelligence, and SingleConnect comes at a perfect time to address this need.” BryteFlow’s platform provides scalable change data capture (CDC) capabilities across multiple data sources, ensuring data integrity between source and target. It integrates seamlessly with major cloud platforms like AWS, Microsoft Azure, and Google Cloud, making it a powerful tool for cloud-based data warehouses and data lakes. Its no-code interface allows for easy and accessible data integration, ensuring that existing BryteFlow customers will experience uninterrupted service and ongoing support. “By combining BryteFlow’s real-time data integration expertise with SingleStore’s capabilities, we aim to help global organizations extract maximum value from their data and scale modern applications,” said Pradnya Bhandary, CEO of BryteFlow. “With SingleConnect, developers will find it easier and faster to access enterprise data sources, tackle complex workloads, and deliver exceptional experiences to their customers.” Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 12, 2024in Data, Enterprise, Generative AI, Google, Salesforce, Technology

AI is revolutionizing BI by transforming it from a retrospective tool into a proactive, real-time decision-making engine.

11Oct

AI Startup Sierra

Bret Taylor, the board chairman of OpenAI, appeared on CNBC’s “Squawk on the Street” to discuss his AI startup, Sierra, which he co-founded in March 2023. Sierra focuses on helping businesses build AI agents that can directly interact with customers, offering capabilities such as answering questions, automating processes, and performing tasks traditionally handled on websites. “This is how companies will offer a branded customer experience capable of having conversations and handling everything you can do on the website,” Taylor explained. Sierra is already valued at approximately $4 billion, and Taylor expressed enthusiasm for building a long-lasting enterprise. Commenting on the current “AI wave,” Taylor predicted the rise of at least 10 “meaningful” enterprise software companies and at least one trillion-dollar consumer company. He also touched on the ongoing discussion around tech regulation, emphasizing that Silicon Valley should focus more on empowering smaller tech companies rather than breaking up larger ones. He noted that the U.S. remains a top destination for entrepreneurs due to its access to capital and relatively light regulation, warning that overly complex regulations could inadvertently strengthen incumbents by increasing challenges for startups. Taylor’s role at OpenAI became more prominent after CEO Sam Altman was temporarily ousted in November. Since then, he has been guiding the company through a period of transition, including leadership changes and its shift toward becoming a for-profit entity. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 11, 2024in Enterprise

09Oct

Smartsheet and AWS Collaborate

Smartsheet and AWS Collaborate to Enhance AI-Driven Decision-Making with New Amazon Q Business Connector October 8, 2024 — During its annual ENGAGE customer conference, Smartsheet (NYSE: SMAR), the enterprise work management platform, announced a partnership with AWS to introduce a new connector that integrates Smartsheet data with Amazon Q Business. This generative AI-powered assistant can answer questions, provide summaries, generate content, and securely complete tasks using data from customers’ enterprise systems. This integration will allow Amazon Q Business users to access insights about their projects and processes managed in Smartsheet, facilitating a cohesive search experience that empowers employees to make informed, data-driven decisions. Smartsheet and AWS Collaborate. As organizations increasingly recognize the importance of data-driven decisions, data silos remain a major hurdle. Research from Salesforce in 2024 indicates that only about 28% of business applications are interconnected. The new connector aims to address this issue by securely merging Smartsheet data with other sources integrated into Amazon Q Business, such as Salesforce, Slack, Microsoft Teams, and AWS. This will benefit over 13 million Smartsheet users globally, including around 85% of the 2024 Fortune 500 companies, allowing them to access their work management data, including sheets, conversations, and files, through AWS’s generative AI-powered assistant. This integration enhances decision-making, productivity, and efficiency. Smartsheet and AWS Collaborate “The Smartsheet connector furthers our strategy to securely integrate Smartsheet with leading enterprise AI tools, allowing customers to work seamlessly across their business applications,” said Ben Canning, SVP of Product Experiences at Smartsheet. “By combining our flexible data model with Amazon Q Business, we’re unlocking access to work management data for our mutual customers, enabling them to focus on achieving business outcomes without worrying about data storage.” For instance, service operations managers can utilize the new connector to manage complex projects more effectively. By posing specific questions to the Amazon Q Business assistant, teams can gain insights from various data sources, including sheets, conversations, and attachments in Smartsheet. The AI assistant conducts thorough searches while respecting access permissions, saving time and enhancing project oversight. This streamlined approach improves client retention, accuracy, and overall service quality. “Generative AI presents a unique opportunity for organizations to transform their internal workflows. The key is securely accessing their own data, regardless of its location or format,” stated Dilip Kumar, Vice President of Amazon Q Business at AWS. “Many enterprises use Smartsheet as their primary collaboration hub, storing billions of rows of data. Allowing Amazon Q Business users to interact with their Smartsheet data in a simple, secure manner boosts productivity, analysis, and decision-making.” “Generative AI is driving a significant shift in how enterprise knowledge is stored, accessed, and utilized,” noted Dion Hinchcliffe, VP of the CIO Practice at The Futurum Group. “This transition offers a chance to redefine what’s possible in data management. A strategic, informed approach to adopting this technology is crucial. By integrating work management data into Amazon Q Business, Smartsheet and AWS are creating a unified AI search experience across their knowledge base, unlocking the true potential of their data.” Empowering Teams to Achieve More with Generative AI Smartsheet is collaborating with industry leaders like AWS to develop AI capabilities that help enterprises manage their critical tasks more strategically and efficiently. Earlier this year, Smartsheet implemented Amazon Q Business internally to enhance knowledge management and boost employee productivity in the cloud. The Smartsheet connector exemplifies how both organizations are delivering powerful AI tools that revolutionize team workflows. Smartsheet continues to integrate generative AI throughout its platform, designed with practicality, transparency, and customer needs in mind. Smartsheet’s AI tools enable organizations to swiftly extract insights from data, create automated processes, generate text and summaries, and accomplish more with the AI assistant. Through the end of December, Smartsheet is offering its entire suite of AI tools to all customers, allowing everyone to leverage AI’s capabilities within the platform. The Smartsheet connector is currently available to Amazon Q Business customers in public preview. About Smartsheet Smartsheet is a modern enterprise work management platform trusted by millions globally, including approximately 85% of the 2024 Fortune 500 companies. As a pioneering leader in its category, Smartsheet delivers powerful solutions that drive performance and foster innovation. Visit www.smartsheet.com for more information. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 9, 2024in AI Tools, Data, Enterprise, Generative AI, Salesforce, Technology

04Oct

Databricks Tools

Databricks recently introduced Databricks Apps, a toolkit designed to simplify AI and data application development. By integrating native development platforms and offering automatic provisioning of serverless compute, the toolkit enables customers to more easily develop and deploy applications. Databricks Apps builds on the existing capabilities of Mosaic AI, which allows users to integrate large language models (LLMs) with their enterprise’s proprietary data. However, the ability to develop interactive AI applications, such as generative AI chatbots, was previously missing. Databricks Apps addresses this gap, allowing developers to build and deploy custom applications entirely within the secure Databricks environment. According to Donald Farmer, founder and principal of TreeHive Strategy, Databricks Apps removes obstacles like the need to set up separate infrastructure for development and deployment, making the process easier and more efficient. The new features allow companies to go beyond implementing AI/ML models and create differentiated applications that leverage their unique data sets. Kevin Petrie, an analyst at BARC U.S., highlighted the significance of Databricks Apps in helping companies develop custom AI applications, which are essential for maintaining a competitive edge. Databricks, founded in 2013, was one of the pioneers of the data lakehouse storage format, and over the last two years, it has expanded its platform to focus on AI and machine learning (ML) capabilities. The company’s $1.3 billion acquisition of MosaicML in June 2023 was a key milestone in building its AI environment. Databricks has since launched DBRX, its own large language model, and introduced further functionalities through product development. Databricks Apps, now available in public preview on AWS and Azure, advances these AI development capabilities, simplifying the process of building applications within a single platform. Developers can use frameworks like Dash, Flask, Gradio, Shiny, and Streamlit, or opt for integrated development environments (IDEs) like Visual Studio Code or PyCharm. The toolkit also provides prebuilt Python templates to accelerate development. Additionally, applications can be deployed and managed directly in Databricks, eliminating the need for external infrastructures. Databricks Apps includes security features such as access control and data lineage through the Unity Catalog. Farmer noted that the support for popular developer frameworks and the automatic provisioning of serverless compute could significantly impact the AI development landscape by reducing the complexity of deploying data architectures. While competitors like AWS, Google Cloud, Microsoft, and Snowflake have also made AI a key focus, Farmer pointed out that Databricks’ integration of AI tools into a unified platform sets it apart. Databricks Apps further enhances this competitive advantage. Despite the added capabilities of Databricks Apps, Petrie cautioned that developing generative AI applications still requires a level of expertise in data, AI, and the business domain. While Databricks aims to make AI more accessible, users will still need substantial knowledge to effectively leverage these tools. Databricks’ vice president of product management, Shanku Niyogi, explained that the new features in Databricks Apps were driven by customer feedback. As enterprise interest in AI grows, customers sought easier ways to develop and deploy internal data applications in a secure environment. Looking ahead, Databricks plans to continue investing in simplifying AI application development, with a focus on enhancing Mosaic AI and expanding its collaborative AI partner ecosystem. Farmer suggested that the company should focus on supporting nontechnical users and emerging AI technologies like multimodal models, which will become increasingly important in the coming years. The introduction of Databricks Apps marks a significant step forward in Databricks’ AI and machine learning strategy, offering users a more streamlined approach to building and deploying AI applications. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 4, 2024in AI Tools, Data, Enterprise, Generative AI, Google, Snowflake

03Oct

Marc Benioff Interviewed

Salesforce, now one of the most influential companies in tech history, was founded by Marc Benioff after his successful tenure at Oracle. Having witnessed the potential of the internet, Benioff realized it would usher in a new era for delivering enterprise software through the cloud. However, this new approach demanded a complete overhaul of traditional business models, marketing strategies, and software development practices. Salesforce would embody this transformation, evolving over the decades into a platform supporting a diverse array of enterprise applications. Today, Salesforce’s flagship initiative is Agentforce, a pioneering wave of AI agents built on the Salesforce platform. This initiative, which I covered in detail earlier this month, exemplifies Benioff’s forward-thinking vision for AI. He passionately argues that Salesforce is well-positioned to lead in this space, and his insights on AI and its potential are as compelling as they are thought-provoking. Before diving into Agentforce and Benioff’s views on AI, it’s important to explore his early life and the founding of Salesforce. Benioff’s path to becoming the CEO of one of the most powerful software companies in the world was shaped by an early interest in technology. His first foray into software development was creating an app called “How to Juggle,” which he sold for $75 to CLOAD Magazine in Goleta, California. This early success marked the beginning of a long career in tech. Benioff went on to establish an Atari game company called Liberty Software and later wrote assembly code for the Mac as part of an internship. Despite his success as a software developer, he transitioned to a leadership role after realizing his interest in the broader business of technology. He credits his time at Oracle, where he learned the intricacies of sales, marketing, and customer communication, as critical to shaping his vision for Salesforce. Oracle, during Larry Ellison’s prime, was an ideal place to hone these business skills, which Benioff would later apply to revolutionize the enterprise software space. With this foundation, Benioff founded Salesforce, a company that has fundamentally changed the way businesses engage with technology. The company’s success lies not just in its cloud-based software, but in its ongoing evolution to address new challenges, including the AI-powered Agentforce initiative, which stands at the forefront of Salesforce’s future growth. Benioff’s journey, from a young programmer to the CEO of a global tech giant, is a testament to his visionary approach and adaptability in an ever-changing tech landscape. Marc Benioff’s early entrepreneurial instincts were evident even before he fully embraced the title of entrepreneur. From a young age, he knew he wanted to build something of his own, though he hadn’t yet honed the full set of skills needed to succeed in business. He had a knack for technology, excelling as a programmer working in assembly code, but his mentors, including university professors and colleagues at Apple, recognized that being an entrepreneur required more than just technical ability. They encouraged him to develop his sales, marketing, and business acumen. His early exposure to these lessons was pivotal in shaping his future trajectory. Benioff’s transition from a programmer to a business leader began when he sought advice from Bill Jost at Apple, who connected him with Gary Gibson, an Oracle executive. After a memorable and unexpected interview, Benioff joined Oracle, starting with a role answering calls at the company’s 800-number. He quickly moved into sales and marketing, eventually working directly with Larry Ellison, who would become a significant mentor over the next 13 years. Benioff’s success at Oracle set the stage for his eventual departure to start Salesforce in 1999. In the mid-1990s, while at Oracle, Benioff had an epiphany while using a web browser. The internet was transforming how software could be delivered, and Benioff saw the potential for a new business model based on cloud computing. At this time, Oracle was focused on the network computer—a vision Benioff did not fully share. After discussing his ideas with Larry Ellison and taking some time off for reflection and research, Benioff recognized that the world was on the cusp of a major shift in technology. He felt compelled to create something new that would leverage the internet, offering software over the web through a subscription model. During his time off, Benioff traveled to Hawaii, reflecting on the future of the tech industry and contemplating ideas. He also experimented with domain names, purchasing You.com and later gifting it to a friend who turned it into a search and AI company. Benioff returned to Larry Ellison to share his vision of a cloud-based business model and later found inspiration from spiritual gurus during a trip to India, who reminded him that success in business should also be grounded in positive values. Benioff’s experience led to the founding of Salesforce with its revolutionary 1-1-1 Model—dedicating 1% of equity, profit, and employee time to philanthropy. Salesforce also embraced emerging technologies such as social, mobile, and AI, and created a new business model through subscription-based services. This combination of technological innovation and a strong sense of social responsibility has set Salesforce apart, attracting both admiration and emulation from other companies. Benioff’s Career Benioff’s career is a testament to the power of surrounding oneself with great people, continuing to learn, and having a clear vision. His leadership at Salesforce has been guided by values he believes are crucial to the company’s success and its ability to make a positive impact on the world. His insights on the Innovator’s Dilemma, a concept popularized by Clayton Christensen, highlight the challenges companies face as they evolve with changing technologies. While Salesforce’s core principles remain intact, the company has continued to adapt to new technology paradigms, ensuring it remains at the forefront of innovation in the software industry. Marc Benioff (MB) recently shared his excitement about the future of AI and its potential to revolutionize business and technology. He explained that, from a business perspective, this is the most thrilling moment in his career. AI, according to him, will transform how enterprises operate, making them more

October 3, 2024in Agentforce Platform, Data, Enterprise, Google, Hyperforce, Salesforce, Salesforce Data Cloud, Snowflake, Technology

03Oct

Supercharged Sales and Service Excellence

When sales and service teams are seamlessly aligned, organizations can transform every service interaction into a powerful opportunity to drive revenue and build customer loyalty. By delivering contextual, personalized offers at the right time, businesses can turn each customer touchpoint into a chance to solve problems, create value, and enhance engagement. With the help of real-time data and AI, we move beyond treating customer interactions as isolated events. Instead, we focus on understanding the unique needs and preferences of each customer, whether they’re reaching out for support, visiting a store, or engaging online. Every touchpoint becomes an opportunity to deliver tailored solutions, strengthen loyalty, and increase revenue. These examples are just a glimpse of the solutions we help our clients deploy. With our deep expertise in AI implementation and industry-specific insights, Tectonic is ideally positioned to guide you through activating AI agents that build on your successes. Our extensive experience across diverse sectors enables us to identify the most impactful opportunities for AI, ensuring tailored solutions that align with your business strategy. Tectonic’s proven approach ensures AI agents are deployed efficiently and effectively, driving ROI and delivering measurable results. Agentforce: Open, Extensible, and Transformative Agentforce is designed to foster smooth interactions between agents created on the platform and external agents and applications. With integration into Salesforce Data Cloud, it enables real-time data access for better, faster decision-making. Tectonic can help facilitate this interconnectivity across various channels and platforms, ensuring seamless operations. In a society that prioritizes digital, artificial intelligence is changing sales and service tactics. Adopting AI agents is crucial for business leaders to keep ahead of the competition and develop more effective and efficient methods of customer and employee support. AI agents are not just upgrades—they are transformative forces that redefine what’s possible. They empower organizations to move from envisioning possibilities to realizing a future of enhanced sales performance, streamlined operations, and unmatched customer satisfaction, all powered by AI. Salesforce’s Agentforce: Scaling Your Workforce with Autonomous AI Agents Agentforce provides fully customizable autonomous AI agents that can integrate with enterprise data and take action across sales, service, marketing, and commerce. The Agent Builder allows users to create agents that automate any business process, in any industry, using existing Salesforce tools such as workflows, Apex code, and prompt templates. Leading companies like The Adecco Group, BACA Systems, OpenTable, Saks, and Wiley are already leveraging Agentforce Service Agents to deliver faster, more personalized customer responses while improving operational efficiency. Salesforce (NYSE: CRM), the world’s #1 AI CRM, has announced the general availability of Agentforce. This new platform layer enables businesses to create and deploy AI agents that autonomously take action across any business function. Unlike traditional chatbots and copilots, Agentforce agents possess advanced reasoning abilities to make decisions and take actions such as resolving customer issues, qualifying sales leads, and optimizing marketing efforts. These agents operate independently—triggered by changes in data, business rules, pre-built automations, or external signals from APIs. Agentforce includes out-of-the-box agents that can be easily customized and deployed with low-code or no-code tools, working around the clock across any channel. The first of these, the Agentforce Service Agent, outperforms traditional chatbots by handling a wide range of tasks—from simple to complex—using pre-built topics and actions for customer support. These agents are fully customizable to serve various industries, such as retail with order management or financial services with billing and payment support. “Agentforce is redefining business possibilities, ushering in an era of AI-driven abundance and limitless workforces that enhance every employee’s capabilities, strengthen customer relationships, and fuel unprecedented growth,” said Marc Benioff, Chair and CEO of Salesforce. “Built on Salesforce’s trusted, fully customizable platform—integrating enterprise data, metadata, AI models, workflows, security, and applications—Agentforce is everything AI was meant to be.” The Power of Agentforce With Agentforce, there’s no need for DIY AI. Unlike other platforms that require complex integrations and custom builds, Agentforce is natively built into the Salesforce Platform. Customers can instantly convert their existing Flows, prompt templates, Apex code, and APIs into agent actions, seamlessly connecting to enterprise data and security models. With the added power of native tools like Data Cloud, Slack, and MuleSoft, Agentforce offers a streamlined and efficient approach to scaling your workforce with AI. The new Agent Builder empowers Salesforce admins and developers to easily create AI agents with natural language instructions and guardrails, enabling even more customization and control. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 3, 2024in Agentforce Platform, Data, Enterprise, Mulesoft, Salesforce, Salesforce Data Cloud

02Oct

Anthropic’s New Approach to RAG

advanced RAG methodology demonstrates how AI can overcome traditional challenges, delivering more precise, context-aware responses while maintaining efficiency and scalability.

October 2, 2024in Data

30Sep

Predictive Analytics in Salesforce

Predictive Analytics in Salesforce: Enhancing Decision-Making with AI In an ever-changing business environment, companies seek tools to forecast trends and anticipate challenges, enabling them to remain competitive. Predictive analytics, powered by Salesforce’s AI capabilities, offers a cutting-edge solution for these needs. In this guide, we’ll explore how predictive analytics works and how Salesforce empowers businesses to make smarter, data-driven decisions. What is Predictive Analytics? Predictive analytics uses historical data, statistical modeling, and machine learning to forecast future outcomes. With the vast amount of data organizations generate—ranging from transaction logs to multimedia—unifying this information can be challenging due to data silos. These silos hinder the development of accurate predictive models and limit Salesforce’s ability to deliver actionable insights. The result? Missed opportunities, inefficiencies, and impersonal customer experiences. When organizations implement proper integrations and data management practices, predictive analytics can harness this data to uncover patterns and predict future events. Techniques such as logistic regression, linear regression, neural networks, and decision trees help businesses gain actionable insights that enhance planning and decision-making. Einstein Prediction Builder A key component of the Salesforce Einstein Suite, Einstein Prediction Builder enables users to create custom AI models with minimal coding or data science expertise. Using in-house data, businesses can anticipate trends, forecast customer behavior, and predict outcomes with tailored precision. Key Features of Einstein Prediction Builder Note: Einstein Prediction Builder requires an Enterprise or Unlimited Edition subscription to access. Predictive Model Types in Salesforce Salesforce employs various predictive models tailored to specific needs: Building Custom Predictions Salesforce supports custom predictions tailored to unique business needs, such as forecasting regional sales or calculating appointment attendance rates. Tips for Building Predictions Prescriptive Analytics: Turning Predictions into Actions Predictive insights are only as valuable as the actions they inspire. Einstein Next Best Action bridges this gap by providing context-specific recommendations based on predictions. How Einstein Next Best Action Works Data Quality: The Foundation of Accurate Predictions The effectiveness of predictive analytics depends on the quality of your data. Poor data—whether due to errors, duplicates, or inconsistencies—can skew results and undermine trust. Best Practices for Data Quality Modern tools like DataGroomr can automate data validation and cleaning, ensuring that predictions are based on trustworthy information. Empowering Smarter Decisions with Predictive Analytics Salesforce’s AI-driven predictive analytics transforms decision-making by providing actionable insights from historical data. Businesses can anticipate trends, improve operational efficiency, and deliver personalized customer experiences. As predictive analytics continues to evolve, companies leveraging these tools will gain a competitive edge in an increasingly dynamic marketplace. Embrace the power of predictive analytics in Salesforce to make faster, more strategic decisions and drive sustained success. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

September 30, 2024in Data, Enterprise, Salesforce, Salesforce Einstein

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