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My Service Journey is Here
17Feb

Salesforce Service Assistant Now Generally Available

Salesforce Service Assistant Now Generally Available in Service Cloud Salesforce has officially launched Service Assistant in Service Cloud, bringing AI-powered agent guidance to customer service teams. The assistant creates step-by-step action plans to help agents resolve queries efficiently by analyzing intent, case history, and customer context. Previously known as Salesforce Service Planner, the solution entered a pilot phase in October 2024 and is now live just four months later. Enhancing Accuracy with Data Cloud Integration To maximize accuracy, Salesforce recommends integrating Service Assistant with Data Cloud and the contact center knowledge base. This connection enables the assistant to access critical business processes and customer history across service, sales, marketing, and more. Key Features of Service Assistant Beyond real-time agent guidance, Service Assistant introduces two standout capabilities: This continuous learning cycle improves agent proficiency, enhances customer satisfaction, and reduces Average Handling Time (AHT). What’s Next for Service Assistant? Despite these capabilities, Salesforce plans to further enhance Service Assistant. In a recent webinar, Kevin Qi, Associate Product Manager at Salesforce, revealed upcoming enhancements in the Summer ’25 release (June 2025): “The next phase of Service Assistant involves actionable plans. It will not only guide service reps but also automate steps like looking up orders and checking eligibility to speed up case resolution.” Beyond summer, Salesforce aims to make Service Assistant more adaptive, supporting additional channels such as messaging and voice while dynamically adjusting to case context changes. Expanding AI & Agentforce Capabilities in Service Cloud Alongside Service Assistant, Salesforce has introduced several AI and Agentforce capabilities across Service Cloud. Highlighted features include: What’s Coming in the Summer ’25 Release? One of the most anticipated features in June 2025 is Agentforce: Service Actions in Slack. Salesforce already enables case swarming in Slack, allowing agents to collaborate with external teams. Now, this guidance will be automatically recorded in the case summary and converted into knowledge articles for future reference. Other upcoming knowledge management features include: Custom AI with Agentforce Beyond prebuilt AI solutions, Agentforce enables brands to create AI-powered workflows tailored to their needs. Service teams can: By integrating Agentforce with Data Cloud, businesses can connect cross-platform workflows and automate enterprise-wide operations. Content updated March 2025. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 17, 2025in Data, Enterprise, Salesforce, Salesforce Service Cloud
deepseek deep dive
15Feb

DeepSeek iOS App Poses Major Privacy Risks

Security Alert: DeepSeek iOS App Poses Major Privacy Risks Cybersecurity researchers at NowSecure have issued a stark warning about the iOS version of DeepSeek, currently the third most popular app on the App Store. Their analysis reveals serious security flaws, making the app a major privacy risk that users should delete immediately. According to NowSecure’s findings, DeepSeek: Additionally, DeepSeek relies on ByteDance’s Volcano Engine, tying it to TikTok’s parent company, further raising privacy and regulatory concerns. For personal devices, this poses a significant security risk. For company-owned iPhones, the risks are even greater, especially regarding data privacy and compliance. US Regulators Take Action DeepSeek’s security risks have drawn scrutiny from U.S. lawmakers concerned about national security and data privacy. Representatives Josh Gottheimer (D-NJ) and Darin LaHood (R-IL) have introduced the No DeepSeek on Government Devices Act, seeking to ban the app from government-issued phones. While the full text of the bill is not yet available, legislators cite research indicating that DeepSeek’s code is “directly linked to the Chinese Communist Party” and capable of transmitting user data to China Mobile, a Chinese state-owned telecom firm sanctioned by the U.S. For those concerned about data security, the safest approach is to remove DeepSeek from your device and, if necessary, switch to a locally-run model that does not transmit data externally. HPE Warns Employees of Data Breach Meanwhile, Hewlett Packard Enterprise (HPE) has notified employees of a nation-state attack that may have compromised personal data. In a letter sent to staff, HPE disclosed that an unauthorized party accessed its cloud email environment, potentially exposing employee information. While the impact appears limited—only ten employees were affected, according to Massachusetts’ data breach report—the breach raises concerns about targeted cyberattacks on enterprise tech firms. HPE had previously disclosed a similar attack in January 2024, attributing it to Russia’s Cozy Bear hacking group, which is known for infiltrating high-profile networks. Reports suggest this latest breach also targeted Microsoft Office 365 accounts, highlighting ongoing threats to corporate cloud environments. Takeaway From DeepSeek’s security risks to HPE’s cyberattack, these incidents underscore the importance of data privacy, secure app usage, and robust enterprise security measures. Whether for personal or corporate security, staying informed and taking proactive steps is critical in today’s evolving digital landscape. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 15, 2025in Data, Enterprise, Laws
The Hidden Risks of Over-Reliance on AI
14Feb

The Hidden Risks of Over-Reliance on AI

Are Marketers Trusting AI Too Much? How to Avoid Losing Your Strategic Edge AI tools have revolutionized how marketers approach research, content creation, and decision-making. However, an overreliance on these tools could undermine critical thinking and strategic planning, leaving marketers vulnerable in a fast-evolving landscape. Here’s how to balance the power of automation with human insight. The Rise of AI in Search and Marketing In late December, SEO consultancy Previsible shared a striking report: Google’s search dominance has plateaued and is now being challenged by AI-assisted search tools. These tools, such as ChatGPT, Claude, and Google’s own AI-enhanced search, are growing in popularity due to their ability to deliver contextually relevant and personalized results. Unlike traditional search, which relies on keyword matching, AI-driven search processes intent and context. This shift is reshaping how users find information and make decisions. How AI Is Changing User Behavior The increasing sophistication of AI tools brings both opportunities and risks. Users often trust AI-generated outputs without question, assuming they’re accurate and complete. Traditional search, by contrast, forces users to critically analyze and filter multiple sources. This blind trust in AI mirrors the concept of “System 1 thinking,” as described by Nobel Prize-winning psychologist Daniel Kahneman in Thinking, Fast and Slow. As AI models like ChatGPT operate primarily as “System 1 thinkers,” users risk adopting a similar approach, bypassing critical analysis in favor of convenience. The Hidden Risks of Over-Reliance on AI Younger marketers may be especially at risk of falling into this trap. Many are using AI tools like ChatGPT to summarize information or generate ideas, often without questioning the accuracy of the outputs. For B2B marketers, the allure of AI lies in its speed and perceived accuracy. However, this reliance on automation could lead to a generation of marketers who lack the ability—or inclination—to think strategically. The danger is clear: unchecked dependence on AI tools could foster a “groupthink” mentality, where creativity and critical thinking are sidelined. Without intervention, marketing departments risk becoming overly reliant on tools that were designed to enhance human efforts, not replace them. How Marketing Leaders Can Address This Threat To counter this trend, marketing leaders must actively promote the development of strategic skills. Here’s how: In a world increasingly driven by AI, marketers who can blend automation with strategic thinking will be best positioned for success. Using AI to Enhance, Not Replace, Strategic Thinking AI should empower marketers to make better decisions—not serve as the sole decision-maker. As one professor aptly put it, “Use AI to become a better student, not to be the student.” The key is balance. By combining the intuitive capabilities of AI with the deliberate, analytical approach of System 2 thinking, marketers can leverage technology without sacrificing creativity or strategy. In short, AI is a tool—not a replacement for human ingenuity. Those who recognize this distinction will thrive in an increasingly automated world. 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 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, 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

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February 14, 2025in AI Tools, Google, Technology
B2B Customer Service with Agentforce
12Feb

B2B Customer Service with Agentforce

Simplify and Transform B2B Customer Service with Agentforce B2B customer service is inherently complex. It involves managing layered relationships, high-value transactions, and specialized support needs—all of which require heightened attention to detail. With fewer but larger customers, the stakes are high. In fact, our research shows that 88% of customers are more likely to remain loyal with exceptional service, underscoring the importance of consistently delivering excellence. Enter Agentforce, an AI-powered solution designed to tackle these challenges. By complementing your service reps, Agentforce handles intricate B2B cases autonomously and within your predefined parameters. This ensures reliable 24/7 support for even the toughest queries, reducing rep burnout and enhancing customer satisfaction. Here’s how Agentforce can redefine B2B customer service and take it to the next level: What You’ll Learn What Is B2B Customer Service? B2B customer service focuses on providing personalized support and expertise to other businesses, addressing their unique needs and challenges. This service model aims to build lasting relationships by boosting loyalty, driving repeat business, and encouraging referrals. What Are AI Agents? AI agents like Agentforce are advanced systems capable of understanding and responding to customer inquiries without human involvement. Unlike basic chatbots, Agentforce uses natural language processing (NLP), machine learning, and contextual understanding to provide intelligent, conversational, and personalized support. At the heart of Agentforce is the Atlas Reasoning Engine, which simplifies complex queries, retrieves precise information from your Data Cloud, and creates accurate, reliable action plans—all within your company’s guardrails. Agentforce’s multi-modal understanding allows it to interpret inputs like text, images, and audio, making it a versatile tool for engaging customers. Crucially, Agentforce continuously learns and adapts, ensuring it evolves with your customers’ needs for more accurate, efficient support. Why AI Agents Are Ideal for B2B Customer Service B2B support often involves managing: Agentforce rises to these challenges by providing scalable, round-the-clock support that accommodates time zone differences, personalizes interactions, and resolves intricate inquiries with ease. Top Benefits of AI Agents in B2B Customer Service Use Cases for Agentforce in B2B Customer Service Challenges of Implementing AI Agents—and How to Solve Them 5 Best Practices for Success Ready to Elevate Your B2B Customer Service? Agentforce empowers your business to deliver consistent, reliable, and scalable support—around the clock. By handling complex interactions and reducing workload on service reps, it builds stronger customer relationships and positions your company for long-term 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 12, 2025in Data, Salesforce
Prompt Decorators
12Feb

Prompt Decorators

Prompt Decorators: A Structured Approach to Enhancing AI Responses Artificial intelligence has transformed how we interact with technology, offering powerful capabilities in content generation, research, and problem-solving. However, the quality of AI responses often hinges on how effectively users craft their prompts. Many encounter challenges such as vague answers, inconsistent outputs, and the need for repetitive refinement. Prompt Decorators provide a solution—structured prefixes that guide AI models to generate clearer, more logical, and better-organized responses. Inspired by Python decorators, this method standardizes prompt engineering, making AI interactions more efficient and reliable. The Challenge of AI Prompting While AI models like ChatGPT excel at generating human-like text, their outputs can vary widely based on prompt phrasing. Common issues include: Without a systematic approach, users waste time fine-tuning prompts instead of getting useful answers. What Are Prompt Decorators? Prompt Decorators are simple prefixes added to prompts to modify AI behavior. They enforce structured reasoning, improve accuracy, and customize responses. Example Without a Decorator: “Suggest a name for an AI YouTube channel.”→ The AI may return a basic list of names without justification. Example With +++Reasoning Decorator: “+++Reasoning Suggest a name for an AI YouTube channel.”→ The AI first explains its naming criteria (e.g., clarity, memorability, relevance) before generating suggestions. Key Prompt Decorators & Their Uses Decorator Function Example Use Case +++Reasoning Forces AI to explain logic before answering “+++Reasoning What’s the best AI model for text generation?” +++StepByStep Breaks complex tasks into clear steps “+++StepByStep How do I fine-tune an LLM?” +++Debate Presents pros and cons for balanced discussion “+++Debate Is cryptocurrency a good investment?” +++Critique Evaluates strengths/weaknesses before suggesting improvements “+++Critique Analyze the pros and cons of online education.” +++Refine(N) Iteratively improves responses (N = refinement rounds) “+++Refine(3) Write a tagline for an AI startup.” +++CiteSources Includes references for claims “+++CiteSources Who invented the printing press?” +++FactCheck Prioritizes verified information “+++FactCheck What are the health benefits of coffee?” +++OutputFormat(FMT) Structures responses (JSON, Markdown, etc.) “+++OutputFormat(JSON) List top AI trends in 2024.” +++Tone(STYLE) Adjusts response tone (formal, casual, etc.) “+++Tone(Formal) Write an email requesting a deadline extension.” Why Use Prompt Decorators? Real-World Applications The Future of Prompt Decorators As AI evolves, Prompt Decorators could: Conclusion Prompt Decorators offer a simple yet powerful way to enhance AI interactions. By integrating structured directives, users can achieve more reliable, insightful, and actionable outputs—reducing frustration and unlocking AI’s full potential. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 12, 2025in Artificial Intelligence, Technology
Rethinking Technology in Local Government
10Feb

Rethinking Technology in Local Government

Rethinking Technology in Local Government: A Call to Action By Richard Young, Head of Local Government, Salesforce The latest survey from Salesforce and LGC underscores an urgent need for a technology transformation in local government. Legacy systems and fragmented infrastructure remain significant roadblocks to digital progress, with nearly half of respondents identifying them as barriers to adoption. Outdated, disconnected systems limit efficiency, frustrate staff and residents, and prevent seamless data sharing—ultimately hindering councils from delivering modern, responsive services. Breaking Down Silos: A Unified Approach To move beyond fragmented solutions, councils must embrace a connected digital ecosystem that integrates systems, data, and stakeholders. Salesforce enables this shift through: ✅ MuleSoft – Seamlessly integrates legacy and modern systems, allowing for real-time data sharing and eliminating silos.✅ Salesforce Customer 360 – Provides a single, unified view of residents, enabling personalized, consistent service delivery across all touchpoints. By adopting a resident-first approach, councils can streamline operations, enhance engagement, and deliver services more effectively. Overcoming Barriers to Digital Transformation While the benefits of modern technology are clear, our survey reveals significant challenges to implementation, including: Salesforce supports councils through these challenges by providing: 🎓 Comprehensive training programs – Equipping staff with the skills to confidently adopt new technology.🤝 Shared service models – Encouraging collaboration across councils to pool resources and scale best practices.🚀 The Government Innovators Network – A knowledge-sharing platform connecting public sector leaders and private technology partners to drive innovation. By focusing on incremental modernization and ROI-driven deployments, councils can maximize value while staying within budget constraints. Empowering Councils for the Future To truly future-proof local government, technology must be: ✔ User-friendly – Intuitive systems reduce friction, enabling both staff and residents to self-service with ease.✔ Scalable and secure – Protecting against cyber threats and evolving challenges.✔ Designed for impact – Fostering collaboration between public and private sectors to drive long-term innovation. Salesforce has already made a measurable impact: 🏛 A UK council integrated over 30 legacy systems, reducing administrative overhead by 40% and increasing resident satisfaction by 25%.🇦🇺 An Australian local authority centralized resident engagement, cutting service request response times by 50%. Across the globe, we are transforming council operations, governance, and resident experiences. A Connected Future Starts Now Now is the time for councils to rethink their approach to technology. By embracing scalable, integrated solutions, they can deliver better services, empower staff, and put residents at the heart of every decision. Together, we can reimagine local government—creating a more connected, efficient, and empowered future. Richard Young, Head of Local Government, Salesforce 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 10, 2025in Data, Mulesoft, Salesforce, Technology
Salesforce’s AI Energy Score
08Feb

Salesforce’s AI Energy Score

Salesforce’s AI Energy Score: Setting a New Standard for AI Sustainability Understanding AI’s Environmental Impact As AI adoption accelerates globally, concerns about its environmental footprint have grown. Due to AI’s reliance on power-intensive data centers, the technology consumes vast amounts of energy and water, raising sustainability challenges. To address this, Salesforce, in collaboration with Hugging Face, Cohere, and Carnegie Mellon University, has introduced the AI Energy Score—a pioneering tool designed to measure and compare AI models’ energy efficiency. The AI Energy Score Launch The AI Energy Score will debut at the AI Action Summit on February 10, 2025, where leaders from over 100 countries, along with private sector and civil society representatives, will convene to discuss AI’s role in sustainability. Recognized by the French Government and the Paris Peace Forum, this initiative marks a significant step toward transparent and accountable AI development. “We are at a critical moment where the rapid acceleration of both the climate crisis and AI innovation intersect,” says Boris Gamazaychikov, Head of AI Sustainability at Salesforce.“AI’s environmental impact has remained largely opaque, with little transparency around its energy consumption. The AI Energy Score provides a standardized framework to disclose and compare these impacts, removing a key blocker to making sustainable AI the norm.” What Is the AI Energy Score? Developed in partnership with Hugging Face, Cohere, and Carnegie Mellon University, the AI Energy Score aims to establish clear and standardized energy consumption metrics for AI models. “The AI Energy Score is a major milestone for sustainable AI,” says Dr. Sasha Luccioni, AI & Climate Lead at Hugging Face. “By creating a transparent rating system, we address a key blocker for reducing AI’s environmental impact. We’re excited to launch this initiative and drive industry-wide adoption.” Key features of the AI Energy Score include: ✅ Standardized energy ratings – A framework for evaluating AI models’ energy efficiency✅ Public leaderboard – A ranking of 200+ AI models across 10 common tasks (e.g., text and image generation)✅ Benchmarking portal – A platform for submitting and assessing AI models, both open and proprietary✅ Recognizable energy use label – A 1–5 star system for easy identification of energy-efficient models✅ Label generator – A tool for AI developers to create and share standardized energy labels The Impact of the AI Energy Score The introduction of this score is expected to have far-reaching implications for the AI industry: 🔹 Driving market preference – Transparency will push demand for more energy-efficient AI models🔹 Incentivizing sustainable development – Public disclosure will encourage AI developers to prioritize efficiency🔹 Empowering informed decisions – AI users and businesses can make better choices based on energy efficiency data Salesforce’s Commitment to Sustainable AI Salesforce is leading by example, becoming the first AI model developer to disclose energy efficiency data for its proprietary models under this framework. This aligns with the company’s broader sustainability goals and ethical AI approach. Agentforce: AI Efficiency at Scale Salesforce’s Agentforce platform, introduced in 2024, is designed to deploy autonomous AI agents across business functions while maintaining energy efficiency. “Agentforce is built with sustainability at its core, delivering high performance while minimizing environmental impact,” explains Boris Gamazaychikov.“Unlike DIY AI approaches that require energy-intensive model training for each customer, Agentforce is optimized out of the box, reducing costly and carbon-heavy training.” Organizations are already leveraging Agentforce for impact-driven efficiencies: ✅ Good360 uses Agentforce to allocate donated goods more efficiently, cutting waste and emissions while saving 1,000+ employee hours annually✅ Businesses can reduce operational costs by optimizing AI model energy consumption “Reducing AI energy use isn’t just good for the environment—it lowers costs, optimizes infrastructure, and improves long-term profitability,” says Suzanne DiBianca, EVP & Chief Impact Officer at Salesforce.“We’re proud to work with industry leaders to build a more transparent AI ecosystem.” Addressing the AI Energy Challenge With AI-driven data center power usage projected to double by 2026, the AI Energy Score is a timely solution to help organizations manage and reduce their AI-related environmental impact. “The AI Energy Score isn’t just an energy-use metric—it’s a strategic business advantage,” adds Boris Gamazaychikov. “By helping organizations assess and optimize AI model energy consumption, it supports lower costs, better infrastructure efficiency, and long-term profitability.” As AI continues to evolve, sustainability must be part of the equation. The AI Energy Score is a major step in ensuring that the AI industry moves toward a more responsible, energy-efficient future.: Setting a New Standard for AI Sustainability Understanding AI’s Environmental Impact As AI adoption accelerates globally, concerns about its environmental footprint have grown. Due to AI’s reliance on power-intensive data centers, the technology consumes vast amounts of energy and water, raising sustainability challenges. To address this, Salesforce, in collaboration with Hugging Face, Cohere, and Carnegie Mellon University, has introduced the AI Energy Score—a pioneering tool designed to measure and compare AI models’ energy efficiency. The AI Energy Score Launch The AI Energy Score will debut at the AI Action Summit on February 10, 2025, where leaders from over 100 countries, along with private sector and civil society representatives, will convene to discuss AI’s role in sustainability. Recognized by the French Government and the Paris Peace Forum, this initiative marks a significant step toward transparent and accountable AI development. “We are at a critical moment where the rapid acceleration of both the climate crisis and AI innovation intersect,” says Boris Gamazaychikov, Head of AI Sustainability at Salesforce.“AI’s environmental impact has remained largely opaque, with little transparency around its energy consumption. The AI Energy Score provides a standardized framework to disclose and compare these impacts, removing a key blocker to making sustainable AI the norm.” What Is the AI Energy Score? Developed in partnership with Hugging Face, Cohere, and Carnegie Mellon University, the AI Energy Score aims to establish clear and standardized energy consumption metrics for AI models. “The AI Energy Score is a major milestone for sustainable AI,” says Dr. Sasha Luccioni, AI & Climate Lead at Hugging Face. “By creating a transparent rating system, we address a key blocker for reducing AI’s

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February 8, 2025in Agentforce Platform, Data, Salesforce, Technology
06Feb

Decision Domain Management

Roger’s first week in the office felt like a wilder than 8 second ride on a raging rodeo bull. Armed with top-notch academic achievements, he hoped to breeze through operational routines and impress his new managers. What he didn’t expect was to land in a whirlwind of half-documented processes, half-baked ideas, and near-constant firefighting. While the organization had detailed SOPs for simple, routine tasks—approving invoices, updating customer records, and shipping standard orders—Roger quickly realized that behind the structured facade, there was a deeper level of uncertainty. Every day, he heard colleagues discuss “strategic pivots” or “risky product bets.” There were whispers about AI-based initiatives that promised to automate entire workflows. Yet, when the conversation shifted to major decisions—like selecting the right AI use cases—leaders often seemed to rely more on intuition than any structured methodology. One afternoon, Roger was invited to a cross-functional meeting about the company’s AI roadmap. Expecting an opportunity to showcase his knowledge, he instead found himself in a room filled with brilliant minds pulling in different directions. Some argued that AI should focus on automating repetitive tasks aligned with existing SOPs. Others insisted that AI’s real value lay in predictive modeling—helping forecast new market opportunities. The debate went in circles, with no consensus on where or how to allocate AI resources. After an hour of heated discussion, the group dispersed, each manager still convinced of the merit of their own perspective but no closer to a resolution. That evening, as Roger stood near the coffee machine, he muttered to himself, “We have SOPs for simple tasks, but nothing for big decisions. How do we even begin selecting which AI models or agents to develop first?” His frustration led him to a conversation with a coworker who had been with the company for years. “We’re missing something fundamental here,” Roger said. “We’re rushing to onboard AI agents that can mimic our SOPs—like some large language model trained to follow rote instructions—but that’s not where the real value lies. We don’t even have a framework for weighing one AI initiative against another. Everything feels like guesswork.” His coworker shrugged. “That’s just how it’s always been. The big decisions happen behind closed doors, mostly based on experience and intuition. If you’re waiting for a blueprint, you might be waiting a long time.” That was Roger’s ;ight bulb moment. Despite all his academic training, he realized the organization lacked a structured approach to high-level decision-making. Sure, they had polished SOPs for operational tasks, but when it came to determining which AI initiatives to prioritize, there were no formal criteria, classifications, or scoring mechanisms in place. Frustrated but determined, Roger decided he needed answers. Two days later, he approached a coworker known for their deep understanding of business strategy and technology. After a quick greeting, he outlined his concerns—the disorganized AI roadmap meeting, the disconnect between SOP-driven automation and strategic AI modeling, and his growing suspicion that even senior leaders were making decisions without a clear framework. His coworker listened, then gestured for him to take a seat. “Take a breath,” they said. “You’re not the first to notice this gap. Let me explain what’s really missing.” Why SOPs Aren’t Enough The coworker acknowledged that the organization was strong in SOPs. “We’re great at detailing exactly how to handle repetitive, rules-based tasks—like verifying invoices or updating inventory. In those areas, we can plug in AI agents pretty easily. They follow a well-defined script and execute tasks efficiently. But that’s just the tip of the iceberg.” They leaned forward and continued, “Where we struggle, as you’ve discovered, is in decision-making at deeper levels—strategic decisions like which new product lines to pursue, or tactical decisions like selecting the right vendor partnerships. There’s no documented methodology for these. It’s all in people’s heads.” Roger tilted his head, intrigued. “So how do we fix something as basic but great impact as that?” “That’s where Decision Domain Management comes in,” he explained. In the context of data governance and management, data domains are the high-level blocks that data professionals use to define master data. Simply put, data domains help data teams logically group data that is of interest to their business or stakeholders. “Think of it as the equivalent of SOPs—but for decision-making. Instead of prescribing exact steps for routine tasks, it helps classify decisions, assess their importance, and determine whether AI can support them—and if so, in what capacity.” They broke it down further. The Decision Types “First, we categorize decisions into three broad types: Once we correctly classify a decision, we get a clearer picture of how critical it is and whether it requires an AI agent (good at routine tasks) or an AI model (good at predictive and analytical tasks).” The Cynefin Framework The coworker then introduced the Cynefin Framework, explaining how it helps categorize decision contexts: By combining Decision Types with the Cynefin Framework, organizations can determine exactly where AI projects will be most beneficial. Putting It into Practice Seeing the spark of understanding in Roger’s eyes, the coworker provided some real-world examples: ✅ AI agents are ideal for simple SOP-based tasks like invoice validation or shipping notifications. ✅ AI models can support complicated decisions, like vendor negotiations, by analyzing performance metrics. ✅ Strategic AI modeling can help navigate complex decisions, such as predicting new market trends, but human judgment is still required. “Once we classify decisions,” the coworker continued, “we can score and prioritize AI investments based on impact and feasibility. Instead of throwing AI at random problems, we make informed choices.” The Lightbulb Moment Roger exhaled, visibly relieved. “So the problem isn’t just that we lack a single best AI approach—it’s that we don’t have a shared structure for decision-making in the first place,” he said. “If we build that structure, we’ll know which AI investments matter most, and we won’t keep debating in circles.” The coworker nodded. “Exactly. Decision Domain Management is the missing blueprint. We can’t expect AI to handle what even humans haven’t clearly defined. By categorizing

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February 6, 2025in Data, Enterprise, Technology
unpatched ai
05Feb

Unpatched.ai

The Mystery of Unpatched.ai: AI-Powered Vulnerability Discovery Raises Questions During January’s Patch Tuesday, Microsoft credited Unpatched.ai for reporting multiple high-severity vulnerabilities. Yet, despite its contributions, the AI-driven bug-finding tool remains an enigma to the cybersecurity community. Last month, Microsoft addressed 159 new vulnerabilities across its widely used products. Among them, Unpatched.ai was acknowledged for identifying three remote code execution flaws—CVE-2025-21186, CVE-2025-21366, and CVE-2025-21395—all of which affect Microsoft Access and received a CVSS score of 7.8. While Microsoft’s recognition highlights Unpatched.ai’s role in vulnerability discovery, little is known about the tool itself. Informa TechTarget reached out to multiple security vendors and experts for insights, but responses only deepened the mystery. A Cryptic Online Presence Unpatched.ai describes itself as “vulnerability discovery by an AI-guided cybersecurity platform” on its website. It provides a list of reported vulnerabilities, which consists solely of Microsoft-related flaws—primarily within Microsoft Access. The platform states that it collaborates with “select enterprise, government, and security vendors based in the U.S. and ally countries.” The company’s “About” page sheds some light on its mission, attributing its research to the need for greater transparency around unpatched software flaws: “We find unpatched issues in software to help customers better identify and manage cyber risk. Many issues are unknown or silently fixed by software vendors, hiding the true risk profile of their products. With the help of AI, we are developing an automated platform to help find and analyze these issues for our customers.” Beyond the website, Unpatched.ai maintains an X account, though much of its activity has been erased. A now-deleted post from January 29 warned that Microsoft’s patch for CVE-2025-21396 was insufficient. When contacted about the post, a Microsoft spokesperson responded, “We are aware of these reports and will take action as needed to help protect customers.” However, Microsoft did not provide additional background on Unpatched.ai. Attempts to reach Unpatched.ai directly have gone unanswered. Piecing Together the Puzzle Efforts to uncover more about Unpatched.ai yielded few concrete details. The domain was registered through Namecheap in September, with ownership masked by a privacy service based in Reykjavik, Iceland. Adam Barnett, lead software engineer at Rapid7, noted that beyond Unpatched.ai’s website, information is scarce. However, he identified a Reddit user, “Fit_Tie_9430,” who has claimed affiliation with the platform. This user shared details about Unpatched.ai’s vulnerability discoveries and linked to now-private YouTube videos demonstrating exploits against Microsoft Access vulnerabilities. Barnett pointed out that Unpatched.ai was also credited for a December Patch Tuesday flaw, CVE-2024-49142. Initially published without attribution, Microsoft later updated the advisory to acknowledge Unpatched.ai’s discovery. Interestingly, the Unpatched.ai website’s favicon—a simple “:)” emoticon—appears to reference the Windows Blue Screen of Death’s “:(” symbol. “It’s a nice touch,” Barnett said, “but I still don’t know who’s behind it. It could be just about anyone with the time, resources, and skills.” Other industry experts share the same uncertainty. Satnam Narang, senior staff research engineer at Tenable, observed that Unpatched.ai’s X account follows only a handful of infosec professionals. “It’s unclear if the service is still in a closed-door phase and will eventually provide more insights about its leadership and team, or who may be backing it,” he said. Alon Yamin, co-founder and CEO of Copyleaks, noted that an AI-driven vulnerability discovery platform was inevitable given the surge in software flaws. While AI can be a game-changer for proactive threat detection, he cautioned against potential misuse. “It’s crucial that Unpatched.ai is deployed carefully, responsibly, and ethically, with safeguards to prevent attackers from exploiting the vulnerabilities it identifies,” Yamin said. The Future of AI-Powered Bug Hunting AI-driven vulnerability discovery is an emerging focus in cybersecurity, though few major breakthroughs have been publicly confirmed. In November, Google announced it had discovered a zero-day vulnerability using AI. Google Project Zero and DeepMind’s AI-powered agent, Big Sleep, identified a buffer stack underflow flaw in the SQLite open-source database engine. With Unpatched.ai making waves yet remaining elusive, the cybersecurity community is left with more questions than answers. Is this the beginning of a new era in AI-powered vulnerability research, or is Unpatched.ai an outlier? Until more information surfaces, the mystery remains. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 5, 2025in Data, Enterprise, Google, Laws
deepseek deep dive
05Feb

Deep Dive into DeepSeek

DeepSeek: The AI Lab Turned Controversial Global Player You know we have to write about anything AI related that is making waves. And DeepSeek is definitely doing that. On April 14, 2023, High-Flyer announced the launch of a dedicated artificial general intelligence (AGI) lab, focused on AI research independent of its financial business. This initiative led to the incorporation of DeepSeek on July 17, 2023, with High-Flyer as its primary investor and backer. DeepSeek’s Breakthrough and the Debate on AI Development DeepSeek quickly gained attention in the AI world, with former India IT Minister Rajeev Chandrasekhar highlighting its impact. He stated that DeepSeek’s success reinforced the idea that better datasets and algorithms—rather than increased compute capacity—are the key to advancing AI capabilities. National Security Concerns: Hidden Risks in DeepSeek’s Code Despite its technological achievements, DeepSeek is now at the center of global controversy. Cybersecurity experts have raised serious concerns about the tool’s potential data-sharing links to the Chinese government. According to a report by ABC News, DeepSeek contains hidden code capable of transmitting user data directly to China. Ivan Tsarynny, CEO of the Ontario-based cybersecurity firm Feroot Security, conducted an analysis of DeepSeek’s code and discovered an embedded function that connects user data to CMPassport.com—the online registry for China Mobile, a state-owned telecommunications company. Key Concerns Raised by Cybersecurity Experts: Global Backlash and Regulatory Actions DeepSeek’s security concerns have sparked international scrutiny. Several governments and organizations have moved swiftly to restrict or ban its use: John Cohen, a former acting Undersecretary for Intelligence and Analysis at the U.S. Department of Homeland Security, described DeepSeek as one of the most blatant cases of suspected Chinese surveillance. He emphasized that it joins a growing list of Chinese tech firms identified as potential national security threats. The Future of DeepSeek DeepSeek’s rapid rise and subsequent scrutiny reflect the broader tensions between AI innovation and national security. As regulators worldwide assess its risks, the company’s future remains uncertain—caught between technological breakthroughs and growing geopolitical concerns. 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 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, 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

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February 5, 2025in AI Tools, Data
Financial Services Sector
04Feb

Fundingo Outshines Mortgage Automator

Why Fundingo Outshines Mortgage Automator: A Salesforce-Based Perspective Introduction In the dynamic world of loan servicing and mortgage management, businesses face increasing demands for flexibility, efficiency, and scalability. While Mortgage Automator is a well-known provider, many users encounter significant challenges, including inflexible loan structures and cumbersome reporting processes. Fundingo, a Salesforce-native solution, addresses these issues head-on with a modern, adaptable, and user-friendly approach to loan management. Pain Points of Mortgage Automator Despite its established presence, Mortgage Automator comes with notable limitations: Fundingo’s Competitive Edge Fundingo offers a suite of advantages designed for modern lending institutions, making it the superior choice: Head-to-Head Comparison Feature Fundingo Mortgage Automator Flexibility High – Supports diverse loan products Limited – Rigid loan structures Reporting Automated and user-friendly Complex and manual processes Integrations Seamless with Salesforce ecosystem Poor integration capabilities Scalability Cost-effective, built-in scalability Expensive add-ons hinder growth Security & Compliance SOC 1 certified Basic security measures Summary Fundingo emerges as the ideal solution for modern loan servicing and mortgage management. By addressing the common challenges associated with Mortgage Automator—rigid loan structures, manual processes, and costly add-ons—Fundingo provides a flexible, scalable, and secure alternative. Its Salesforce-native design, built-in CRM, mobile accessibility, exceptional uptime, and robust security measures make it the best competitor in the market, empowering financial institutions to deliver exceptional service while optimizing operational efficiency. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 4, 2025in Data
copilots and agentic ai
03Feb

Transforming Industries and Redefining Workflows

The Rise of Agentic AI: Transforming Industries and Redefining Workflows Artificial Intelligence (AI) is evolving faster than we anticipated. No longer limited to predicting outcomes or generating content, AI systems are now capable of handling complex tasks and making autonomous decisions. This new era—driven by Agentic AI—is set to redefine the workplace and transform industries. From Prediction to Autonomy: The Three Waves of AI To understand where we’re headed, it’s important to see how far AI has come. Arun Parameswaran, SVP & MD of Salesforce India, describes it as a fundamental shift: “What has changed with agents is their ability to handle complex reasoning… and, most importantly, to take action.” Unlike previous AI models that recommend or predict, Agentic AI executes tasks, reshaping customer experiences and operational workflows. Agentic AI in Action: Industry Applications At a recent Mint x Salesforce India deep-dive event on AI, industry leaders explored how Agentic AI is driving transformation across sectors. The panel featured: Here’s how Agentic AI is already making an impact: 1. Revolutionizing Customer Support Traditional chatbots have limited capabilities. Agentic AI, however, understands urgency and context. 2. Accelerating Business Decisions In finance and supply chain management, AI agents analyze vast amounts of data and execute decisions autonomously. 3. Transforming Travel & Aviation Airlines are leveraging AI to optimize booking systems, reduce costs, and enhance efficiency. 4. Automating Wealth Management AI agents in financial services monitor markets, adjust strategies, and offer personalized investment recommendations in real time. The Risks & Responsibilities of Agentic AI With great autonomy comes great responsibility. The potential of Agentic AI is vast—but so are the challenges: The Future of Work: AI as a Partner, Not a Replacement Despite concerns about job displacement, AI is more likely to reshape rather than replace roles. What Are AI Agents? AI agents go beyond traditional models like ChatGPT or Gemini. They are proactive, self-learning systems that: They fall into two categories: “AI agents don’t just wait for commands; they anticipate needs and act,” says Dr. Tomer Simon, Chief Scientist at Microsoft Research Israel. AI Agents in the Workplace: A Shift in Roles AI agents streamline processes, but they don’t eliminate the need for human oversight. Salesforce’s Agentforce is a prime example: “Companies need to integrate AI, not fear it. Those who fail to adopt AI tools risk drowning in tasks AI can handle,” warns Dr. Omri Allouche, Chief Scientist at Gong. The Road Ahead: AI-Driven Business Growth Agentic AI is not about replacing people—it’s about empowering them. As organizations re-evaluate workflows and embrace AI collaboration, the companies that act early will gain a competitive edge in efficiency and innovation. Final Thought The AI revolution is here, and Agentic AI is at its forefront. The key question isn’t whether AI will transform industries—it’s how organizations will adapt and thrive in this new era. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 3, 2025in Agentic AI, AI Tools, Artificial Intelligence, Data, Generative AI, Google, Laws, Salesforce, Technology
Basejump on AI Analytics
01Feb

Basejump on AI Analytics

The Evolution of Data and AI: A New Frontier Once considered the new oil, data is no longer the sole focus of business transformation. The emergence of artificial intelligence (AI) has shifted the conversation toward compute power as the fundamental resource driving innovation. Sequoia Capital emphasizes AI’s transformative impact, stating: “The fields that generative AI addresses — knowledge work and creative work — comprise billions of workers. [If] Generative AI can make these workers at least 10% more efficient and/or creative: they become not only faster and more efficient, but more capable than before. Therefore, Generative AI has the potential to generate trillions of dollars of economic value.”— Sonya Huang, Pat Grady, Generative AI: A Creative New World Whether this vision materializes remains to be seen, but the comparisons to past technological revolutions—such as the internet and mobile computing—are hard to ignore. The Role of AI in Knowledge Work and Data Analytics Data analytics has seen unprecedented growth, prompting businesses to reassess its value. With a projected compound annual growth rate (CAGR) of 27.3% through 2030, the market’s rapid expansion has led to a push for better tools and standards. Data analytics has evolved from a discipline primarily rooted in physics, mathematics, accounting, and economics to a more structured academic field. This shift is evident in the surge of data science degrees. The National Center for Education Statistics reported a 968% increase in data science bachelor’s degrees awarded from 2020 to 2022, highlighting growing demand. Modern Data Analytics: From ETL to ELTL Traditional extract-transform-load (ETL) processes have struggled to keep up with modern analytical demands. The introduction of extract-load-transform (ELT) architectures, championed by tools like dbt, empowered data teams by shifting transformation ownership from data architects to analysts. However, this speed came at a cost: fragmented data governance and inconsistencies in reporting. A more refined approach—ELTL (extract-load-transform-load)—adds a critical governance step, ensuring structured data models before visualization and reporting. Data Governance, the Semantic Layer, and AI Unstructured data delivery has led to discrepancies across dashboards and reports. To address this, solutions such as dbt’s semantic layer and SQLMesh provide standardized testing, metadata management, and auditing mechanisms. AI plays a crucial role here, offering: AI-Driven Precision Analytics AI is set to revolutionize data querying by replacing cumbersome dashboards with precise, real-time insights. Borrowing from the concept of precision medicine, “precision analytics” ensures that businesses receive tailored data transformations instantly. This shift reduces reliance on static filters and rigid dashboards, allowing AI to dynamically generate and refine queries. The Rise of Data Objects AI-generated SQL queries—what we term “data objects”—are distinct from traditional dashboards in that they are: AI Solutions: Retrieving and Querying Data AI-powered data analytics falls into two broad categories: Building Trust in AI-Driven Analytics AI-generated analytics must be trustworthy, requiring: The Future of AI in Data Analytics AI will not replace data teams but will enhance their efficiency by reducing bottlenecks and accelerating insights. Organizations that integrate AI with strong data governance will achieve a competitive edge, enabling faster, more accurate, and more relevant analytics. The shift toward AI-driven data analytics is inevitable. The question is: will organizations embrace the change and refine their strategies, or will they be left behind in the wake of innovation? 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 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, 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

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February 1, 2025in Artificial Intelligence, Data, Enterprise, Generative AI, Technology

Einstein Service Agent

It’s been a little over a year since the global surge in GenAI chatbots, sparked by the excitement around ChatGPT. Since then, numerous vendors, both large and mid-sized, have invested heavily in the technology, and many users have already adopted AI-powered chatbots. The competition is intensifying, with CRM giant Salesforce releasing its own GenAI chatbot software, Einstein Service Agent. Einstein Service Agent, built on the Einstein 1 Platform, is Salesforce’s first fully autonomous AI agent. It interacts with large language models (LLMs) by analyzing the context of customer messages to determine the next actions. Utilizing GenAI, the agent generates conversational responses grounded in a company’s trusted business data, including Salesforce CRM data. Salesforce claims that service organizations can now significantly reduce the number of tedious inquiries that hinder productivity, allowing human agents to focus on more complex tasks. For customers, this means getting answers faster without waiting for human agents. Additionally, the service promises 24/7 availability for customer communication in natural language, with an easy handoff to human agents for more complicated issues. Businesses are increasingly turning to AI-based chatbots because, unlike traditional chatbots, they don’t rely on specific programmed queries and can understand context and nuance. Alongside Salesforce, other tech leaders like AWS and Google Cloud have released their own chatbots, such as Amazon Lex and Vertex AI, continuously enhancing their software. Recently, AWS updated its chatbot with the QnAIntent capability in Amazon Lex, allowing integration with a knowledge base in Amazon Bedrock. Similarly, Google released Vertex AI Agent Builder earlier this year, enabling organizations to build AI agents with no code, which can function together with one main agent and subagents. The AI arms race is just beginning, with more vendors developing software to meet market demands. For users, this means that while AI takes over many manual and tedious tasks, the primary challenge will be choosing the right vendor that best suits the needs and resources of their business. 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 Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 31, 2025in Data, Einstein 1 Platform, Google, Salesforce, Technology

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