Gemini Archives - gettectonic.com

Grok 3 Model Explained

Grok 3 Model Explained: Everything You Need to Know xAI has introduced its latest large language model (LLM), Grok 3, expanding its capabilities with advanced reasoning, knowledge retrieval, and text summarization. In the competitive landscape of generative AI (GenAI), LLMs and their chatbot services have become essential tools for users and organizations. While OpenAI’s ChatGPT (powered by the GPT series) pioneered the modern GenAI era, alternatives like Anthropic’s Claude, Google Gemini, and now Grok (developed by Elon Musk’s xAI) offer diverse choices. The term grok originates from Robert Heinlein’s 1961 sci-fi novel Stranger in a Strange Land, meaning to deeply understand something. Grok is closely tied to X (formerly Twitter), where it serves as an integrated AI chatbot, though it’s also available on other platforms. What Is Grok 3? Grok 3 is xAI’s latest LLM, announced on February 17, 2025, in a live stream featuring CEO Elon Musk and the engineering team. Musk, known for founding Tesla, SpaceX, and acquiring Twitter (now X), launched xAI on March 9, 2023, with the mission to “understand the universe.” Grok 3 is the third iteration of the model, built using Rust and Python. Unlike Grok 1 (partially open-sourced under Apache 2.0), Grok 3 is proprietary. Key Innovations in Grok 3 Grok 3 excels in advanced reasoning, positioning it as a strong competitor against models like OpenAI’s o3 and DeepSeek-R1. What Can Grok 3 Do? Grok 3 operates in two core modes: 1. Think Mode 2. DeepSearch Mode Core Capabilities ✔ Advanced Reasoning – Multi-step problem-solving with self-correction.✔ Content Summarization – Text, images, and video summaries.✔ Text Generation – Human-like writing for various use cases.✔ Knowledge Retrieval – Accesses real-time web data (especially in DeepSearch mode).✔ Mathematics – Strong performance on benchmarks like AIME 2024.✔ Coding – Writes, debugs, and optimizes code.✔ Voice Mode – Supports spoken responses. Previous Grok Versions Model Release Date Key Features Grok 1 Nov. 3, 2023 Humorous, personality-driven responses. Grok 1.5 Mar. 28, 2024 Expanded context (128K tokens), better problem-solving. Grok 1.5V Apr. 12, 2024 First multimodal version (image understanding). Grok 2 Aug. 14, 2024 Full multimodal support, image generation via Black Forest Labs’ FLUX. Grok 3 vs. GPT-4o vs. DeepSeek-R1 Feature Grok 3 GPT-4o DeepSeek-R1 Release Date Feb. 17, 2025 May 24, 2024 Jan. 20, 2025 Developer xAI (USA) OpenAI (USA) DeepSeek (China) Reasoning Advanced (Think mode) Limited Strong Real-Time Data DeepSearch (web access) Training data cutoff Training data cutoff License Proprietary Proprietary Open-source Coding (LiveCodeBench) 79.4 72.9 64.3 Math (AIME 2024) 99.3 87.3 79.8 How to Use Grok 3 1. On X (Twitter) 2. Grok.com 3. Mobile App (iOS/Android) Same subscription options as Grok.com. 4. API (Coming Soon) No confirmed release date yet. Final Thoughts Grok 3 is a powerful reasoning-focused LLM with real-time search capabilities, making it a strong alternative to GPT-4o and DeepSeek-R1. With its DeepSearch and Think modes, it offers advanced problem-solving beyond traditional chatbots. Will it surpass OpenAI and DeepSeek? Only time—and benchmarks—will tell. 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

May 21, 2025in AI Knowledge Base, AI Tools, AI-Powered Writing, Artificial Intelligence, Artificial Intelligence, Creative AI Tools, Data, Generative AI, Generative AI Tools, Google0 Comments

05May

Is Using DeepSeek a Security Risk?

Despite its efficiency and customizability, DeepSeek—a Chinese AI chatbot—raises serious concerns about data privacy, censorship, and security vulnerabilities for business users. DeepSeek’s Rapid Rise and Security Concerns Two years after ChatGPT’s launch, China introduced a major rival: DeepSeek. Within days of its release in January 2025, DeepSeek became the most downloaded freeware app on Apple’s iOS App Store and Google Play in the U.S. However, its fast adoption has sparked significant privacy and security concerns, especially for businesses that may input sensitive data. What Is DeepSeek? Developed by a Chinese AI startup of the same name, DeepSeek is an open-source generative AI chatbot that competes with ChatGPT, Google’s Gemini, and Anthropic’s Claude. Unlike its rivals, DeepSeek is entirely free to use via a web application, requiring only an email or phone number for registration. DeepSeek stands out for its efficiency—achieving results comparable to ChatGPT with significantly fewer GPUs. While it excels in technical and mathematical domains, ChatGPT offers broader, context-aware responses across a wider range of topics. DeepSeek Web App vs. Local Hosting Users can access DeepSeek through its web and mobile apps or by hosting models locally via GitHub. When using DeepSeek’s web app, interactions occur on servers controlled by DeepSeek, subjecting users to its data-sharing policies. In contrast, local hosting allows organizations to maintain control over their data but shifts security responsibilities to the user. Key Security Risks of DeepSeek 1. Data Privacy & Government Oversight DeepSeek operates under China’s strict data laws, which require companies to cooperate with government authorities. Its privacy policy explicitly states that user data—including account details, input history, device metadata, and location data—is stored on servers in China, making it accessible to the Chinese government. This centralization raises concerns for businesses, as sensitive corporate data entered into DeepSeek may be subject to state oversight without notification. Some Western governments, such as Italy, have already banned DeepSeek over privacy concerns, while U.S. lawmakers are considering similar restrictions. 2. Open-Source Risks: Disinformation & Security Exploits DeepSeek’s open-source model offers flexibility but also creates risks: Unlike OpenAI and Google, which enforce strict content safety measures, DeepSeek’s open-source nature makes it more vulnerable to manipulation. 3. Centralized Data Storage Risks Most Western AI providers use decentralized, region-specific data centers to comply with privacy laws like GDPR. DeepSeek, however, stores all user data in China, raising concerns for international businesses handling sensitive information. 4. AI Hallucinations & Misinformation DeepSeek has been found to be more prone to AI hallucinations—where the model generates false or misleading information. This can lead to: 5. Encryption & Security Weaknesses Security audits of DeepSeek’s iOS app revealed several vulnerabilities: How DeepSeek Compares to ChatGPT & Gemini Security Factor DeepSeek ChatGPT Gemini Data Storage China-only Global, region-specific Global, region-specific Government Oversight Subject to China’s data laws U.S./EU privacy laws apply U.S./EU privacy laws apply Guardrail Protection Easier to bypass Strong, regularly updated Strong, regularly updated Transparency Limited public disclosures Security white papers, third-party audits Security white papers, third-party audits Should Businesses Use DeepSeek? Businesses handling sensitive information should exercise extreme caution when considering DeepSeek. Its centralized data storage in China, potential government oversight, and open-source vulnerabilities make it a higher-risk alternative compared to Western AI tools like ChatGPT and Gemini. Organizations concerned about data security should either avoid using DeepSeek’s web application or only interact with the model through local hosting to maintain control over their data. 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

May 5, 2025in AI Tools, Data, Generative AI, Google, Laws0 Comments

02May

The AI Agent Revolution

The AI Agent Revolution: How Tectonic is Unifying Disparate AI Systems for Enterprises AI agents are proliferating at breakneck speed—embedded in platforms, deployed as standalone apps, and built on proprietary or open-source SDKs. Yet as these intelligent systems multiply, enterprises face a critical challenge: getting them to communicate, collaborate, and scale effectively across complex IT environments. Recent moves by Tectonic, Salesforce, and Google Cloud highlight the next frontier of enterprise AI: seamless, cross-platform agent orchestration. We’ve reached an inflection point where human-AI synergy can transform business operations—but only if organizations can unify their agent ecosystems. The AI Agent Collaboration Challenge Today’s enterprises use AI agents for:✔ Salesforce’s Agentforce (CRM automation)✔ Google’s Agentspace (cloud-based workflows)✔ Custom agents (built on Vertex AI, OpenAI, or open-source models) But without interoperability, these agents operate in silos—limiting their potential. Tectonic bridges this gap with secure, enterprise-grade agent orchestration, enabling businesses to: Tectonic and Supported Agent OS: The Glue Holding AI Ecosystems Together Tectonic and Agent Operating Systems (OS) are business-focused platform for orchestrating AI agents across enterprise environments. An “agent operating system” (AOS) is a type of operating system designed to facilitate the development, deployment, and management of AI agents, which are software systems that can act autonomously to achieve goals. AOS systems aim to provide a platform for AI agents to operate efficiently and effectively, offering features like resource management, context switching, and tool integration. AIOS, for example, is a particular implementation of this concept that aims to address the challenges of managing large language model (LLM)-based AI agents How It Works Real-World Use Cases 1. Salesforce + Google Gemini: Smarter CRM Salesforce’s Agentforce now integrates Google Gemini, enabling:🔹 Better RAG (Retrieval-Augmented Generation) for faster, more accurate customer responses🔹 Predictive trend analysis embedded directly in CRM workflows Tectonic’s Role: Deploys multi-agent solutions that turn AI insights into actionable items—like auto-recommending next steps for sales teams. 2. Retail: Unified Customer Experiences A retailer combines: Result: Customers get instant, accurate updates on orders—no manual backend checks required. 3. Financial Services: AI-Powered Risk Analysis Banks use: Outcome: Suspicious transactions trigger automated compliance workflows without leaving Salesforce. Tectonic’s AI Activation Path: From Pilot to Production For enterprises ready to scale AI agents, Tectonic offers a rapid deployment framework:✅ Discovery and Road Mapping – Co-design high-impact use cases✅ Rapid Implementation – Deploy working agents in sandbox environments✅ Pre-Built Industry Libraries – Accelerate time-to-value The Future: Harmonized AI Ecosystems The biggest barrier to AI adoption isn’t technology—it’s fragmentation. With the Agent OS in place, businesses can finally:✔ Break down silos between Salesforce, Google Cloud, and custom AI✔ Automate complex workflows end-to-end✔ Scale AI responsibly with enterprise-grade governance The bottom line? AI agents are powerful alone—but unstoppable when unified. Ready to orchestrate your AI ecosystem?Discover how Tectonic’s Agentforce approach can transform your enterprise AI strategy. 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

May 2, 2025in Data, Enterprise, Google, Salesforce, Technology

21Apr

Copilots and Agents

Which Agentic AI Features Truly Matter? Modern large language models (LLMs) are often evaluated based on their ability to support agentic AI capabilities. However, the effectiveness of these features depends on the specific problems AI agents are designed to solve. The term “AI agent” is frequently applied to any AI application that performs intelligent tasks on behalf of a user. However, true AI agents—of which there are still relatively few—differ significantly from conventional AI assistants. This discussion focuses specifically on personal AI applications rather than AI solutions for teams and organizations. In this domain, AI agents are more comparable to “copilots” than traditional AI assistants. What Sets AI Agents Apart from Other AI Tools? Clarifying the distinctions between AI agents, copilots, and assistants helps define their unique capabilities: AI Copilots AI copilots represent an advanced subset of AI assistants. Unlike traditional assistants, copilots leverage broader context awareness and long-term memory to provide intelligent suggestions. While ChatGPT already functions as a form of AI copilot, its ability to determine what to remember remains an area for improvement. A defining characteristic of AI copilots—one absent in ChatGPT—is proactive behavior. For example, an AI copilot can generate intelligent suggestions in response to common user requests by recognizing patterns observed across multiple interactions. This learning often occurs through in-context learning, while fine-tuning remains optional. Additionally, copilots can retain sequences of past user requests and analyze both memory and current context to anticipate user needs and offer relevant suggestions at the appropriate time. Although AI copilots may appear proactive, their operational environment is typically confined to a specific application. Unlike AI agents, which take real actions within broader environments, copilots are generally limited to triggering user-facing messages. However, the integration of background LLM calls introduces a level of automation beyond traditional AI assistants, whose outputs are always explicitly requested. AI Agents and Reasoning In personal applications, an AI agent functions similarly to an AI copilot but incorporates at least one of three additional capabilities: Reasoning and self-monitoring are critical LLM capabilities that support goal-oriented behavior. Major LLM providers continue to enhance these features, with recent advancements including: As of March 2025, Grok 3 and Gemini 2.0 Flash Thinking rank highest on the LMArena leaderboard, which evaluates AI performance based on user assessments. This competitive landscape highlights the rapid evolution of reasoning-focused LLMs, a critical factor for the advancement of AI agents. Defining AI Agents While reasoning is often cited as a defining feature of AI agents, it is fundamentally an LLM capability rather than a distinction between agents and copilots. Both require reasoning—agents for decision-making and copilots for generating intelligent suggestions. Similarly, an agent’s ability to take action in an external environment is not exclusive to AI agents. Many AI copilots perform actions within a confined system. For example, an AI copilot assisting with document editing in a web-based CMS can both provide feedback and make direct modifications within the system. The same applies to sensor capabilities. AI copilots not only observe user actions but also monitor entire systems, detecting external changes to documents, applications, or web pages. Key Distinctions: Autonomy and Versatility The fundamental differences between AI copilots and AI agents lie in autonomy and versatility: If an AI system is labeled as a domain-specific agent or an industry-specific vertical agent, it may essentially function as an AI copilot. The distinction between copilots and agents is becoming increasingly nuanced. Therefore, the term AI agent should be reserved for highly versatile, multi-purpose AI systems capable of operating across diverse domains. Notable examples include OpenAI’s Operator and Deep Research. 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 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

April 21, 2025in Agentic AI, AI Tools, Data, Google, Salesforce

20Apr

Salesforce’s AI Evolution:

Salesforce’s AI Evolution: Efficiency, Expansion, and What Comes Next Salesforce isn’t just a CRM giant anymore—it’s becoming a central hub for AI-driven enterprise automation. Its Agentforce platform, already in use by over 3,000 customers, is proving its worth, both for clients and internally. The company has automated 380,000 support requests with an 84% resolution rate without human intervention, while sales productivity has jumped 7% thanks to AI-generated leads. But the bigger story might be how Salesforce is changing the way businesses pay for AI. Moving toward consumption-based pricing—charging based on how much companies use AI agents and data—means revenue might fluctuate, but it also aligns with how modern tech scales. And with $37.9 billion in FY25 revenue (up 9% YoY) and net income surging 50%, Salesforce has the financial muscle to experiment. What’s Driving the AI Growth? The Risks: Unpredictability in the Shift The move to usage-based pricing means revenue could swing with customer adoption rates. If businesses are slow to ramp up AI usage, growth could stall. But if adoption accelerates—as it has internally, where AI has boosted engineering productivity by 30%—this model could pay off big. The Bottom Line Salesforce is betting that AI will make it indispensable to enterprises. With strong financials, a growing AI customer base, and smart partnerships, it’s well-positioned—but the real test will be whether businesses fully embrace AI agents at scale. If they do, Salesforce could become far more than a CRM. (Originally published on wdstock, April 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

April 20, 2025in AgentExchange, Agentforce Platform, Data, Enterprise, Google, Salesforce

14Apr

What Does the Salesforce Google Cloud Partnership Mean?

Salesforce and Google Cloud Expand AI Partnership: What It Means for Your Business Enterprise AI is evolving at an unprecedented pace. This week, Salesforce and Google Cloud announced a major expansion of their strategic partnership, promising to give businesses greater flexibility, power, and choice in building AI-driven customer experiences and data strategies. This collaboration isn’t just about new technology—it’s about reimagining how businesses engage customers, unlock insights, and drive efficiency with AI. But what does that mean in practical terms? Let’s break down the top key opportunities. Why This Matters for Your Business In today’s business arena, AI isn’t just an advantage—it’s a necessity. With this partnership, businesses can: ✅ Unify Data Seamlessly – Break down silos with a zero-copy architecture, eliminating data fragmentation.✅ Leverage AI Flexibility – Choose predictive, generative, and multi-modal AI models without vendor lock-in.✅ Ensure Trust & Security – Use bias detection, explainability tools, and enterprise-grade security.✅ Streamline Workflows – Automate processes across Salesforce, Google Cloud, and other key platforms. This partnership isn’t just about adding AI—it’s about creating an intelligent, unified ecosystem that connects data, applications, and AI models. AI in Action: How Businesses Can Benefit 1️⃣ Smarter, Faster Customer Support with AI Agents With Salesforce Agentforce powered by Google Gemini AI, businesses can deploy multi-modal AI agents that handle text, images, audio, and video, creating more natural and intelligent customer interactions. 🔹 AI-Powered Insurance ClaimsA customer submits an insurance claim by uploading images of car damage and leaving an audio voicemail. Agentforce can:✔️ Analyze both the image and audio to assess the claim.✔️ Cross-check details using real-time Google Search grounding.✔️ Generate a claim recommendation in seconds, reducing wait times. 🔹 AI-Driven Contact CentersSupport agents struggle to gauge frustration over the phone. With Google Cloud AI in Service Cloud, businesses can:✔️ Analyze tone and sentiment in real time.✔️ Escalate calls automatically when frustration is detected.✔️ Provide AI coaching to help agents respond effectively. 2️⃣ Proactive Business Insights: AI That Thinks Ahead AI doesn’t just respond to customer needs—it anticipates them. By integrating Salesforce Data Cloud with Google BigQuery and Vertex AI, businesses can predict and prevent issues before they arise. 🔹 AI-Powered Supply Chain Risk DetectionA global retailer can:✔️ Monitor real-time risks (weather, port congestion, geopolitical issues).✔️ Predict delays before they happen.✔️ Automatically adjust supply routes to minimize disruptions. 🔹 AI-Driven Sales Forecasting & Lead ScoringWith Gemini AI inside Agentforce, sales teams can:✔️ Predict lead conversion rates with AI-driven analytics.✔️ Analyze customer intent from emails, calls, and social interactions.✔️ Get AI-powered recommendations to optimize outreach. 3️⃣ Hyper-Personalized Customer Experiences Customers expect brands to know them. With Salesforce Data Cloud + Google AI, businesses can deliver personalized experiences at scale. 🔹 AI-Powered Shopping AssistantsA luxury e-commerce brand can:✔️ Let customers upload a photo of an item they love.✔️ Use AI to identify similar products and make recommendations.✔️ Incorporate real-time sentiment analysis to refine suggestions. 🔹 AI-Driven Dynamic Pricing & PromotionsA travel company using Salesforce Data Cloud + Vertex AI can:✔️ Analyze real-time demand, competitor pricing, and customer behavior.✔️ Dynamically adjust pricing and offer personalized promotions.✔️ Deploy A/B tests to optimize revenue strategies. 4️⃣ A Unified Data Strategy for Smarter Decisions The biggest advantage of this partnership? Seamless connectivity between Salesforce Data Cloud, Vertex AI, BigQuery, Tableau, and Looker, creating AI-powered business intelligence. 🔹 AI-Powered Business DashboardsA global enterprise with multiple CRM and ERP systems can:✔️ Consolidate real-time data without duplication.✔️ Use AI-powered insights to surface key trends.✔️ Automate predictive analytics dashboards for proactive decision-making. 🔹 AI-Driven Revenue IntelligenceA SaaS company can:✔️ Analyze churn risk and upsell opportunities.✔️ Use AI-driven insights to optimize sales and marketing.✔️ Deploy custom Vertex AI models directly in Salesforce workflows. The Takeaway The Salesforce-Google Cloud partnership brings unmatched AI and data capabilities to businesses, enabling: ✅ Seamless data unification for smarter decision-making.✅ AI-powered automation to reduce workload and drive efficiency.✅ Advanced AI models for hyper-personalized customer experiences. As AI adoption accelerates, businesses that invest in the right strategy today will lead tomorrow. With Salesforce Data Cloud and Google Vertex AI, companies can embrace AI confidently, break down data silos, and drive transformation like never before. 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 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

April 14, 2025in Data, Enterprise, Google, Google Analytics, Salesforce, Salesforce Data Cloud, Technology

01Apr

AI Model Race Intensifies

AI Model Race Intensifies as OpenAI, Google, and DeepSeek Roll Out New Releases The generative AI competition is heating up as major players like OpenAI, Google, and DeepSeek rapidly release upgraded models. However, enterprises are shifting focus from incremental model improvements to agentic AI—systems that autonomously perform complex tasks. Three Major Releases in 24 Hours This week saw a flurry of AI advancements: Competition Over Innovation? While the rapid releases highlight the breakneck pace of AI development, some analysts see diminishing differentiation between models. The Future: Agentic AI & Real-World Use Cases As model fatigue sets in, businesses are focusing on domain-specific AI applications that deliver measurable ROI. The AI race continues, but the real winners will be those who translate cutting-edge models into practical, agent-driven solutions. Key Takeaways:✔ DeepSeek’s open-source V3 pressures rivals to embrace transparency.✔ GPT-4o’s hyper-realistic images raise deepfake concerns.✔ Gemini 2.5 focuses on structured reasoning for complex tasks.✔ Agentic AI, not just model upgrades, is the next enterprise priority. 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

April 1, 2025in Agentic AI, Enterprise, Generative AI, Google

01Apr

AI Agents Are About to Disrupt Your Marketing Channels

AI Agents Are About to Disrupt Your Marketing Channels—Here’s How to Adapt The Future of Marketing Isn’t Human-Centric—It’s Agent-Driven AI agents are poised to revolutionize how brands and consumers interact. These autonomous systems don’t just assist—they research, decide, and transact on behalf of users, fundamentally altering the role of traditional marketing channels. Google knows this. That’s why it’s replacing traditional search with Gemini, an AI agent that delivers answers, not just links. Meta is integrating AI across WhatsApp and Messenger, enabling two-way, large-scale brand interactions. Soon, every channel—email, social, loyalty programs, even your website—will become an AI-powered research and transaction hub. The question isn’t if this will impact your marketing strategy—it’s how soon. What Are AI Agents—And Why Should Marketers Care? AI agents are the next evolution of autonomous AI, combining:✅ Generative AI (content creation, personalization)✅ Predictive AI (data-driven decision-making)✅ Complex task execution (end-to-end customer journeys) Today’s challenge? Most companies struggle to move from AI experimentation to real-world impact. Agents change that—they bridge the gap between hype and execution, turning AI potential into measurable business results. 3 Ways to Future-Proof Your Channel Strategy 1. Build a Bulletproof Data Foundation (Now) AI agents won’t just use data—they’ll demand it to make decisions for customers. 🔹 Example: A customer asks an agent, “Find me the best CRM for small businesses.”🔹 Without structured data: The agent may overlook your product.🔹 With optimized data: Your CRM appears as a top recommendation, complete with pricing, features, and a seamless sign-up link. Action Step: Audit your product data, pricing, and USPs. Ensure they’re machine-readable and easily accessible to AI-driven platforms. 2. Rethink “Channels” as AI Conversation Hubs Traditional marketing funnels (search → browse → convert) will collapse. Instead: Action Step: Optimize for AI-native experiences—structured FAQs, API-accessible pricing, and instant conversion paths. 3. Prepare for AI-to-AI Negotiation B2B and high-consideration purchases (e.g., SaaS, automotive, real estate) will see AI agents negotiating deals on behalf of users. 🔹 Example: A corporate procurement AI evaluates your software against competitors, automatically requesting discounts or custom terms.🔹 Winners will be brands that enable AI-friendly decision-making (clear pricing, comparison data, instant approvals). Action Step: Develop agent-friendly sales collateral—dynamic pricing tables, competitor comparisons, and API-driven contract automation. The Bottom Line: Adapt or Get Displaced The shift to agent-driven marketing isn’t gradual—it’s exponential. Companies that wait will find themselves invisible to AI intermediaries shaping customer decisions. Your roadmap: The future belongs to marketers who design for AI-first experiences. The time to act is now. “AI agents won’t just change marketing—they’ll redefine it. The brands that win will be those that engineer their systems for machines, not just people.”—Salesforce AI Research, 2024 Ready to future-proof your strategy? Contact Tectonic. 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

April 1, 2025in Agentforce Platform, Data, Generative AI, Google, Salesforce, Salesforce Implementation Services, Salesforce Marketing Automation

29Mar

AI Agents

What AI Agents Are Available on the Market? Limitations of Operator, Computer Use, and Similar Agents OpenAI Operator can be seen as a semi-autonomous agent, but many users note that it asks too many questions and requires excessive confirmations, even in situations that pose no risk:“Operator is like driving a car with cruise control — occasionally taking your foot off the pedals — but it’s far from full-blown autopilot.” Furthermore, although Operator is technically designed to interact with any website, in reality, it’s far from a universal solution. It works reliably on a predefined set of platforms for tasks like shopping and restaurant reservations (such as Instacart and OpenTable), where its functionality has been tested. But outside of these, its performance is inconsistent — sometimes even generating incorrect or entirely fabricated data. Google’s Project Mariner, which aims to offer similar capabilities within Chrome, remains in closed beta for now. Meanwhile, many are eagerly anticipating a consumer product from Claude, which released the API for its Claude Computer Use agent (built on a slightly different principles) back in October 2024. One thing seems certain, though — it will be even more “cautious” than Operator, meaning it’s unlikely to handle tasks like sending emails or posting on social media on your behalf. Thus, browser-based agents come with at least two key limitations:— they work reliably only on a predefined set of websites;— certain actions are prohibited (for example, allowing an agent to send emails autonomously could create conflicts between its owner and others). Mobile agents face similar constraints. Take Perplexity Assistant, one of the earliest attempts at a “versatile” mobile AI agent — it still supports only a limited range of apps where it can operate on behalf of the user. Deep Research Agents To highlight the contrast, let’s look at AI agents built specifically for deep research. This category has seen a surge in new tools recently, and they deliver significantly better results than standard AI-powered web search. Deep Research tools qualify as AI agents due to their high level of autonomy. At this stage, no truly agentic tool exists that can handle any problem on our behalf — even in a semi-autonomous mode, let alone a fully autonomous one. However, there are highly effective agents within specific domains, such as deep research agents. With that in mind, let’s categorize typical AI applications into several groups (use cases) and tackle the following question for each group. 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

March 29, 2025in Data, Google, Salesforce

16Mar

The Evolving Role of AI Agents in Key Industries

Legal Services The future of AI in the legal field lies in deeper collaboration between human lawyers and AI systems. AI agents will handle routine document processing, contract analysis, and compliance checks, while legal professionals focus on strategy, negotiation, and final validation. This approach ensures efficiency without compromising accuracy or legal accountability. Finance The financial sector has been an early adopter of AI agents, leveraging them for market analysis, trading, and risk management. 1. Market Analysis & Research 2. Trading & Investment 3. Risk Management Current Limitations: While results are promising, financial AI applications require strict risk management and regulatory oversight. Most firms start with narrowly scoped use cases—such as single-asset trading—before expanding into complex portfolio management. Research & Science AI agents are transforming scientific research by accelerating discovery while maintaining rigorous methodology. A multi-agent approach is proving valuable throughout the research lifecycle: This framework has already shown success in chemistry, where AI agents have identified novel catalysts and reaction pathways. With Google’s Gemini Deep Research, AI-driven knowledge synthesis is expanding beyond specialized fields to broader scientific domains. Challenges & Considerations: The key to success is integrating AI agents into existing research methodologies while preserving scientific rigor. Emerging AI Agent Trends Across industries, three core patterns define the evolution of AI agents: While AI agents hold immense potential, most industries remain in an experimental phase of adoption. Many organizations start with Retrieval-Augmented Generation (RAG) before advancing to fully autonomous agents. The Challenge of Implementation Adopting AI agents requires careful evaluation of their benefits vs. complexity: Organizations must balance innovation, security, and operational efficiency to maximize the impact of AI agents in their industries. 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

March 16, 2025in Data, Enterprise, Google

12Mar

Google Expands AI Search Capabilities with Gemini 2.0

Google is taking a significant leap forward in AI-powered search with the introduction of Gemini 2.0, expanding its experimental AI features to enhance complex search queries. This update broadens AI accessibility and introduces new capabilities for handling intricate searches. Enhanced AI Overviews Rolling Out in the U.S. The first phase of this expansion is launching in the United States, with AI Overviews gaining improved functionality. This enhancement enables Google Search to tackle more complex queries, including coding and advanced math problems. While there’s no confirmed timeline for its availability in other regions, such features typically expand to Europe and beyond over time. The Impact of Gemini 2.0 Gemini 2.0 brings faster, higher-quality AI responses, making AI-driven search more effective in handling nuanced and sophisticated questions. The deeper integration of AI into search marks a substantial step toward a more intuitive and powerful search experience. AI-Only Search: A Possible Future? Google is also experimenting with an AI-first search model, which could shift the traditional search experience away from classic blue links and toward AI-generated summaries. This would fundamentally change the way users interact with search engines. However, given how ingrained traditional search behavior is, the shift to an AI-dominated search model remains uncertain. AI Mode in Search Labs Further advancing its AI search capabilities, Google is introducing AI Mode within Search Labs. Designed for complex, multi-part queries, AI Mode leverages advanced reasoning to consolidate what would have previously required multiple searches into a single, AI-generated response. Initially, AI Mode will be available exclusively to Google One AI Premium subscribers through the Labs program. This phased rollout allows Google to gather feedback and refine the feature before making it widely available. As AI continues to reshape search, Google’s latest innovations signal a shift toward a more intelligent, context-aware search experience—one that may redefine how we find information online. 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

March 12, 2025in Google

11Mar

When to Use AI Agents and Copilots

Do Organizations Need AI Agents or Copilots for These Use Cases? Organizations often explore AI solutions for specific operational needs. Three primary AI use cases include: The question arises: Which AI tools best suit these needs? Should an organization invest in a high-end AI subscription, such as ChatGPT Pro with the Operator agent ($200/month), or opt for ChatGPT Plus with the o3-mini reasoning model and copilot features, such as memory and custom GPTs? AI Tool Selection Criteria When evaluating AI agents versus AI copilots, key considerations include: A. The time and effort required to articulate the problem for the AI. B. The level of control preferred in the problem-solving process. C. The importance of achieving the most optimal outcome. Use Case 1: Shopping AI Agents Many existing AI shopping solutions are labeled as agents, but they do not exhibit true autonomy. Instead, they serve as assistants with limited capabilities. For instance, Perplexity’s “Shop Like a Pro” assists with selecting products but depends on vendor integration for completing purchases, rather than executing transactions autonomously. Despite current limitations, some users create their own AI shopping agents by integrating browser-based AI tools with no-code automation platforms like n8n, Zapier, or Make.com. These custom-built agents offer greater autonomy and versatility than off-the-shelf solutions. However, the need for AI agents in shopping remains debatable. The act of shopping often provides a sense of anticipation and engagement, which a fully autonomous AI agent could eliminate. In contrast, AI copilots can enhance the experience by reducing time investment while preserving user involvement. The same applies to vacation planning—while an AI agent could book optimal flights and accommodations, many users prefer a guided approach to maintain a sense of anticipation and control. Moreover, financial transactions should not be fully entrusted to AI agents due to potential risks. AI-powered form-filling can be beneficial, but human oversight remains essential. The decision to use an AI agent for shopping depends on how much involvement users wish to retain in the process. Use Case 2: Executive AI Assistant Many professionals seek AI-driven solutions to handle routine tasks such as scheduling, reminders, and email management. However, current AI assistants lack full autonomy in managing these activities comprehensively. For instance, Google’s Gemini Advanced provides AI-powered features in Google Calendar and Gmail, but its integration remains limited—requiring manual activation and lacking full interconnectivity between tasks. Similarly, Apple Intelligence offers fragmented AI functionalities rather than a seamless assistant experience. Some technically inclined users have developed custom executive assistants using automation tools. However, for the broader market, fully functional, user-friendly AI executive assistants are still in development by major tech companies. When evaluating the necessity of AI agents in routine tasks, the key factors include: Use Case 3: AI Research Deep research AI agents have significantly outperformed traditional search methods in both speed and accuracy, provided sufficient relevant data is available. Advanced AI-driven research tools, such as Perplexity Deep Research and Grok 3 DeepSearch, have demonstrated superior efficiency compared to manual search. Despite their capabilities, these agents often require refinement in their responses. AI-generated reports may focus on irrelevant details without proper guidance. However, many researchers find that leveraging AI significantly enhances the efficiency and breadth of their work. For organizations, the decision to utilize AI agents for research depends on their need for: While AI agents remain imperfect, they are rapidly evolving, particularly in deep research applications. As technology advances, their ability to support decision-making processes will likely continue to expand. 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

March 11, 2025in AI Tools, Data, Google, Technology

06Mar

Google and Salesforce Expand Partnership

Google and Salesforce Expand Partnership to Enhance AI Agent Capabilities Google and Salesforce are deepening their collaboration to provide customers with greater flexibility in AI agent deployment. This expanded partnership will integrate Google Gemini within Salesforce’s Agentforce platform, enabling AI agents to process images, audio, and video with advanced multimodal capabilities. Enhanced AI Functionality with Gemini Through this integration, AI agents will gain access to Gemini’s powerful models, allowing them to handle complex tasks with extended context windows and leverage real-time insights from Google Search via Vertex AI. This collaboration aims to empower businesses with AI solutions that are not limited to a single model provider, offering crucial flexibility in AI customization. Srini Tallapragada, Salesforce’s President and Chief Engineering and Customer Success Officer, emphasized that the integration offers customers the ability to choose the applications and models that best suit their needs. “Salesforce offers a complete enterprise-grade agentic AI platform that makes it easy to deploy new capabilities quickly and realize business value fast. Google Cloud is a pioneer in enterprise agentic AI, offering some of the most powerful models, agents, and AI development tools on the planet. Together, we are creating the best place for businesses to scale with digital labor.” Key Benefits of the Integration The partnership is set to deliver significant advantages for businesses, as outlined in the official announcement: Thomas Kurian, CEO of Google Cloud, highlighted the benefits of this collaboration: “Our mutual customers have asked for seamless integration across Salesforce and Google Cloud. This expanded partnership enables them to accelerate AI transformations with state-of-the-art AI models, agentic AI, and advanced data analytics.” Strengthening Customer Service Integrations The partnership will also enhance the connection between Salesforce Service Cloud and Google Cloud’s Customer Engagement Suite, providing AI-driven improvements to customer support. Key upcoming features include: Expanding AI-Powered Decision-Making Beyond Gemini, Agentforce will integrate Google Search through Vertex AI, leveraging secure connections between Salesforce Data Cloud and Google BigQuery. This will enable AI agents to access real-time information for improved accuracy and decision-making. For example, in supply chain management, AI can track shipments, monitor inventory in Salesforce Commerce Cloud, and anticipate disruptions using real-time data on weather, port congestion, and geopolitical events. Additionally, joint customers will be able to utilize Salesforce’s unified platform—including Agentforce, Data Cloud, and Customer 360—on Google Cloud’s AI-optimized infrastructure. This integration ensures enhanced security through dynamic grounding, zero data retention, and toxicity detection via the Einstein Trust Layer. Businesses will also soon have the option to purchase Salesforce products via the Google Cloud Marketplace. More AI Innovations from Google and Salesforce Google recently announced the development of a personalized AI-powered chatbot that will be integrated into its devices, including smartphones, laptops, and tablets. This tool will automatically answer calls, process requests, and respond on behalf of users. Meanwhile, Salesforce’s Service Assistant—formerly known as Salesforce Service Planner—has launched on Service Cloud. Designed to support live agents, it generates step-by-step plans for resolving customer inquiries by analyzing intent, case history, and customer context. For optimal performance, Salesforce recommends integrating it with Data Cloud and the contact center knowledge base. With this expanded partnership, Google and Salesforce are setting the stage for businesses to leverage cutting-edge AI technology, driving innovation and operational efficiency across industries. 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

March 6, 2025in Agentforce Platform, Agentic AI, Data, Enterprise, Google, Salesforce, Salesforce Commerce Cloud, Salesforce Data Cloud, Salesforce Service Cloud, Technology

28Feb

The Coalition for Sustainable AI

The Coalition for Sustainable AI: Aligning AI Development with Environmental Responsibility The rapid rise of artificial intelligence (AI) presents both groundbreaking opportunities and significant environmental challenges. Recognizing the need for responsible AI development, France, the United Nations Environment Programme (UNEP), and the International Telecommunication Union (ITU) have established the Coalition for Sustainable AI—a global, multi-stakeholder initiative dedicated to ensuring AI supports sustainability rather than exacerbating environmental harm. A Shared Vision for Sustainable AI The Coalition for Sustainable AI, launched at the Paris AI Action Summit 2025, brings together public and private sector leaders to align AI advancements with environmental goals. The initiative seeks to: Why This Coalition Matters As AI infrastructure becomes as fundamental as water, energy, and transport, its environmental implications must be addressed proactively. AI technologies have the potential to redefine entire industries—just as the Industrial Revolution once did—while offering unprecedented capabilities to tackle climate change, optimize resource management, and enhance environmental decision-making. By bringing together a diverse network of stakeholders, the Coalition recognizes that the digital and AI revolution and the environmental crisis are two defining challenges of our time. Mission and Leadership The Coalition operates under two core principles: Founding Leaders: Driving Global Collaboration The Coalition’s role extends beyond advocacy. It serves as a platform to: This initiative will also maintain momentum through major global forums such as AI Summits, COP conferences, and other international policy discussions, ensuring AI remains at the forefront of sustainability efforts. Industry Leaders Join the Movement The Coalition for Sustainable AI has already attracted a diverse group of corporations, research institutions, NGOs, investors, and public sector organizations committed to this mission. Corporate Members Include: Salesforce, Nvidia, IBM, Hugging Face, Capgemini, Thales, Schneider Electric, Philips, TotalEnergies, Baidu, Orange, L’Oréal Groupe, Mistral AI, AMD, Dassault Systèmes, and more. Research Institutions and NGOs: Stockholm Environment Institute, Mila, Vrije Universiteit Amsterdam, Università di Pavia, Climate Change AI, The Shift Project, Royal Academy of Engineering, and others. Investors and Public Sector Representatives: Ardian, Crédit Agricole, Eurazeo, Mirova, BPI France, the Republic of Serbia’s Ministry of Science, and more. Salesforce’s Commitment to AI Sustainability Boris Gamazaychikov, Head of AI Sustainability at Salesforce, emphasized the importance of this initiative, stating: “I’m proud that Salesforce is one of the initial members, and I hope that many more join on this critical journey. Thanks to the French Government, UNEP, and ITU for organizing this important initiative.” Looking Ahead: The Future of Sustainable AI The Coalition for Sustainable AI marks a critical step toward ensuring that AI serves as a force for climate action, biodiversity preservation, and sustainable development. As AI continues to reshape the global economy, initiatives like this will help balance technological progress with environmental responsibility. With momentum building and more organizations joining the effort, the Coalition aims to drive lasting impact—paving the way for a future where AI and sustainability go hand in hand. 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

February 28, 2025in Artificial Intelligence

24Feb

Salesforce and Google Announcement

Salesforce (NYSE:CRM) has entered into a deal with Google (NASDAQ:GOOGL) to offer its customer relations management software, Agentforce artificial intelligence assistants, and Data Cloud offerings through Google Cloud, the companies announced today. Google and Salesforce already have many of the same clients, and this new deal will allow for more product integration between Google Workspace and Salesforce’s customer relationship management and AI offerings. Salesforce already uses Amazon (AMZN) Web Services for much of its cloud computing. “Our mutual customers have asked us to be able to work more seamlessly across Salesforce and Google Cloud, and this expanded partnership will help them accelerate their AI transformations with agentic AI, state-of-the-art AI models, data analytics, and more,” said Thomas Kurian, CEO of Google Cloud. The deal is expected to total $2.5B over the next seven years, according to a report by Bloomberg. Salesforce and Google today announced a major expansion of their strategic partnership, delivering choice in the models and capabilities businesses use to build and deploy AI-powered agents. In today’s constantly evolving AI landscape, innovations like autonomous agents are emerging so quickly that businesses struggle to keep pace. This expanded partnership provides crucial flexibility, empowering customers to develop tailored AI solutions that meet their specific needs, rather than being locked into a single model provider. Google Cloud is at the forefront of enterprise AI innovation with millions of developers building with Google’s cutting-edge Gemini models and on Google Cloud’s AI-optimized infrastructure. This expanded partnership will empower Salesforce customers to build Agentforce agents using Gemini and to deploy Salesforce on Google Cloud. This is an expansion of the existing partnership that allows customers to use data from Data Cloud and Google BigQuery bi-directionally via zero-copy technology—further equipping customers with the data, AI, trust, and actions they need to bring autonomous agents into their businesses. Additionally, this integration empowers Agentforce agents with the ability to reference up-to-the-minute data, news, current events, and credible citations, substantially enhancing their contextual awareness and ability to deliver accurate, evidence-backed responses. For example, in supply chain management and logistics, an agent built with Agentforce could track shipments and monitor inventory levels in Salesforce Commerce Cloud and proactively identify potential disruptions using real-time data from Google Search, including weather conditions, port congestion, and geopolitical events. Availability is expected in the coming months. AI: Unlocking the Power of Choice and Flexibility with Gemini and Agentforce Businesses need the freedom to choose the best models for their needs rather than be locked into one vendor. In 2025, Google’s Gemini models will also be available for prompt building and reasoning directly within Agentforce. With Gemini and Agentforce, businesses will benefit from: For example, an insurance customer can submit a claim with photos of the damage and an audio voicemail from a witness. Agentforce, using Gemini, can then help the insurance provider deliver better customer experiences by processing all these inputs, assessing the claim’s validity, and even using text-to-speech to contact the customer with a resolution, streamlining the traditionally lengthy claims process. Availability is expected this year. Trust: Salesforce Platform deployed on Google Cloud Customers will be able to use Salesforce’s unified platform (Agentforce, Data Cloud, Customer 360) on Google Cloud’s highly secure, AI-optimized infrastructure, benefiting from features like dynamic grounding, zero data retention, and toxicity detection provided by the Einstein Trust Layer. Once Salesforce products are available on Google Cloud, customers will also have the ability to procure Salesforce offerings through the Google Cloud Marketplace, opening up new possibilities for global businesses to optimize their investments across Salesforce and Google Cloud and benefiting thousands of existing joint customers. Action: Enhanced Employee Productivity and Customer Service with AI-Powered Integrations Millions use Salesforce and Google Cloud daily. This partnership prioritizes choice and flexibility, enabling seamless cross-platform work. New and deeper connections between platforms like Salesforce Service Cloud and Google Cloud’s Customer Engagement Suite, as well as Slack and Google Workspace, will empower AI agents and service representatives with unified data access, streamlined workflows, and advanced AI capabilities, regardless of platform. Salesforce and Google Cloud are deeply integrating their customer service platforms—Salesforce Service Cloud and Google Cloud’s Customer Engagement Suite—to create a seamless and intelligent support experience. Expected later this year, this unified approach empowers AI agents in Service Cloud with: Salesforce and Google Cloud are also exploring deeper integrations between Slack and Google Workspace, boosting productivity and creating a more cohesive digital workspace for teams and organizations. The companies are currently exploring use cases such as: Expanding Partnership Capabilities and Integrations This partnership goes beyond core product integrations to deliver a more connected and intelligent data foundation for businesses. Expected availability throughout 2025: This landmark partnership between Salesforce and Google represents a strategic paradigm shift in enterprise AI deployment, emphasizing infrastructure innovation, AI capability enhancement, and enterprise value. The integration of Google Search grounding provides a unique competitive advantage, offering real-time, factual responses backed by the world’s most comprehensive search engine. The companies are committed to ongoing innovation and deeper collaboration to empower businesses with even more powerful solutions. 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 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

February 24, 2025in Agentic AI, Artificial Intelligence, Data, Enterprise, Google, Salesforce, Salesforce Commerce Cloud, Salesforce Service Cloud, Technology

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