scalability Archives - gettectonic.com

28Apr

Salesforce Advanced Routing

Salesforce Advanced Routing is a feature within the Salesforce Service Cloud that helps organizations efficiently route cases, leads, and other work items to the most appropriate agents or teams. This ensures that customer inquiries and issues are handled by the right person at the right time, improving response times, customer satisfaction, and overall operational efficiency. Key Features of Salesforce Advanced Routing: Benefits of Salesforce Advanced Routing: Use Cases: Implementation Considerations: In summary, Salesforce Advanced Routing is a powerful tool that helps organizations efficiently manage and route work items to the most appropriate agents or teams. By leveraging features like omni-channel routing, skill-based routing, and real-time routing, businesses can improve customer experience, increase agent efficiency, and optimize their overall operations. 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 28, 2025in Data, Enterprise, Salesforce, Salesforce Einstein, Salesforce Service Cloud0 Comments

25Apr

Embracing “Intelligent Austerity”

Embracing “Intelligent Austerity”: How Scotland Can Lead the Way in Public Sector Innovation As the UK Government enforces a 15% reduction in operating costs across departments, the pressure to streamline workflows through generative AI has never been greater. While these targets have sparked concern in Westminster, Scotland’s legacy of innovation—from tidal energy to healthcare—positions it to redefine what austerity can achieve. Rather than resorting to blunt cuts that undermine services and hurt the most vulnerable constituents, Scotland has a unique opportunity to pioneer intelligent austerity: delivering significant cost savings and productivity gains without sacrificing the quality of essential public services. But how? A Smarter Approach to Public Services At Salesforce, we’re not just driving agentic transformation—we’re challenging governments to rethink efficiency. Our technology is already embedded across the UK public sector and beyond. With Agentforce, our goal isn’t to replace human workers but to empower them by eliminating repetitive, low-value tasks. When I speak with civil servants, I ask a simple question: “What parts of your day drain your productivity?” The answer is almost always the same: tedious administrative work that stifles innovation. The key to unlocking societal progress—whether in fighting child poverty, boosting the economy, or tackling climate change—lies in making small, daily efficiency gains. By automating routine tasks, we free up staff to focus on what they do best: high-impact, human-centric work. Agentforce serves as a practical blueprint for intelligent austerity, delivering lasting efficiencies while preserving—and even enhancing—the human touch in public services. Intelligent Austerity: Efficiency Without Sacrifice Traditional austerity often means deep, painful cuts that erode services and fuel public frustration. Intelligent austerity, by contrast, targets inefficiencies—like costly call centres and outdated administrative processes—while reinvesting savings where they matter most. Instead of lengthy, expensive IT overhauls that tie departments to consultants, we advocate for off-the-shelf AI solutions that deliver value in weeks, not years. These integrate seamlessly with existing systems, improving transparency, agility, and scalability from day one. The result? Departments can exceed cost-saving targets—even surpassing the 15% goal—without the downsides of traditional austerity. Agents in Action: Real-World Success Stories These examples prove that AI-driven transformation can counter fiscal pressures while improving service delivery—a win-win for both budgets and citizens. Scotland’s AI Opportunity Imagine every government department equipped with a 24/7 AI expert—an intelligent assistant capable of answering policy questions, processing documents, or even serving as a strategic advisor. Early AI adoption is like the first SatNav systems: helpful but imperfect. The real breakthrough comes when AI evolves into a collision avoidance system—actively preventing problems and enhancing decision-making. Our AI Agents Handbook outlines how Scotland can harness this potential. By adopting AI strategically, public services can achieve cost savings that are reinvested in key priorities—eradicating child poverty, growing the economy, and addressing the climate crisis. The Future: Smarter, More Agile Public Services AI isn’t about replacing humans—it’s about empowering them. With each small efficiency gain, departments become more agile, better equipped to deliver sustainable, high-quality services. Scotland has the chance to lead this shift, turning fiscal challenges into opportunities for innovation. Interested in learning more? Let’s discuss how AI Agents can transform your organization. Get in touch for a personalized consultation. 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 25, 2025in AI Tools, Generative AI, Generative AI Tools, Salesforce, Technology0 Comments

20Apr

Architecture for Enterprise-Grade Agentic AI Systems

LangGraph: The Architecture for Enterprise-Grade Agentic AI Systems Modern enterprises need AI that doesn’t just answer questions—but thinks, plans, and acts autonomously. LangGraph provides the framework to build these next-generation agentic systems capable of: ✅ Multi-step reasoning across complex workflows✅ Dynamic decision-making with real-time tool selection✅ Stateful execution that maintains context across operations✅ Seamless integration with enterprise knowledge bases and APIs 1. LangGraph’s Graph-Based Architecture At its core, LangGraph models AI workflows as Directed Acyclic Graphs (DAGs): This structure enables:✔ Conditional branching (different paths based on data)✔ Parallel processing where possible✔ Guaranteed completion (no infinite loops) Example Use Case:A customer service agent that: 2. Multi-Hop Knowledge Retrieval Enterprise queries often require connecting information across multiple sources. LangGraph treats this as a graph traversal problem: python Copy # Neo4j integration for structured knowledge from langchain.graphs import Neo4jGraph graph = Neo4jGraph(url=”bolt://localhost:7687″, username=”neo4j”, password=”password”) query = “”” MATCH (doc:Document)-[:REFERENCES]->(policy:Policy) WHERE policy.name = ‘GDPR’ RETURN doc.title, doc.url “”” results = graph.query(query) # → Feeds into LangGraph nodes Hybrid Approach: 3. Building Autonomous Agents LangGraph + LangChain agents create systems that: python Copy from langchain.agents import initialize_agent, Tool from langchain.chat_models import ChatOpenAI # Define tools search_tool = Tool( name=”ProductSearch”, func=search_product_db, description=”Searches internal product catalog” ) # Initialize agent agent = initialize_agent( tools=[search_tool], llm=ChatOpenAI(model=”gpt-4″), agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION ) # Execute response = agent.run(“Find compatible accessories for Model X-42”) 4. Full Implementation Example Enterprise Document Processing System: python Copy from langgraph.graph import StateGraph from langchain.embeddings import OpenAIEmbeddings from langchain.vectorstores import Pinecone # 1. Define shared state class DocProcessingState(BaseModel): query: str retrieved_docs: list = [] analysis: str = “” actions: list = [] # 2. Create nodes def retrieve(state): vectorstore = Pinecone.from_existing_index(“docs”, OpenAIEmbeddings()) state.retrieved_docs = vectorstore.similarity_search(state.query) return state def analyze(state): # LLM analysis of documents state.analysis = llm(f”Summarize key points from: {state.retrieved_docs}”) return state # 3. Build workflow workflow = StateGraph(DocProcessingState) workflow.add_node(“retrieve”, retrieve) workflow.add_node(“analyze”, analyze) workflow.add_edge(“retrieve”, “analyze”) workflow.add_edge(“analyze”, END) # 4. Execute agent = workflow.compile() result = agent.invoke({“query”: “2025 compliance changes”}) Why This Matters for Enterprises The Future:LangGraph enables AI systems that don’t just assist workers—but autonomously execute complete business processes while adhering to organizational rules and structures. “This isn’t chatbot AI—it’s digital workforce AI.” Next Steps: 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

April 20, 2025in Agentic AI, Data, Enterprise0 Comments

17Apr

AI and Automation

The advent of AI agents is widely discussed as a transformative force in application development, with much of the focus on the automation that generative AI brings to the process. This shift is expected to significantly reduce the time and effort required for tasks such as coding, testing, deployment, and monitoring. However, what is even more intriguing is the change not just in how applications are built, but in what is being built. This perspective was highlighted during last week’s Salesforce developer conference, TDX25. Developers are no longer required to build entire applications from scratch. Instead, they can focus on creating modular building blocks and guidelines, allowing AI agents to dynamically assemble these components at runtime. In a pre-briefing for the event, Alice Steinglass, EVP and GM of Salesforce Platform, outlined this new approach. She explained that with AI agents, development is broken down into smaller, more manageable chunks. The agent dynamically composes these pieces at runtime, making individual instructions smaller and easier to test. This approach also introduces greater flexibility, as agents can interpret instructions based on policy documents rather than relying on rigid if-then statements. Steinglass elaborated: “With agents, I’m actually doing it differently. I’m breaking it down into smaller chunks and saying, ‘Hey, here’s what I want to do in this scenario, here’s what I want to do in this scenario.’ And then the agent, at runtime, is able to dynamically compose these individual pieces together, which means the individual instructions are much smaller. That makes it easier to test. It also means I can bring in more flexibility and understanding so my agent can interpret some of those instructions. I could have a policy document that explains them instead of hard coding them with if-then statements.” During a follow-up conversation, Steinglass further explored the practical implications of this shift. She acknowledged that adapting to this new paradigm would be a significant change for developers, comparable to the transition from web to mobile applications. However, she emphasized that the transition would be gradual, with stepping stones along the way. She noted: “It’s a sea change in the way we build applications. I don’t think it’s going to happen all at once. People will move over piece by piece, but the result’s going to be a fundamentally different way of building applications.” Different Building Blocks One reason the transition will be gradual is that most AI agents and applications built by enterprises will still incorporate traditional, deterministic functions. What will change is how these existing building blocks are combined with generative AI components. Instead of hard-coding business logic into predetermined steps, AI agents can adapt on-the-fly to new policies, rules, and goals. Steinglass provided an example from customer service: “What AI allows us to do is to break down those processes into components. Some of them will still be deterministic. For example, in a service agent scenario, AI can handle tasks like understanding customer intent and executing flexible actions based on policy documents. However, tasks like issuing a return or connecting to an ERP system will remain deterministic to ensure consistency and compliance.” She also highlighted how deterministic processes are often used for high-compliance tasks, which are automated due to their strict rules and scalability. In contrast, tasks requiring more human thought or frequent changes were previously left unautomated. Now, AI can bridge these gaps by gluing together deterministic and non-deterministic components. In sales, Salesforce’s Sales Development Representative (SDR) agent exemplifies this hybrid approach. The definition of who the SDR contacts is deterministic, based on factors like value or reachability. However, composing the outreach and handling interactions rely on generative AI’s flexibility. Deterministic processes re-enter the picture when moving a prospect from lead to opportunity. Steinglass explained that many enterprise processes follow this pattern, where deterministic inputs trigger workflows that benefit from AI’s adaptability. Connections to Existing Systems The introduction of the Agentforce API last week marked a significant step in enabling connections to existing systems, often through middleware like MuleSoft. This allows agents to act autonomously in response to events or asynchronous triggers, rather than waiting for human input. Many of these interactions will involve deterministic calls to external systems. However, non-deterministic interactions with autonomous agents in other systems require richer protocols to pass sufficient context. Steinglass noted that while some partners are beginning to introduce actions in the AgentExchange marketplace, standardized protocols like Anthropic’s Model Context Protocol (MCP) are still evolving. She commented: “I think there are pieces that will go through APIs and events, similar to how handoffs between systems work today. But there’s also a need for richer agent-to-agent communication. MuleSoft has already built out AI support for the Model Context Protocol, and we’re working with partners to evolve these protocols further.” She emphasized that even as richer communication protocols emerge, they will coexist with traditional deterministic calls. For example, some interactions will require synchronous, context-rich communication, while others will resemble API calls, where an agent simply requests a task to be completed without sharing extensive context. Agent Maturity Map To help organizations adapt to these new ways of building applications, Salesforce uses an agent maturity map. The first stage involves building a simple knowledge agent capable of answering questions relevant to the organization’s context. The next stage is enabling the agent to take actions, transitioning from an AI Q&A bot to a true agentic capability. Over time, organizations can develop standalone agents capable of taking multiple actions across the organization and eventually orchestrate a digital workforce of multiple agents. Steinglass explained: “Step one is ensuring the agent can answer questions about my data with my information. Step two is enabling it to take an action, starting with one action and moving to multiple actions. Step three involves taking actions outside the organization and leveraging different capabilities, eventually leading to a coordinated, multi-agent digital workforce.” Salesforce’s low-code tooling and comprehensive DevSecOps toolkit provide a significant advantage in this journey. Steinglass highlighted that Salesforce’s low-code approach allows business owners to build processes and workflows,

April 17, 2025in AgentExchange, Agentic AI, Data, Enterprise, Generative AI, Mulesoft, Salesforce, Technology0 Comments

14Apr

Tectonic Shook Things Up at AgentForce World Tour in Denver

The Tectonic team attended Salesforce’s Denver AgentForce World Tour this week. It was a great experience to develop our AgentBlazer team and a true seismic time was had by all! AI Agents were the topic of conversation and kept things lively! One almost expected to meet an Agentic Robot around every corner. We were all excited to network with Salesforce, customers, and partners alike. Key Takeaways Autonomous AI agents can understand and interpret customers’ questions using natural language, with minimal human intervention. Here’s what you need to know. The AI Assistant Revolution: Empowering Every Employee Imagine if every person in your company—from the CEO to frontline employees—had a dedicated assistant at their fingertips. An assistant who:✔ Knows your customers inside out✔ Delivers instant, data-driven insights✔ Helps prioritize next best actions Thanks to AI agents, this future is already here—and it’s transforming how businesses operate. How AI Agents Are Supercharging Teams 1. Instant Insights, No Manual Work 🔹 Generative AI agents analyze your trusted customer data in seconds—eliminating hours of manual research.🔹 Sales, service, and marketing teams get real-time recommendations, allowing them to focus on high-impact work. 2. Scaling Teams Without Adding Headcount 🔹 AI agents handle routine tasks—customer inquiries, data entry, meeting prep—freeing employees for strategic work.🔹 Quickly ramp up productivity during peak demand without overburdening staff. 3. Proactive Problem-Solving 🔹 AI doesn’t just react—it predicts.🔹 Identifies risks, suggests optimizations, and prevents small issues from becoming big ones. 4. Personalized Support for Every Role 🔹 Sales: AI suggests the best leads, crafts follow-ups, and forecasts deals.🔹 Service: Resolves common cases instantly, escalating only when needed.🔹 Leadership: Delivers real-time business insights for faster decisions. The Future of Work Is AI-Augmented AI agents aren’t replacing humans—they’re empowering them. By automating the mundane and enhancing decision-making, they help teams:✅ Work smarter, not harder✅ Deliver better customer experiences✅ Stay ahead of the competition The question isn’t if your company should adopt AI agents—it’s how soon you can start leveraging them. Tectonic, a trusted Salesforce partner, is here to help. Ready to explore AI-powered productivity? Let’s talk about the right AI strategy for your business. AI Agents: Your Intelligent Digital Workforce What Is an AI Agent? An AI agent is an autonomous artificial intelligence system that understands, processes, and responds to customer inquiries—without human intervention. Built using platforms like Agentforce, these agents leverage machine learning (ML) and natural language processing (NLP) to handle tasks ranging from simple FAQs to complex problem-solving. Unlike traditional AI, which requires manual programming for each task, AI agents continuously learn and improve from interactions, becoming smarter over time. How Do AI Agents Work? AI agents operate through a seamless four-step process: 💡 Result? Faster resolutions, happier customers, and more efficient teams. 6 Game-Changing Benefits of AI Agents Feature Impact 1. 24/7 Availability Instant support across time zones. 2. Hyper-Efficiency Handle thousands of queries simultaneously—no wait times. 3. Smarter Escalations Auto-route complex cases to the best-suited human agent. 4. Personalized Experiences Tailor responses using real-time customer data. 5. Scalability Grow support capacity without hiring more staff. 6. Data-Backed Insights Uncover trends to optimize operations & CX. “72% of companies already deploy AI—with generative AI adoption accelerating.” – McKinsey AI Agents in Action: Industry Use Cases 🏦 Finance ✔ Personalized wealth advice based on spending habits✔ Auto-summarize client cases for faster resolutions 🏭 Manufacturing ✔ Predict equipment failures before they happen✔ Optimize supply chain decisions with real-time data 🛒 Retail & Consumer Goods ✔ Smart inventory tracking (e.g., flagging stock discrepancies)✔ AI-generated promo content for targeted campaigns 🚗 Automotive ✔ Proactive vehicle maintenance alerts via telematics✔ Dynamic dealership promotions to boost sales 🏥 Healthcare ✔ Automated patient scheduling with the right specialist✔ Clinical trial matching using AI-driven eligibility checks Join the AI Revolution with Agentforce AI agents aren’t just tools—they’re productivity multipliers that help teams:✅ Work faster with automated workflows✅ Serve customers better with personalized AI assistance✅ Stay ahead with predictive insights 📈 Ready to transform your business? Connect with Tectonic today, or check out our Agentforce Quickstart offering. Connect with the Tectonic Agentforce team and launch your Agentic Revolution. AI Agents: The Ultimate Productivity Multiplier for Every Team AI agents aren’t just transforming customer service—they’re revolutionizing how every department operates. From 24/7 customer support to hyper-personalized marketing campaigns, AI agents help teams work smarter, move faster, and deliver exceptional experiences. Here’s how AI agents supercharge key business functions: 🤝 AI Agents for Service Teams Never miss a customer inquiry—even at 2 AM.✔ Instant, 24/7 support across email, chat, and social media✔ Smart escalation—AI routes complex cases to human agents with full context✔ Brand-consistent responses powered by your CRM data 🔹 With Agentforce for Service, deploy AI agents in minutes using prebuilt templates—or customize them for your unique needs. 💰 AI Agents for Sales Teams Turn every lead into a conversation—automatically.✔ Autonomous lead engagement—AI answers product questions & books meetings✔ Always-on SDRs—Agentforce Sales Development Reps qualify leads 24/7✔ Controlled escalation—Set rules for when & how AI hands off to your team 🔹 No more missed opportunities—AI keeps your pipeline full while your reps focus on closing. 🛍️ AI Agents for Commerce Teams Personal shopping assistants—powered by AI.✔ Smart product recommendations based on browsing & purchase history✔ Guided shopping experiences—AI helps customers find what they need faster✔ Omnichannel support—Engage shoppers on your site, WhatsApp, and more 🔹 Boost conversions with AI that acts like your best sales associate—for every customer. 📢 AI Agents for Marketing Teams Campaigns that write, optimize, and improve themselves.✔ AI-generated campaign briefs—audience targeting, messaging & KPIs✔ Automated content creation—draft ads, emails & social posts in your brand voice✔ Performance optimization—AI analyzes results & suggests improvements 🔹 With Agentforce Campaigns, launch better campaigns in hours—not weeks. Why AI Agents? The Bottom Line ✅ Scale operations without scaling headcount✅ Deliver instant, personalized experiences 24/7✅ Free your team to focus on high-value work “Companies using AI agents see 40% faster response times and 30% higher customer satisfaction.” Ready to deploy your AI workforce? See how Agentforce can transform your business #FutureOfWork

April 14, 2025in Agentforce Platform, Artificial Intelligence, Data, Generative AI, Salesforce0 Comments

Salesforce Essentials and Salesforce Professional

09Apr

Benefits of Salesforce Essentials for Small Businesses

Salesforce Essentials: A Game-Changer for Small Businesses Salesforce is a leading force in the Customer Relationship Management (CRM) industry, offering scalable solutions tailored to businesses of all sizes. While global enterprises like Amazon, Accenture, Adidas, and American Express leverage its capabilities, Salesforce also caters to small businesses with Salesforce Essentials. Launched in 2017, this cloud-based CRM simplifies customer relationship management for small teams without the complexity and cost of enterprise-level solutions. What Is Salesforce Essentials? Salesforce Essentials is a streamlined CRM designed for small businesses with fewer than 10 users. It provides core features such as lead management, sales tracking, customer support, and business analytics. With an intuitive interface and cost-effective pricing, Essentials enables small businesses to leverage Salesforce’s powerful CRM tools without being overwhelmed by extensive configurations. With a cloud-first approach, Salesforce Essentials centralizes customer data on a single platform, enhancing efficiency, boosting productivity, and improving customer interactions. Who Should Use Salesforce Essentials? Salesforce Essentials is ideal for small businesses seeking a straightforward, affordable CRM to manage customer relationships, track sales, and provide support—without the complexities of traditional CRM systems. If your business currently relies on spreadsheets or disparate tools to manage customer data, Essentials offers a more organized and integrated solution. Designed for teams of up to 10 users, it is an excellent starting point for small businesses looking to scale their CRM capabilities as they grow. Key Features of Salesforce Essentials 1. Comprehensive CRM Capabilities Salesforce Essentials consolidates sales tracking, customer inquiries, and support into a single interface. This holistic approach ensures small businesses can manage customer data efficiently as they expand. 2. AI-Driven Automation Essentials includes Einstein Activity Capture, which automatically records emails, meetings, and calendar events. This eliminates manual data entry and allows teams to focus on strategic tasks. AI-driven insights further enhance customer relationship management and sales forecasting. 3. User-Friendly Interface The platform features an intuitive dashboard that provides real-time updates, task lists, and customizable views. The drag-and-drop interface simplifies navigation, reducing the learning curve for small business teams. 4. Personalized Setup Salesforce Essentials offers guided setup tailored to business needs, whether managing contacts, streamlining sales cycles, or improving customer support. 5. Third-Party Integrations While not all Salesforce AppExchange apps are compatible, Essentials supports key third-party integrations, enabling small businesses to sync data across multiple platforms seamlessly. Benefits of Salesforce Essentials for Small Businesses 1. Data Synchronization Salesforce Essentials allows businesses to import and sync data from spreadsheets, emails, and other sources. Einstein Activity Capture automates data collection, ensuring accurate and up-to-date records. 2. Affordability Priced at per user per month, Salesforce Essentials is a cost-effective CRM solution with essential features typically found in more expensive systems. 3. Scalability Though initially designed for small teams, Essentials facilitates a smooth transition to more advanced Salesforce solutions as business needs evolve. 4. Mobile Accessibility With a mobile app, Salesforce Essentials enables small businesses to manage customer relationships anytime, anywhere. 5. Training and Support Salesforce offers extensive learning resources through Trailhead, in-app tutorials, and an installation assistant, helping small businesses maximize their CRM investment. Pricing and Getting Started Salesforce Essentials starts at $25 per user per month, making it an accessible upgrade from spreadsheets or less sophisticated CRM tools. For businesses requiring advanced features, Salesforce provides higher-tier plans such as Sales Professional and Service Professional, both starting at $75 per user per month. To get started, businesses can explore a pre-built demo with dummy data before importing their own customer information. Integration with Google or Outlook ensures seamless email and calendar synchronization. With mobile access and a scalable framework, Salesforce Essentials is a strategic investment for small businesses aiming for growth. Conclusion Salesforce Essentials is a powerful yet affordable CRM tailored for small businesses. It offers an intuitive interface, automation tools, and seamless scalability to support growing teams. By adopting Salesforce Essentials, small businesses can enhance efficiency, strengthen customer relationships, and position themselves for long-term success. 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 9, 2025in Data, Enterprise, Google, Salesforce0 Comments

04Apr

The AI SDR Revolution

The AI SDR Revolution: How AI is Transforming Sales Development The Problem: Sales Teams Are Drowning in Leads Your marketing team is crushing it—inbound leads are pouring in. But your Sales Development Representatives (SDRs) are overwhelmed, spending over two-thirds of their time on non-selling tasks like data entry, follow-ups, and lead qualification. The result? Missed opportunities, slower response times, and fewer deals closed. Enter the AI SDR—a game-changing solution that automates top-of-funnel sales tasks, letting human reps focus on what they do best: closing deals. What is an AI SDR? An AI-powered Sales Development Representative (SDR) automates repetitive sales tasks like:✅ Lead qualification (identifying high-intent prospects)✅ Automated outreach (personalized emails, follow-ups)✅ Meeting scheduling (booking demos directly into reps’ calendars)✅ CRM updates (logging interactions automatically) Unlike human SDRs, AI SDRs work 24/7, ensuring no lead slips through the cracks. How AI SDRs Work Human SDRs juggle: AI SDRs handle the same tasks—but autonomously—using:🔹 Machine Learning (ML) to analyze lead intent🔹 Natural Language Processing (NLP) to engage in human-like conversations🔹 Automation to execute tasks end-to-end Example: Agentforce AI SDRs Powered by Salesforce’s Customer 360, Data Cloud, and Einstein AI, these AI agents: AI SDR vs. Human SDR: Who Wins? Capability AI SDR Human SDR Response Time Instant Hours/Days Availability 24/7 Business hours Personalization Data-driven Relationship-driven Scalability Thousands of leads at once Limited by bandwidth Emotional IQ Rule-based High empathy The Best Approach? AI + Human Collaboration Salesforce data shows reps using AI see higher win rates and more closed deals. 5 Key Benefits of AI SDRs AI SDRs in Action: Real-World Results Case Study: VTT Technical Research Centre (Finland) The Future of AI SDRs 🚀 Greater Autonomy – Handling prospecting & research🎯 Hyper-Personalization – Leveraging Data Cloud for tailored messaging📞 Multimodal Engagement – Voice, video, and chat interactions 84% of sales leaders believe AI will dominate lead gen in the next 2 years. How to Implement AI SDRs Successfully Final Verdict: AI SDRs Are a Sales Superpower AI won’t replace SDRs—it will make them unstoppable. By automating grunt work, AI SDRs help teams:✔ Respond faster✔ Qualify smarter✔ Close more deals The question isn’t if you should adopt AI SDRs—it’s how soon can you start? Ready to supercharge your sales team? Explore AI SDR solutions today. 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 4, 2025in Agentforce Platform, Artificial Intelligence, Data0 Comments

03Apr

Databricks Launches Lakeflow Connect to Simplify Enterprise Data Ingestion

San Francisco, [April 2, 2025] – Databricks has taken a major step toward streamlining enterprise data integration with the general availability of Lakeflow Connect, its new low-code/no-code connector system. The initial release features preconfigured integrations with Salesforce and Workday, with plans to expand support to additional SaaS platforms, databases, and file sources in the coming months. Simplifying the Data Ingestion Challenge Data ingestion—the process of moving data from source systems into analytics environments—has long been a complex, resource-intensive task for enterprises. Traditional approaches require stitching together multiple tools (such as Apache Kafka or CDC solutions) and maintaining custom pipelines, often leading to scalability issues and high operational overhead. Lakeflow Connect aims to eliminate these pain points by providing: “Customers need this data, but before Lakeflow Connect, they were forced to rely on third-party tools that often failed at scale—or build custom solutions,” said Michael Armbrust, Distinguished Software Engineer at Databricks. “Now, ingestion is point-and-click within Databricks.” Why Salesforce and Workday First? The choice of initial connectors reflects the growing demand for real-time, structured data to power AI and generative AI applications. According to Kevin Petrie, Analyst at BARC U.S., more than 90% of AI leaders are experimenting with structured data, and nearly two-thirds use real-time feeds for model training. “Salesforce and Workday provide exactly the type of data needed for real-time ML and GenAI,” Petrie noted. “Databricks is smart to simplify access in this way.” Competitive Differentiation While other vendors offer connector solutions (e.g., Qlik’s Connector Factory), Lakeflow Connect stands out through: “Serverless compute is quietly important,” said Donald Farmer, Principal at TreeHive Strategy. “It’s not just about scalability—rapid startup times are critical for reducing pipeline latency.” The Road Ahead Databricks has already outlined plans to expand Lakeflow Connect with connectors for: Though the company hasn’t committed to a timeline, Armbrust hinted at upcoming announcements at the Data + AI Summit in June. Broader Vision: Democratizing Data Engineering Beyond ingestion, Databricks is focused on unifying the data engineering lifecycle. “Historically, you needed deep Spark or Scala expertise to build production-grade pipelines,” Armbrust said. “Now, we’re enabling SQL users—or even UI-only users—to achieve the same results.” Looking further ahead, Petrie suggested Databricks could enhance cross-team collaboration for agentic AI development, integrating Lakeflow with Mosaic AI and MLflow to bridge data, model, and application lifecycles. The Bottom LineLakeflow Connect marks a strategic move by Databricks to reduce friction in data pipelines—addressing a key bottleneck for enterprises scaling AI initiatives. As the connector ecosystem grows, it could further solidify Databricks’ position as an end-to-end platform for data and AI. For more details, visit Databricks.com. Key Takeaways:✅ Now Available: Salesforce & Workday connectors✅ Serverless, governed, and scalable ingestion✅ Future integrations with Google Analytics, ServiceNow, and more✅ June previews expected at Data + AI Summit 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 3, 2025in Agentic AI, Data, Enterprise, Generative AI, Google, Google Analytics, Salesforce0 Comments

03Apr

5 Attributes of Agents

Salesforce predicts you will have deployed over 100 AI Agents by the end of the year. What are they? What do they do? Why do you need them? Let’s explore the 5 key attributes of AI Agents. What Is an AI Agent? An AI agent is an intelligent software system that uses artificial intelligence to autonomously pursue goals and complete tasks on behalf of users. Unlike traditional programs, AI agents exhibit reasoning, planning, memory, and decision-making abilities, allowing them to learn, adapt, and operate with minimal human intervention. These agents leverage generative AI and foundation models to process multimodal inputs—such as text, voice, video, and code—enabling them to:✔ Understand and analyze information✔ Make logical decisions✔ Learn from interactions✔ Collaborate with other agents✔ Automate complex workflows From customer service bots to autonomous research assistants, AI agents are transforming industries by handling tasks that once required human intelligence. Key Features of an AI Agent Modern AI agents go beyond simple automation—they possess advanced cognitive and interactive capabilities: Feature Description Reasoning Uses logic to analyze data, solve problems, and make decisions. Acting Executes tasks—whether digital (sending messages, updating databases) or physical (controlling robots). Observing Gathers real-time data via sensors, NLP, or computer vision to understand its environment. Planning Strategizes steps to achieve goals, anticipating obstacles and optimizing actions. Collaborating Works with humans or other AI agents to accomplish shared objectives. Self-Refining Continuously improves through machine learning and feedback. AI Agents vs. AI Assistants vs. Bots While all three automate tasks, they differ in autonomy, complexity, and learning ability: Aspect AI Agent AI Assistant Bot Purpose Autonomously performs complex tasks. Assists users with guided interactions. Follows pre-set rules for simple tasks. Autonomy High—makes independent decisions. Medium—requires user input. Low—limited to scripted responses. Learning Adapts and improves over time. May learn from interactions. Minimal or no learning. Interaction Proactive and goal-driven. Reactive (responds to user requests). Trigger-based (e.g., chatbots). Example: How Do AI Agents Work? AI agents operate through a structured framework: Types of AI Agents AI agents can be classified based on interaction style and collaboration level: 1. By Interaction 2. By Number of Agents Benefits of AI Agents ✅ 24/7 Automation – Handles repetitive tasks without fatigue.✅ Enhanced Decision-Making – Analyzes vast data for insights.✅ Scalability – Manages workflows across industries.✅ Continuous Learning – Improves performance over time. The Future of AI Agents As AI advances, agents will become more autonomous, intuitive, and integrated into daily workflows—from healthcare diagnostics to smart city management. Want to see AI agents in action? Explore 300+ real-world AI use cases from leading organizations. 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 3, 2025in Artificial Intelligence, Data, Generative AI, Salesforce0 Comments

24Mar

Agents are the Future of Customer Engagement

Agentic Customer Engagement is Here There was a time when customer service meant going into a brick and mortar building and talking to a person face to face. It was time consuming and did not guarantee a solution. The mail order business brought on the need for the 800 number to contact a merchant. The dot com boom brought customer engagement opportunities directly to our homes. Ios and Android apps brought customer engagement to our fingertips. Yet we still were dependent upon the availability of humans or at least chatbots. Customer service often repressed customer engagement, not enhanced it. Agents, like Salesforce Agentforce, brought 24 7 customer engagement to us no matter where we are, when it is, or how complicated our issue is. And agents improved customer service! What’s next? Robots and drones who deliver our items and answer our questions? Who knows. AI bots are transforming client relationships and customer service. To achieve unparalleled efficiency, these intelligent systems plan and automate difficult activities, make deft decisions, and blend in seamlessly with current workflows. Yes, it’s widely believed that AI agents will play a crucial role in the future of customer engagement, offering personalized, efficient, and consistent experiences across various channels. Here’s why AI agents are poised to be a key driver in customer engagement: AI agents are becoming smarter every day, using machine learning and natural language processing to predict customer needs, handle complex queries with empathy and offer real-time, personalized assistance. How AI Agents Are Redefining Customer Engagement Marketing is undergoing a seismic transformation. Tectonic shift, if you will. The past decade was dominated by complex tech stacks and data integration—now, AI is shifting the focus back to what truly matters: crafting impactful content and campaigns. Welcome to the era of agentic customer engagement and marketing. The Rise of Marketing Agents Unlike traditional customer service agents handling one-to-one interactions, marketing agents amplify human expertise to engage audiences at scale—whether targeting broad segments or hyper-personalized personas. They ensure consistent, high-quality messaging across every channel while automating the intricate backend work of delivering the right content to the right customer at the right time. This shift is powered by rapid AI advancements: How Agentic Engagement Amplifies Marketing Marketing agents don’t replace human creativity—they extend it. Once strategists set guidelines, approve messaging, and define brand voice, agents execute with precision across channels. At Typeface, for example, AI securely learns brand tones and styles to generate on-brand imagery, text, and videos—ensuring every asset aligns with the company’s identity. Key Capabilities of Marketing Agents The Human-Agent Partnership AI agents don’t replace marketers—they empower them. Humans bring creativity, emotional intelligence, and strategic decision-making; agents handle execution, data processing, and scalability. Marketers will evolve into “agent wranglers”, setting objectives, monitoring performance, and ensuring alignment with business goals. Meanwhile, agents will work in interconnected ecosystems—where a content agent’s blog post triggers a social agent’s promotion, while a performance agent optimizes distribution, and a brand agent tracks reception. Preparing for the Agent Era To stay ahead, businesses should:✅ Start small, think big – Pilot agents in low-risk areas before scaling.✅ Train teams – Ensure marketers understand agent management.✅ Build governance frameworks – Define oversight and intervention protocols.✅ Strengthen data infrastructure – Clean, structured data fuels agent effectiveness.✅ Maintain human oversight – Regularly audit agent outputs for quality and alignment. Work with a Salesforce partner like Tectonic to prepare for the Agent Era. The Future is Agentic The age of AI-driven marketing isn’t coming—it’s here. Companies that embrace agentic engagement will unlock unprecedented efficiency, personalization, and impact. The question isn’t if you’ll adopt AI agents—it’s how soon. Ready to accelerate your strategy? Discover how Agentforce (Salesforce’s agentic layer) can cut deployment time by 16x while boosting accuracy by 70%. The future of marketing isn’t just automated—it’s autonomous, adaptive, and agentic. Are you prepared? The Future of Customer Experience: AI-Driven Efficiency and Innovation Businesses have long understood the connection between operational efficiency and superior customer experience (CX). However, the rapid advancement of AI-powered technologies, including next-generation hardware and virtual agents, is transforming this connection into a measurable driver of value creation. Increasingly well-documented use cases for generative AI (GenAI) demonstrate that companies can simultaneously deliver a vastly superior customer experience at a significantly lower cost-to-serve, resulting in substantial financial gains. From Customer Journeys to Autonomous Customer Missions To achieve this ideal balance, companies are shifting from traditional customer journeys—where users actively manage their own experiences via apps—to a more comprehensive approach driven by trusted autonomous agents. These agents are designed to complete specific tasks with minimal human involvement, creating an entirely new paradigm for customer engagement. While early implementations may be rudimentary, the convergence of hardware and AI will lead to sophisticated, seamless experiences far beyond current capabilities. AI-Enabled Internal and External Transformation AI is already driving transformation both internally and externally. Internally, it streamlines processes, enhances employee experiences, and significantly boosts productivity. In customer service operations, for example, GenAI has driven productivity improvements of 15% to 30%, with some companies targeting up to 80% efficiency gains. Externally, AI is reshaping customer interactions, making them more personalized, efficient, and intuitive. Virtual co-pilots assist customers by answering inquiries, processing returns, and curating tailored offers—freeing human employees to focus on complex issues that require nuanced decision-making. Linking Operational Efficiency to Customer Experience Leading organizations are demonstrating how AI-driven efficiencies translate into enhanced CX. Despite these gains, companies must raise the bar even further to fully capitalize on AI’s potential. The convergence of next-generation hardware with AI-driven automation presents an unprecedented opportunity to redefine customer engagement. From App-Driven Experiences to Autonomous Agents At Dreamforce 2024, Salesforce CEO Marc Benioff highlighted that service employees waste over 40% of their time on repetitive, low-value tasks. Similarly, customers face friction in making significant purchases or planning events. Google research indicates that travelers may engage in over 700 digital touchpoints when planning a trip—a fragmented and often frustrating experience. Imagine instead a network of proprietary and third-party agents seamlessly executing customer missions—such as purchasing a car or planning a vacation—without requiring constant user input. These AI agents

March 24, 2025in Agentforce Platform, Agentic AI, Data, Generative AI, Google, Salesforce0 Comments

21Mar

Salesforce Development Services

Salesforce has become one of the leading platforms to change the business-to-customer relationships and experience. Salesforce development services don’t just offer Salesforce solutions and software implementation; they help you adopt a customized functionality that enriches delivery and profit. Salesforce, by definition, is a powerful platform that enables a business to adopt CRM-driven leads and expansion in the industry. At Tectonic, we believe that a decision to opt for Salesforce services is just the beginning of a battle to beat the competition. This is where Tectonic comes in with custom coding and the finest Salesforce development services; we help you figure out everything from configurations and complications to legacy data systems and more. We are made up of a team of Salesforce experts, development professionals, and years of experience in strategic consulting, planning, integration, implementation, deployment, and delivery of business-changing and success-driven services. Why choose Tectonic’s Salesforce Development services? Tectonic, with its years of expertise and experience in technical services and strategic consulting, has the most efficient and organized set of professionals to help your business understand and embed everything-Salesforce. Tectonic understands innovation and change can be overwhelming and sound too complex, and it is our business to handle that for you while delivering a profitable and growing system that expands your reach in the industry. And remains scalable over time. The industry has moved from traditional on-premises CRM to cloud-based CRM to address scalability, change management, and time-to-market needs of businesses. For companies looking for SaaS offerings on the cloud, Salesforce is an undisputed leader. Also, companies looking to build customized business applications can capitalize on Force.com as a platform as a service (PaaS). Implement innovative Salesforce solutions that streamline your operations, boost your productivity, and drive sustainable growth. Work with our team of certified Salesforce developers who bring extensive experience and in-depth knowledge to every project. At Tectonic we focus on industries where we have expertise to help you get the most impactful Salesforce development. Get customized Salesforce development services from Tectonic designed to meet your unique business needs, ensuring seamless integration and enhanced functionality. Build and deploy scalable Salesforce platforms that adapt as your business grows and evolves, keeping you ahead of the competition. Collaborate with Tectonic to unlock the full potential of Salesforce, where development is turning challenges into opportunities for success. 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

March 21, 2025in Data, Salesforce, Salesforce Development Services0 Comments

21Mar

Agentforce is 16x Faster and 75% More Accurate Than DIY

You are 2x more likely to launch your agents when working with a Salesforce partner, like Tectonic. Agentic AI is creating a digitial labor revolution. Human-only Workforce: Humans with Agents Your digital workforce requires more than a large language model. Data Apps Agents When you can bring all these tools together in a big, trusted, unified, and open platform you achieve: Adoption is the key to growth, and your Salesforce partner creates the unique unlock. Tectonic will set up a foundation for seamless integration of agents within your existing Salesforce ecosystem. We will professionally assess your agentic maturity and create a value proposition to keep you on track. Tectonic will help you innovate, protect, and grow. The steady state of priorities is innovate, protect, and optimize; as defined above. The crossroads you are at involve the new paradigm of AI Priorities. Where are you on the scale of Agentic Maturity: Reach out to Tectonic to determin your Agent Maturity and step up your game with AI Agents today. 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 21, 2025in Agentic AI, Data, Enterprise, Salesforce0 Comments

19Mar

Data Lake vs. Data Warehouse: Understanding the Differences and Use Cases

Organizations today manage vast amounts of data, and how they store and process that data plays a critical role in business intelligence. Data lakes and data warehouses represent two distinct approaches to large-scale data storage, each with unique strengths. While they are often compared, they are not mutually exclusive—when used strategically, they complement each other to provide powerful insights. This guide explores the key differences between data lakes and data warehouses, their advantages, and when to use each. What is a Data Lake? A data lake is a centralized repository that stores vast amounts of raw data in its native format until needed. Unlike structured databases, data lakes use a flat architecture, meaning the data remains unprocessed and unstructured, retaining its original form. Key Features of Data Lakes: Challenges of Data Lakes: What is a Data Warehouse? A data warehouse is a structured repository optimized for analysis and business intelligence (BI). Unlike data lakes, which store raw data, data warehouses transform, clean, and organize data into a structured format for easy querying and reporting. Key Features of Data Warehouses: Challenges of Data Warehouses: Data Lake vs. Data Warehouse: Key Differences Feature Data Lake Data Warehouse Data Type Structured, semi-structured, and unstructured Primarily structured data Storage Format Raw, native format Processed and organized Use Case Big data, AI/ML analytics, real-time insights Business intelligence, reporting, transactions Cost Lower (scalable, less processing needed) Higher (due to transformation and storage costs) Flexibility High—schema-on-read Low—schema-on-write Ease of Use Requires data engineers and scientists Business analysts can use directly Security Less secure, requires governance More secure, with access control Choosing Between a Data Lake and Data Warehouse The best choice depends on the business objectives and data needs: Many organizations use both—storing raw data in a lake and processing refined data in a warehouse. For example, a company might: By integrating both storage solutions, businesses can maximize efficiency, reduce costs, and enable better decision-making. Conclusion Rather than viewing data lakes and data warehouses as competing technologies, organizations should recognize their complementary roles. While data warehouses provide structured, high-performance analytics, data lakes offer the flexibility needed for big data storage and ai-driven insights. The key to success is balancing both solutions to meet current and future data needs—ensuring agility, cost efficiency, and scalability in a rapidly evolving digital world. 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

March 19, 2025in Salesforce0 Comments

17Mar

Salesforce Energy and Utilities Cloud Explained

Salesforce Energy and Utilities Cloud is a specialized industry solution built on the Salesforce platform, designed to meet the unique needs of energy and utility companies. It helps these organizations manage customer relationships, streamline operations, and drive digital transformation in an increasingly complex and regulated industry. The cloud solution provides tools for customer engagement, field service management, and regulatory compliance, among other functionalities. Key Features of Salesforce Energy and Utilities Cloud: Benefits of Salesforce Energy and Utilities Cloud: Use Cases: Implementation Considerations: In summary, Salesforce Energy and Utilities Cloud is a comprehensive solution designed to help energy and utility companies enhance customer engagement, streamline operations, and achieve regulatory compliance. By leveraging advanced technologies and industry-specific functionalities, utilities can drive digital transformation and improve overall performance. 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

March 17, 2025in Data, Salesforce, Salesforce Einstein0 Comments

17Mar

Salesforce Unveils Agentforce 2dx

Salesforce Unveils Agentforce 2dx: A Major Leap in AI Agent Capabilities Proactive, Autonomous AI Agents to Bridge the Skills Gap Salesforce has announced a major upgrade to its AI agent platform with Agentforce 2dx, a next-generation solution designed to move beyond reactive, chat-based interactions. With enhanced efficiency, agility, and scalability, Agentforce 2dx enables AI agents to operate autonomously, integrating seamlessly with existing data systems, business logic, and user interfaces. The Future of Work: AI Agents Filling the Labor Gap “Companies today have more work than workers, and Agentforce is stepping in to fill the gap,” said Adam Evans, EVP and GM of Salesforce’s AI Platform. Unlike traditional AI chatbots that rely on rigid programming or manual prompts, agentic AI dynamically adapts to live data and evolving business needs, making it far more effective in real-world applications. Introducing AgentExchange: A Marketplace for AI Agent Templates Alongside Agentforce 2dx, Salesforce is launching AgentExchange, an online marketplace where businesses can access and share pre-built AI agent templates and actions. From launch, AgentExchange will feature: The AI Agent Race Heats Up Salesforce’s announcement comes amid intensified industry focus on AI agents. Microsoft and AWS have recently made significant moves, with Microsoft research revealing that 72% of business leaders expect AI agents to be fully integrated into their operations soon—21% within the next year and 39% within two years. Meanwhile, AWS is reportedly forming a dedicated AI agent division, led by Swami Sivasubramanian, VP of AI and Data, reporting directly to CEO Matt Garman. Salesforce CEO Marc Benioff has been vocal about the future of AI agents, predicting that tomorrow’s CEOs will need to manage both human employees and AI-powered agents. With Agentforce 2dx and AgentExchange, Salesforce is positioning itself at the forefront of this transformation, empowering businesses to automate, scale, and innovate 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

March 17, 2025in AgentExchange, Agentic AI, Data, Salesforce0 Comments

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