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Shift From AI Agents to AI Agent Tool Use
20Mar

Building Scalable AI Agents

Building Scalable AI Agents: Infrastructure, Planning, and Security The key building blocks of AI agents—planning, tool integration, and memory—demand sophisticated infrastructure to function effectively in production environments. As the technology advances, several critical components have emerged as essential for successful deployments. Development Frameworks & Architecture The ecosystem for AI agent development has matured, with several key frameworks leading the way: While these frameworks offer unique features, successful agents typically share three core architectural components: Despite these strong foundations, production deployments often require customization to address high-scale workloads, security requirements, and system integrations. Planning & Execution Handling complex tasks requires advanced planning and execution flows, typically structured around: An agent’s effectiveness hinges on its ability to: ✅ Generate structured plans by intelligently combining tools and knowledge (e.g., correctly sequencing API calls for a customer refund request).✅ Validate each task step to prevent errors from compounding.✅ Optimize computational costs in long-running operations.✅ Recover from failures through dynamic replanning.✅ Apply multiple validation strategies, from structural verification to runtime testing.✅ Collaborate with other agents when consensus-based decisions improve accuracy. While multi-agent consensus models improve accuracy, they are computationally expensive. Even OpenAI finds that running parallel model instances for consensus-based responses remains cost-prohibitive, with ChatGPT Pro priced at $200/month. Running majority-vote systems for complex tasks can triple or quintuple costs, making single-agent architectures with robust planning and validation more viable for production use. Memory & Retrieval AI agents require advanced memory management to maintain context and learn from experience. Memory systems typically include: 1. Context Window 2. Working Memory (State Maintained During a Task) Key context management techniques: 3. Long-Term Memory & Knowledge Management AI agents rely on structured storage systems for persistent knowledge: Advanced Memory Capabilities Standardization efforts like Anthropic’s Model Context Protocol (MCP) are emerging to streamline memory integration, but challenges remain in balancing computational efficiency, consistency, and real-time retrieval. Security & Execution As AI agents gain autonomy, security and auditability become critical. Production deployments require multiple layers of protection: 1. Tool Access Control 2. Execution Validation 3. Secure Execution Environments 4. API Governance & Access Control 5. Monitoring & Observability 6. Audit Trails These security measures must balance flexibility, reliability, and operational control to ensure trustworthy AI-driven automation. Conclusion Building production-ready AI agents requires a carefully designed infrastructure that balances:✅ Advanced memory systems for context retention.✅ Sophisticated planning capabilities to break down tasks.✅ Secure execution environments with strong access controls. While AI agents offer immense potential, their adoption remains experimental across industries. Organizations must strategically evaluate where AI agents justify their complexity, ensuring that they provide clear, measurable benefits over traditional AI models. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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March 20, 2025in Data, Technology0 Comments
11Mar

Salesforce Introduces AgentExchange

Salesforce Introduces AgentExchange: Empowering Businesses with AI-Driven Digital Labor Salesforce has unveiled AgentExchange, a marketplace embedded directly within the Salesforce platform, designed to simplify the way businesses, developers, and partners build, discover, and monetize AI-driven digital labor. This launch extends Salesforce’s Agentforce ecosystem, reinforcing the company’s commitment to accelerating enterprise adoption of advanced, role-based AI agents. Shifting to Role-Based AI AgentExchange arrives as industries shift from task-based automation to standardized, role-based AI agents. These intelligent agents leverage structured metadata to autonomously perform specific business roles, enhancing operational efficiency and scalability. Salesforce joins key industry players like Workday, SAP, and ServiceNow in shaping this emerging landscape. “Agentic AI is transforming the way businesses operate. Traditional software is rigid — it’s clicks, code, and logic. With AI agents, solutions can now observe, reason, and act autonomously, driving digital labor that expands organizational capabilities.” Adam Evans, EVP and GM of Salesforce AI Marketplace Capabilities and Partner Ecosystem AgentExchange launches with over 200 trusted partners, including Google Cloud, DocuSign, Box, and Workday, offering a variety of secure and compliant pre-built components such as: Real-World Use Cases AgentExchange supports solutions across various industries: Metadata-Driven Integration A core feature of AgentExchange is its metadata standardization, which defines agent capabilities, interfaces, and compliance requirements. This metadata-centric approach simplifies integration, reduces deployment complexity, and empowers organizations to adopt AI agents with confidence. Competitive Edge and CRM-Centric Focus Salesforce distinguishes AgentExchange with its strong focus on CRM-related, customer-facing solutions. While competitors like Workday emphasize HR automation and SAP covers broader ERP functions, Salesforce leverages real-time customer data and Slack integration to enhance front-office interactions. This CRM-centric focus equips businesses with tools to improve customer experience management, further differentiating Salesforce in the AI-driven digital labor space. Enabling an Open AI Ecosystem AgentExchange signals Salesforce’s commitment to fostering an open AI ecosystem, empowering partners, developers, and the Agentblazer community to build and monetize AI-driven solutions. The marketplace includes hundreds of vetted solutions designed to accelerate the adoption of intelligent digital labor across industries. Mark Stewart, CEO and President of Goodyear, shared his excitement about the platform: “AgentExchange offers ready-to-use solutions that enhance our speed, efficiency, and customer experience. This innovation aligns perfectly with Goodyear’s focus on delivering value to our customers.” Partner Innovations Key partners are already contributing to AgentExchange with impactful solutions: Driving the Future of Digital Labor Brian Landsman, EVP & GM of Global Business Development & Partnerships at Salesforce, connected AgentExchange to Salesforce’s AppExchange legacy: “When we launched AppExchange in 2005, we unlocked new value for our platform. AgentExchange now builds on that success, inviting partners, startups, and developers to shape the future of digital labor.” AgentExchange empowers organizations to seamlessly adopt trusted AI solutions, enabling developers to leverage partner expertise and integrate industry-specific capabilities directly within Salesforce. This innovative marketplace positions Salesforce as a leader in AI-driven digital transformation, driving efficiency, innovation, and growth in the evolving digital labor economy. Let Tectonic guide you though this exciting new release aimed to get you up and running even faster with Agentforce! Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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March 11, 2025in AgentExchange, Agentic AI, Data, Enterprise, Google, Salesforce0 Comments
Salesforce Flow Approval Orchestration
09Mar

Salesforce Flow Approval Orchestration

Salesforce Flow Approval Orchestration: A Winner for Approval Processes Approval Processes have long been a key feature in Salesforce, enabling professionals to implement structured, multi-step approvals for records. With the shift towards Salesforce Flow as the primary declarative automation tool, it was only a matter of time before approval functionality became natively integrated. Enter Flow Approval Orchestration—a new way to build and manage approvals entirely within Flow Builder at no additional cost. Introducing Flow Approval Orchestration Spring ’25 introduces Approval Orchestration Flow Types, expanding Flow’s capabilities beyond merely invoking an existing Approval Process. These new flows offer a robust solution for both simple and complex approval workflows, accommodating both internal and external users and systems. Approval Orchestration flows come in two types: Stages and Steps: The Core of Approval Orchestration Approval Orchestration relies on Stages and Steps to structure approvals. Stages contain multiple Steps that can execute sequentially or in parallel based on specified criteria. Within each Stage, two types of Steps are available: By default, a Stage is completed once all its Steps are finished, but this can be customized with additional conditions or an Evaluation Flow for more complex logic. Building an Approval Process in Flow Builder Approval Orchestration offers flexibility for various business scenarios. Let’s consider an example where an Opportunity requires approval upon creation, but only if the related Account is classified as a Customer Account. Steps to Implement: For opportunities over 500K, a secondary approver is required. The Decision Element in Flow allows navigation between different Stages, ensuring complex approval hierarchies are handled efficiently. Enhancing User Experience & Management To streamline approval management: Key Considerations Before transitioning to Flow Approval Orchestration, keep these in mind: Final Thoughts Bringing all approval-related automation into Flow Builder is a significant leap forward for Salesforce admins. Flow Approval Orchestration not only simplifies complex approval logic but also enhances visibility and control over approvals. Try it in a sandbox environment to explore its potential and tailor it to your specific business needs. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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March 9, 2025in Salesforce, Salesforce Flow0 Comments
spring 25
06Mar

Spring 25 Revealed

Spring ’25 Salesforce Release: What’s New and How to Prepare As winter lingers, the Salesforce Ohana is already embracing the promise of spring—a season of renewal, growth, and transformation. The Salesforce Spring ’25 Release brings fresh innovations designed to enhance productivity, streamline integrations, and optimize your CRM experience. With powerful AI enhancements, security updates, and UI improvements, this release is set to elevate the way you work. Let’s explore the key updates and how you can prepare to make the most of these enhancements. 1. Changes to Einstein Activity Capture Permissions What’s New?Salesforce is refining access to Einstein Activity Capture (EAC), ensuring more controlled and secure usage. Sales Engagement Basic Users will no longer have default access to EAC and must be assigned the Standard Einstein Activity Capture permission set to continue using the feature. Why It Matters:This update enhances security by limiting access to users with the appropriate permissions, improving governance over activity data. How to Prepare: 2. Transition to ICU Locale Formats What’s New?Salesforce is shifting from Oracle’s JDK Locale formats to ICU Locale Formats for handling date, currency, and numeric data. Why It Matters:ICU formats provide better internationalization and localization, improving accuracy and consistency across different regions. How to Prepare: 3. Introduction of LWC Stacked Modals What’s New?Lightning Web Components (LWC) now support stacked modals, allowing multiple modal windows to remain open simultaneously. Why It Matters:This improves the user experience by enabling seamless navigation between modal windows without losing context. How to Prepare: 4. Secure Redirection for Flows What’s New?Salesforce now requires that retURL parameters used in Flow redirections be explicitly added to the trusted URLs list. Why It Matters:This security enhancement mitigates risks associated with unauthorized redirections, protecting user data. How to Prepare: 5. Rollbacks for Apex Action Exceptions in REST API What’s New?Salesforce now enforces automatic rollbacks for exceptions occurring during Apex actions invoked via REST API. Why It Matters:This update ensures data integrity by preventing incomplete or failed operations from saving partial updates. How to Prepare: Final Thoughts The Spring ’25 release brings vital enhancements to permissions, security, UI, and API reliability. By proactively testing and preparing, you can ensure a seamless transition while unlocking the full potential of these updates. Stay ahead of the curve and leverage these improvements to create a more efficient, secure, and innovative Salesforce environment. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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March 6, 2025in Data0 Comments
AI Data Cloud and Integration
03Mar

It is Time to Implement Data Cloud

With Salesforce Data Cloud you can: With incomplete data your 360-degree customer view is limited and often leads to multiple sales reps working on the same lead. Slow access to the right leads at the right time leads to missed opportunties and delayed closings. If your team cannot trust the data due to siloes and inaccuracies, they avoid using it. It is Time to Implement Data Cloud. Unified Connect and harmonize data from all your Salesforce applications and external data systems. Then activate your data with insights and automation across every customer touchpoint. Powerful With Data Cloud and Agentforce, you can create the most intelligent agents possible, giving them access to the exact data they need to deliver any employee or customer experience. Secure Securely connect your data to any large language model (LLM) without sacrificing data governance and security thanks to the Einstein 1 trust layer. Open Data Cloud is fully open and extensible – bring your own data lake or model to reduce complexity and leverage what’s already been built. Plus, share out to popular destinations like Snowflake, Google Ads, or Meta Ads. Salesforce Data Cloud is the only hyperscale data engine native to Salesforce. It is more than a CDP. It goes beyond a data lake. You can do more with Data Cloud. Your Agentforce journey begins with Data Cloud. Agents need the right data to work. With Data Cloud, you can create the most intelligent agents possible, giving them access to the exact data they need to deliver any employee or customer experience. Use any data in your organization with Agentforce in a safe and secure manner thanks to the Einstein 1 Trust Layer. Datablazers are Salesforce community members who are passionate about driving business growth with data and AI powered by Data Cloud. Sign up to join a growing group of members to learn, connect, and grow with Data Cloud. Join today. The path to AI success begins and ends with quality data. Business, IT, and analytics decision makers with high data maturity were 2x more likely than low-maturity leaders to have the quality data needed to use AI effectively, according to our State of Data and Analytics report. “What’s data maturity?” you might wonder. Hang tight, we’ll explain in chapter 1 of this guide. Data-leading companies also experience: Your data strategy isn’t just important, it’s critical in getting you to the head of the market with new AI technology by your side. That’s why this Salesforce guide is based on recent industry findings and provides best practices to help your company get the most from your data. Tectonic will be sharing a focus on the 360 degree customer view with Salesforce Data Cloud in our insights. Stay tuned. It is Time to Implement Data Cloud Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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March 3, 2025in Data, Einstein 1 Platform, Einstein Insights, Google, Salesforce, Salesforce Data Cloud, Salesforce Implementation Services, Snowflake, Technology0 Comments
Granular Locking in Salesforce
26Feb

Granular Locking in Salesforce

Granular Locking in Salesforce: Enhancing Performance & Reducing Contention Granular locking in Salesforce is a powerful feature designed to minimize record lock contention, particularly in high-data-volume environments or those with complex automation processes. By refining traditional locking constraints, this mechanism allows Salesforce to manage simultaneous updates more efficiently, improving system performance and reducing errors. What is Granular Locking? Granular locking is an advanced record-locking mechanism that applies locks at a more detailed level, preventing unnecessary locking of parent or related records. This is especially useful in scenarios where multiple records are updated concurrently, reducing row lock contention in parent-child relationships. Key Features: ✅ Fine-Grained Locks – Prevents excessive locking of parent or related records.✅ Enhanced Concurrency – Allows multiple simultaneous updates to child records without conflicts.✅ Improved Performance – Minimizes errors like “Unable to lock row” by reducing contention. Why is Granular Locking Important? 1️⃣ Concurrent Record Updates 2️⃣ Optimized Automation 3️⃣ Scaling High-Volume Transactions How Granular Locking Works Granular locking ensures that:🔹 Parent records remain unlocked when child records are updated.🔹 Locks apply only to the specific records being modified instead of affecting entire datasets. Example: 🚫 Without Granular Locking: Updating an Opportunity record locks the parent Account and all related child records.✅ With Granular Locking: Only the specific Opportunity record is locked, allowing the Account and other child records to remain accessible. When Does Granular Locking Apply? 🔹 Master-Detail Relationships – Prevents parent records from being unnecessarily locked during child record updates.🔹 Campaign Hierarchies – Ensures that updates to child campaigns don’t lock parent campaigns.🔹 Sharing Recalculations – Reduces locking issues when Salesforce recalculates sharing rules for parent-child data relationships. Benefits of Granular Locking 🚀 Reduced Lock Contention – Minimizes conflicts in multi-user environments.📉 Fewer Errors – Decreases “Unable to obtain exclusive access to this record” errors.⚡ Faster Automation – Improves workflow and trigger execution speed.📊 Better Scalability – Enhances performance in high-transaction environments. Best Practices for Using Granular Locking ✅ Optimize Relationship Design: Avoid complex parent-child structures that could lead to unnecessary locking.✅ Minimize Simultaneous Updates: Reduce concurrent updates on the same parent record.✅ Use Asynchronous Processing: Implement Batch Apex or Queueable Apex for large data operations.✅ Test in High-Volume Scenarios: Simulate real-world data loads in a sandbox environment.✅ Monitor Locking Issues: Use debug logs and Event Monitoring to track and resolve locking conflicts. Common Issues & Solutions ❌ Error: “Unable to Lock Row”🔹 Cause: Simultaneous updates to related records.🔹 Solution: Redesign workflows or use asynchronous processing to reduce contention. ❌ Slow Performance in Campaign Updates🔹 Cause: Hierarchical campaign relationships triggering excessive locks.🔹 Solution: Ensure campaigns are structured to take advantage of granular locking. ❌ Automation Conflicts🔹 Cause: Multiple automation tools acting on the same records.🔹 Solution: Consolidate triggers and workflows to minimize overlaps. How to Enable Granular Locking for Campaign Hierarchies Although granular locking is enabled by default for most Salesforce operations, certain features (like hierarchical campaign locking) require manual activation. 🔹 Steps to Enable Granular Locking in Campaign Hierarchies:1️⃣ Navigate to Setup.2️⃣ Go to Campaign Settings.3️⃣ Check the box for Enable Improved Campaign Management (Granular Locking).4️⃣ Save your changes. Conclusion Granular locking is a vital feature in Salesforce that optimizes record management by reducing contention, minimizing errors, and improving system performance in high-transaction environments. By implementing best practices and leveraging fine-grained locks, organizations can scale efficiently while ensuring smooth automation and record updates. For teams handling complex data relationships, granular locking provides the flexibility, scalability, and reliability needed to maintain a high-performing Salesforce environment. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 26, 2025in Data, Salesforce0 Comments

Data Cloud Billable Usage

Data Cloud Billable Usage Overview Usage of certain Data Cloud features impacts credit consumption. To track usage, access your Digital Wallet within your Salesforce org. For specific billing details, refer to your contract or contact your Account Executive. Important Notes ⚠️ Customer Data Platform (CDP) Licensing – If your Data Cloud org operates under a CDP license, refer to Customer Data Platform Billable Usage Calculations instead.⚠️ Sandbox Usage – Data Cloud sandbox consumption affects credits, with usage tracked separately on Data Cloud sandbox cards. Understanding Usage Calculations Credit consumption is based on the number of units used multiplied by the multiplier on the rate card for that usage type. Consumption is categorized as follows: 1. Data Service Usage Service usage is measured by records processed, queried, or analyzed. Billing Category Description Batch Data Pipeline Based on the volume of batch data processed via Data Cloud data streams. Batch Data Transforms Measured by the higher of rows read vs. rows written. Incremental transforms only count changed rows after the first run. Batch Profile Unification Based on source profiles processed by an identity resolution ruleset. After the first run, only new/modified profiles are counted. Batch Calculated Insights Based on the number of records in underlying objects used to generate Calculated Insights. Data Queries Based on records processed, which depends on query structure and total records in the queried objects. Unstructured Data Processed Measured by the amount of unstructured data (PDFs, audio/video files) processed. Streaming Data Pipeline Based on records ingested through real-time data streams (web, mobile, streaming ingestion API). Streaming Data Transforms Measured by the number of records processed in real-time transformations. Streaming Calculated Insights Usage is based on the number of records processed in streaming insights calculations. Streaming Actions (including lookups) Measured by the number of records processed in data lookups and enrichments. Inferences Based on predictive AI model usage, including one prediction, prescriptions, and top predictors. Applies to internal (Einstein AI) and external (BYOM) models. Data Share Rows Shared (Data Out) Based on the new/changed records processed for data sharing. Data Federation or Sharing Rows Accessed Based on records returned from external data sources. Only cross-region/cross-cloud queries consume credits. Sub-second Real-Time Events & API Based on profile events, engagement events, and API calls in real-time processing. Private Connect Data Processed Measured by GB of data transferred via private network routes. 🔹 Retired Billing Categories: Accelerated Data Queries and Real-Time Profile API (no longer billed after August 16, 2024). 2. Data Storage Allocation Storage usage applies to Data Cloud, Data Cloud for Marketing, and Data Cloud for Tableau. Billing Category Description Storage Beyond Allocation Measured by data storage exceeding your allocated limit. 3. Data Spaces Billing Category Description Data Spaces Usage is based on the number of data spaces beyond the default allocation. 4. Segmentation & Activation Usage applies to Data Cloud for Marketing customers and is based on records processed, queried, or activated. Billing Category Description Segmentation Based on the number of records processed for segmentation. Batch Activations Measured by records processed for batch activations. Activate DMO – Streaming Based on new/updated records in the Data Model Object (DMO) during an activation. If a data graph is used, the count is doubled. 5. Ad Audiences Service Usage Usage is calculated based on the number of ad audience targets created. Billing Category Description Ad Audiences Measured by the number of ad audience targets generated. 6. Data Cloud Real-Time Profile Real-time service usage is based on the number of records associated with real-time data graphs. Billing Category Description Sub-second Real-Time Profiles & Entities Based on the unique real-time data graph records appearing in the cache during the billing month. Each unique record is counted only once, even if it appears multiple times. 📌 Example: If a real-time data graph contains 10M cached records on day one, and 1M new records are added daily for 30 days, the total count would be 40M records. 7. Customer Data Platform (CDP) Billing Previously named Customer Data Platform orgs are billed based on contracted entitlements. Understanding these calculations can help optimize data management and cost efficiency. Track & Manage Your Usage 🔹 Digital Wallet – Monitor Data Cloud consumption across all categories.🔹 Feature & Usage Documentation – Review guidelines before activating features to optimize cost.🔹 Account Executive Consultation – Contact your AE to understand credit consumption and scalability options. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 26, 2025in Data, Salesforce, Salesforce Data Cloud0 Comments
Salesforce Unified Knowledge
26Feb

AI Through a Unified Platform

Maximizing AI Potential Through a Unified Platform In today’s interconnected business landscape, siloed teams are a thing of the past—especially for organizations aiming to harness the full power of AI. With businesses leveraging an average of 991 applications across various platforms, disconnected systems are all too common, resulting in suboptimal experiences for both employees and customers. A unified platform eliminates these barriers, enabling teams to collaborate effortlessly across departments. By centralizing data on one platform, organizations unlock AI’s true potential, delivering more meaningful and actionable results. But what does a unified platform approach look like? And how does it enable AI agents to transform business processes? Let’s dive in. How AI Agents Perform Better on Unified Platforms Traditional rule-based systems often bombard teams with irrelevant updates triggered by static field values, causing critical information to be overlooked. By contrast, AI agents, guided by human-defined frameworks, operate based on context rather than rigid rules, making them more effective at managing complex workflows. However, for AI agents to succeed, they require seamless access to data and systems. Without a unified platform, they can’t function cohesively across departments. This is where Salesforce’s platform approach stands out—it allows businesses to create both custom and out-of-the-box AI solutions that integrate effortlessly, thanks to a shared metadata foundation. Real-World AI Applications: Smarter Hiring with AI Agents Let’s consider a scenario where a company builds a custom AI agent for its recruiting app to streamline hiring: This approach highlights the value of connecting systems. By enabling seamless data sharing across HR, Legal, and Finance, the AI agent ensures an efficient, collaborative hiring process. Unlike rule-based automation, which follows rigid “if-then” logic, AI agents incorporate context and intelligence into workflows. This makes them more adaptive and impactful, driving real results for businesses. Extending AI’s Reach with Platform Login Licenses While AI agents can transform workflows, not every team member needs full-time access to them. Some employees use these tools daily, while others engage with them occasionally. Platform Login Licenses offer a cost-effective solution by granting temporary, on-demand access. For instance, an employee eligible for a referral bonus might only need to check the HR platform occasionally to track their status. A Platform Login License lets them interact with the AI agent when necessary, without requiring a full-time account. This flexibility ensures companies can extend AI-driven productivity to more users without overspending on unused licenses. Why a Unified Platform Is Essential Salesforce’s unified platform provides the consistency and scalability organizations need, whether using custom-built AI agents or ready-made solutions. By sharing a common metadata foundation, these tools access richer data, leading to smarter decision-making and improved workflows. Seamless data flow between agents and apps enhances collaboration and unlocks the full potential of AI. Teams can work smarter, not harder, with tools tailored to their specific needs, whether they use them daily or occasionally. Start Building Your AI-Driven Future Today AI’s transformative potential lies not just in the technology but in the foundation it’s built upon. A unified platform equips businesses to create powerful, interconnected AI solutions that streamline processes and foster collaboration. With Salesforce’s Platform Login Licenses, you can extend the benefits of AI agents to the right people at the right time—without unnecessary costs. Discover AgentforceLearn how Agentforce AI agents provide continuous support to employees and customers, helping your organization succeed. Explore the Benefits Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 26, 2025in Data, Salesforce, Technology0 Comments
Storing and Querying Log Data with Event Log Objects
25Feb

Storing and Querying Log Data with Event Log Objects

The Event Log Object framework provides a structured way to access event data stored in Salesforce. Unlike Event Log Files, which present event data as downloadable CSV files, Event Log Objects allow users to query event logs directly using SOQL. This approach offers a more integrated and dynamic way to analyze security, performance, and user activity data within Salesforce. Key Features of Event Log Objects Availability and Requirements Enabling Event Log Objects To enable Event Log Objects, follow these steps in Setup: Querying Event Log Data Event Log Objects provide valuable insights through SOQL queries, allowing organizations to track activity across security, application performance, and user engagement. Sample Queries by Use Case Security Analysis Identify users exporting the most rows via reports: sqlCopyEditSELECT UserIdentifier, SUM(RowCount) FROM ReportEventLog WHERE Origin=’ReportExported’ AND DAY_ONLY(Timestamp) > LAST_N_DAYS:10 GROUP BY UserIdentifier ORDER BY SUM(RowCount) DESC Application Performance Monitoring (APM) Track unexpected Apex exceptions by category: sqlCopyEditSELECT ExceptionCategory, COUNT(Timestamp) FROM ApexUnexpectedExcpEventLog WHERE DAY_ONLY(Timestamp) > LAST_N_DAYS:10 GROUP BY ExceptionCategory ORDER BY COUNT(Timestamp) DESC Product Intelligence Determine the most loaded Lightning pages: sqlCopyEditSELECT COUNT(Timestamp), PageUrl FROM LightningPageViewEventLog WHERE DAY_ONLY(Timestamp) > LAST_N_DAYS:10 GROUP BY PageUrl ORDER BY COUNT(Timestamp) DESC Key Considerations Available Event Log Objects Salesforce provides a wide range of Event Log Objects, each designed to capture specific types of system events: Visualizing Log Data with CRM Analytics Organizations can transform raw log data into actionable insights using Salesforce Direct in CRM Analytics. This enables users to: Best Practices for Event Log Objects To maximize the value of Event Log Objects, follow these best practices: By effectively leveraging Event Log Objects, organizations can enhance security monitoring, troubleshoot performance issues, and gain deeper insights into Salesforce activity. For more details on Event Log Objects and their use cases, refer to the Salesforce Object Reference Guide. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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February 25, 2025in Data, Enterprise, Hyperforce, Salesforce, Salesforce Shield0 Comments
Salesforce’s AI Energy Score
08Feb

Salesforce’s AI Energy Score

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

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February 8, 2025in Agentforce Platform, Data, Salesforce, Technology0 Comments
Agentforce Redefines Generative AI
16Jan

Agentforce Redefines Generative AI

Agentforce: Redefining Generative AI in Salesforce Many Dreamforce attendees who expected to hear about Einstein Copilot were surprised when Salesforce introduced Agentforce just a week before the conference. While it might seem like a rebranding of Copilot, Agentforce marks a significant evolution by enabling more autonomous agents that go beyond summarizing or generating content to perform specific actions. Here’s a breakdown of the transition and what it means for Salesforce users: Key Vocabulary Updates How Agentforce Works Agents take user input, known as an “utterance,” and translate it into actionable steps based on predefined configurations. This allows the system to enhance performance over time while delivering responses tailored to user needs. Understanding Agentforce 1. Topics: Organizing Agent Capabilities Agentforce introduces “Topics,” a new layer of organization that categorizes actions by business function. When a user provides an utterance, the agent identifies the relevant topic first, then determines the best actions to address it. 2. Actions: What Agents Can Do Actions remain largely unchanged from Einstein Copilot. These are tasks agents perform to execute plans. 3. Prompts: The Key to Better Results LLMs rely on prompts to generate outputs, and crafting effective prompts is essential for reducing irrelevant responses and optimizing agent behavior. How Generative AI Enhances Salesforce Agentforce unlocks several benefits across productivity, personalization, standardization, and efficiency: Implementing Agentforce: Tips for Success Getting Started Start by using standard Agent actions. These out-of-the-box tools, such as opportunity summarization or close plan creation, provide a strong foundation. You can make minor adjustments to optimize their performance before diving into more complex custom actions. Testing and Iteration Testing AI agents is different from traditional workflows. Agents must handle various phrasing of the same user request (utterances) while maintaining consistency in responses. The Future of Salesforce with Agentforce As you gain expertise in planning, developing, testing, and deploying Agentforce actions, you’ll unlock new possibilities for transforming your Salesforce experience. With generative AI tools like Agentforce, Salesforce evolves from a traditional point-and-click interface into an intelligent, agent-driven platform with streamlined, conversational workflows. This isn’t just an upgrade — it’s the foundation for reimagining how businesses interact with their CRM in an AI-assisted world. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 16, 2025in Agentforce Platform, AI Tools, Data, Generative AI, Salesforce
Salesforce Spring ’25 Release
09Jan

Salesforce Spring ’25 Release

Salesforce Spring ’25 Release: Key Features and Enhancements Salesforce delivers triannual updates—Spring, Summer, and Winter—to introduce new features, enhancements, and fixes to the platform. These updates are applied automatically to Salesforce environments, ensuring all users benefit from the latest innovations without needing manual upgrades. The Spring ’25 functionality is now available in Preview Developer Orgs, allowing users to explore and test upcoming features before the general release. Preview Developer Orgs: Exploring the Future Preview Developer Orgs provide sandbox environments or developer editions equipped with new release functionality during the preview window. These allow admins and developers to: With access to a Preview Org, you can explore the following cutting-edge features: 1. Reactive Screen Actions Enhanced Screen Flow Reactivity: This feature enables screen flow components to update dynamically in real-time based on changes in other components. Users no longer need to navigate away or manually refresh to see updates, ensuring smoother, more interactive experiences. New in Spring ’25:You can now create an autolaunched flow to fetch data reactively from the database and display it immediately on the screen, eliminating the need for an action button. Use Case:When creating an Opportunity, the ZIP code of the associated Account determines the follow-up owner based on a reference table stored in a custom object. With reactive screen actions, selecting an Opportunity row dynamically displays the Account, Owner, and Assigned Person without additional clicks. 2. Progress Indicator for Flow Stages Salesforce introduces a built-in Progress Indicator for screen flows, providing users with a visual tracker of their progress through multi-step flows. Key Features: Limitations:The progress indicator does not yet support user-driven navigation through stages. 3. Immediate Input Validation in Screen Flows Validation functionality in flows has been upgraded to support real-time error detection. What’s New: 4. Email Action Attachment Support Email Action Enhancements: Spring ’25 introduces the ability to attach files to emails directly within flows. How It Works: Note: Files do not need to be made public for attachments, as long as the flow user has access to the files. 5. Get Records with a Specified Limit The LIMIT operator, commonly used in SOQL, is now available in flows. Benefits: 6. New Flow Modal Enhancements Salesforce has redesigned the Flow Type Picker modal, making it easier for users to select the right automation type. What’s New: 7. UI and Accessibility Improvements Conclusion The Salesforce Spring ’25 release is packed with features designed to enhance efficiency, usability, and innovation. From reactive screen flows and real-time validation to email action attachments and improved UI elements, this release sets a new standard for how users interact with the Salesforce platform. Stay ahead by leveraging Preview Developer Orgs to test these enhancements and ensure a smooth transition to the production environment. As Salesforce continues to innovate, these updates are just the beginning of a more seamless, intelligent platform experience. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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January 9, 2025in Data, Salesforce

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