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Agentforce

Enterprise AI agent platform that enables companies to build, deploy, and manage autonomous AI agents that work 24/7 for customers, suppliers, and employees. Integrates with Salesforce ecosystem and trusted business data.

Starting at~$2 per conversation
Visit Agentforce →
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Overview

Agentforce is Salesforce's enterprise-grade AI agent platform, designed to let organizations build, deploy, customize, and manage autonomous AI agents that operate around the clock across customer service, sales, marketing, commerce, and internal employee workflows. Unlike standalone chatbots or copilots that simply respond to prompts, Agentforce agents are positioned as true digital labor — they reason over trusted business data, take actions in connected systems, hand off to humans when needed, and continuously learn from outcomes within the Salesforce Customer 360 ecosystem.

At the core of Agentforce is the Atlas Reasoning Engine, which combines large language models with retrieval over Salesforce Data Cloud, customer metadata, and business policies to plan multi-step tasks. Agents can be assembled in the Agent Builder using natural language, where admins define topics (areas of responsibility), instructions (guardrails and tone), and actions (Flows, Apex, prompt templates, MuleSoft APIs, or external tools). This means companies can stand up specialized agents — for example, a Service Agent that resolves returns end to end, a Sales Development Representative agent that nurtures inbound leads 24/7, a Personal Shopper for ecommerce, or an internal HR agent that answers benefits questions — without having to write a model from scratch.

Because Agentforce is layered on Salesforce, it inherits the platform's permissioning, audit logs, and the Einstein Trust Layer, which adds zero-data-retention prompts, toxicity detection, PII masking, and bias scoring. This is the platform's main pitch to regulated industries: agents that can act on real customer data without that data leaking into third-party model training. Agentforce can be embedded in Service Cloud, Sales Cloud, Slack, Tableau, Commerce Cloud, and any custom site, and it interoperates with external models via BYO LLM and partner integrations including Anthropic, Google, OpenAI, and others through Model Builder.

Agentforce is sold primarily on a consumption basis (per-conversation pricing) on top of existing Salesforce licenses, making it most economical for organizations already invested in the Salesforce stack. It is positioned as a direct competitor to Microsoft Copilot Studio, Google Agentspace, ServiceNow AI Agents, and standalone agent frameworks, with Salesforce emphasizing deeper CRM grounding and out-of-the-box business actions as its differentiator. The platform has become Salesforce's flagship AI bet, with Agentforce 2.0 and 3.0 expanding voice agents, Slack-native agents, agent-to-agent collaboration, and an AgentExchange marketplace of pre-built skills from partners.

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Key Features

Atlas Reasoning Engine: Salesforce's planning layer that decomposes user goals into multi-step task graphs, retrieves grounding data from Data Cloud, evaluates candidate actions, and refines plans based on observed outcomes+
Agent Builder: low-code studio where admins define an agent's Topics (domains of responsibility), Instructions (behavior and guardrails), and Actions (Flows, Apex, prompt templates, MuleSoft APIs, or external connectors)+
Einstein Trust Layer: governance layer providing PII masking, zero data retention agreements with model providers, toxicity and bias scoring, audit logs, and policy enforcement before prompts leave Salesforce+
Data Cloud grounding: agents retrieve real-time, unified customer profiles, transaction history, and unstructured content (PDFs, knowledge articles, emails) via vector and hybrid search rather than relying on model memory+
Pre-built agent templates: ready-to-customize Service Agent, Sales Development Rep, Sales Coach, Personal Shopper, Campaigns, and Employee agents that shorten go-live time+
Model Builder and BYO LLM: route reasoning to Anthropic, OpenAI, Google, Amazon Bedrock, or customer-hosted models, with consistent trust and observability tooling+
Voice and Slack channels: native voice agents for phone deployments and Slack-native agents that operate inside team channels and DMs+
AgentExchange: marketplace of partner-built topics, actions, and full agent templates installable into a customer org+
Testing Center: automated evaluations, regression tests, and synthetic conversation generation to validate agent behavior before and after deployment+

Pricing Plans

Agentforce Service Agent

~$2 per conversation

    Agentforce Sales Agents (SDR & Sales Coach)

    Custom enterprise pricing

      Agentforce for Employees

      Custom enterprise pricing

        Agentforce Platform / Foundations

        Included with qualifying Salesforce editions

          See Full Pricing →Free vs Paid →Is it worth it? →

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          Best Use Cases

          đŸŽ¯

          Scaling Tier-1 customer service to handle case deflection, returns, order status, and password resets 24/7 with seamless human handoff in Service Cloud

          ⚡

          Automating inbound lead qualification and follow-up with an SDR agent that researches accounts, drafts emails, and books meetings into AEs' calendars

          🔧

          Powering personalized ecommerce experiences with a Personal Shopper agent that recommends products, answers questions, and completes checkout via Commerce Cloud

          🚀

          Standing up internal employee agents in Slack for HR benefits questions, IT ticket triage, and policy lookups grounded in company documents

          💡

          Augmenting field service operations with agents that schedule technicians, troubleshoot equipment, and update work orders from mobile

          🔄

          Running outbound marketing campaigns where agents segment audiences, draft creative variants, and adjust send strategy based on engagement data

          Pros & Cons

          ✓ Pros

          • ✓Deep native integration with Salesforce CRM data, Flows, Apex, and Data Cloud means agents can take real actions on opportunities, cases, and accounts without custom plumbing
          • ✓Einstein Trust Layer provides enterprise-grade governance with PII masking, zero data retention, audit trails, and toxicity detection — critical for regulated industries
          • ✓Low-code Agent Builder lets admins define topics, instructions, and actions in natural language, so non-developers can ship production agents
          • ✓Pre-built agent templates (Service Agent, SDR, Sales Coach, Personal Shopper, Campaigns) shorten time-to-value compared to building from a generic framework
          • ✓BYO LLM and Model Builder support let customers swap in Anthropic, OpenAI, Google, or fine-tuned private models rather than being locked to one vendor
          • ✓AgentExchange marketplace and partner ecosystem provide reusable skills, topics, and prompt templates from ISVs and SI partners

          ✗ Cons

          • ✗Per-conversation consumption pricing (~$2 per conversation) can become unpredictable and expensive at scale, especially for high-volume self-service deployments
          • ✗Real value is gated behind owning Salesforce Data Cloud and the broader Salesforce stack — standalone adoption is impractical and not the intended use case
          • ✗Implementation typically requires Salesforce-certified partners or internal admins fluent in Flows, Apex, and Data Cloud, raising the total cost of ownership
          • ✗Customers have reported gaps between marketing claims about autonomy and the reality of needing significant prompt engineering, topic tuning, and human oversight
          • ✗Less flexible than open agent frameworks (LangGraph, CrewAI) for novel non-CRM use cases or for teams that want full control over orchestration code

          Frequently Asked Questions

          What is Agentforce and how is it different from Einstein Copilot?+

          Agentforce is Salesforce's platform for building autonomous AI agents that proactively take actions across business workflows, while Einstein Copilot was a conversational assistant embedded in Salesforce apps. Einstein Copilot has been folded into the broader Agentforce platform, which now encompasses both assistive copilots and fully autonomous agents that can resolve cases, qualify leads, or run commerce tasks end to end.

          How much does Agentforce cost?+

          Agentforce is sold on a consumption model, historically around $2 per conversation, on top of the customer's existing Salesforce licenses and Data Cloud subscription. Pricing varies by edition, agent type (service, sales, voice), and negotiated enterprise agreements, so most deployments require a custom quote from Salesforce.

          Can Agentforce use models other than Salesforce's own?+

          Yes. Through Model Builder and BYO LLM support, Agentforce can route reasoning to Anthropic Claude, OpenAI GPT, Google Gemini, Amazon Bedrock models, or customer-hosted fine-tuned models, while still applying the Einstein Trust Layer for governance.

          Is customer data used to train the underlying models?+

          No. The Einstein Trust Layer enforces zero data retention with model providers, masks PII before prompts leave the Salesforce environment, and prevents customer data from being used to train third-party foundation models. All interactions are logged for audit within Salesforce.

          What kinds of agents can be built with Agentforce?+

          Common deployments include service agents that resolve customer cases, SDR agents that engage and qualify inbound leads, personal shopper agents for commerce sites, sales coach agents that prep reps for calls, marketing campaign agents, and internal employee agents for HR, IT, and operations questions, all assembled in Agent Builder from topics, instructions, and actions.
          đŸĻž

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          What's New in 2026

          Heading into 2026, Salesforce has continued to expand Agentforce well beyond its original service-agent roots. Agentforce 3 introduced an upgraded Atlas Reasoning Engine with improved multi-step planning, agent-to-agent delegation so specialized agents can collaborate on complex workflows, and richer voice capabilities for contact centers. The AgentExchange marketplace has grown substantially, with hundreds of partner-built topics and actions available for one-click installation. Native integrations with Anthropic Claude, Google Gemini, and other frontier models via Model Builder give customers more choice in the underlying LLM. Slack has been repositioned as a primary surface for Agentforce, with agents operating directly in channels and DMs alongside humans. Salesforce has also rolled out Testing Center for automated agent evaluation, expanded Agentforce for Field Service, Commerce, and Marketing, and announced deeper interoperability with MCP-style tool standards so external systems can be exposed to agents more easily.

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          Quick Info

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          AI Agents

          Website

          www.salesforce.com/agentforce/
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