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Product

Four AI agents for your Salesforce org, with a human in every write.

The Salesforce Agent Platform connects to your org and your repo, then gives your teams agents for understanding, building, selling, and supporting on top of Salesforce.

Four agents, one platform

Each agent is built on the same shared plumbing: organizations, permissions, connections, the LLM layer, and background jobs.

Agent 01

Org Intelligence

Builds a living picture of your Salesforce org and metadata repo: objects, automation, Apex and LWC, permissions, integrations, and drift between org and repo.

  • Health score and tech-debt findings
  • Org vs. repo drift detection
  • Versioned snapshots you can diff
Agent 02

Dev Agent

Designs and builds business automation and UI, choosing between Flow and Apex, scaffolding Apex, LWC, and Flow, and running static analysis before anything is reviewed.

  • Design, then approve, then generate
  • PMD, ESLint, and Code Analyzer checks
  • Opens pull requests. Never deploys directly
Agent 03

Sales Agent

Pipeline insight for reps and managers: forecast rollups, deal risk flags, coaching, and grounded follow-up drafts over your playbooks and deal data.

  • Forecast and win-rate figures computed, not guessed
  • Deal risk rules with reasons
  • Drafts only. Nothing is sent or written to Salesforce
Agent 04

Service Agent

Case triage, sentiment, knowledge suggestions, and response drafting, with escalation driven by rules you configure.

  • Structured triage and escalation rules
  • Replies grounded in your knowledge base
  • Read-only access to cases. Never writes to Salesforce

Build your own agents and workflows

The four built-in agents are a starting point. Your team can design agents and multi-step flows that fit your processes, using the same tools, permissions, and approvals.

Custom agents

Admins configure chat agents for a specific job, choose the tools they can use, and publish them to the people who need them.

  • Role-based access per agent
  • Tools limited to what you allow
  • Usable in the console and in Slack

Agentic workflows

Design multi-step flows that combine tool calls, agent steps, and conditions, with triggers and an approval step where a person must sign off.

  • Visual workflow designer
  • Approvals with named approvers and timeouts
  • Runs tracked step by step

RAG-grounded agents

Load your documents, runbooks, and enablement content into vector collections, then let agents and workflow steps search them before they answer.

  • Collections from files, the API, or a workflow
  • Vector search steps inside flows
  • Answers tied to the source material

Connects to the tools you already use

Agents work where your engineering, delivery, and sales teams already work. Each connection uses scoped, encrypted credentials.

Git

GitHub repositories

Connect a repository to analyze your Salesforce metadata, track drift against the org, and have the Dev Agent open pull requests on new branches.

Jira

Jira Cloud

Start an agent request from a ticket, post progress back, and let the platform update ticket status as work moves through review.

Slack

Channels and direct messages

Get notifications, ask the agents questions, and approve workflow steps from Slack without switching tools.

Salesforce

OAuth and JWT

Read orgs, metadata, and pipeline data through each user's own connection, so Salesforce permissions still decide what each person sees.

Built for security and control

Agents are only useful if your admins and security team can trust them. These are the guarantees the platform is designed around.

Permissions come from Salesforce

Sales and Service reads run through the user's own Salesforce connection, so sharing rules, role hierarchy, and field-level security still apply.

Tenant isolation by design

Every organization's data is row-isolated, and the role is re-read on every request. Removing a member takes effect on their next request.

Humans approve every write

Write actions wait for a person to approve their exact inputs. Changes ship as reviewed pull requests, never as direct deployments.

Model-agnostic, Claude by default

A provider-agnostic LLM layer runs Claude by default, with tool calls validated against schemas and every model call metered per organization.

How it fits together

Your people reach the platform through the console, Slack, or Claude Code. One core runs every agent, workflow, and search, and reaches your data and tools through scoped connections.

Salesforce Agent Platform architecture Users reach the platform core through the web console, Slack, or Claude Code. The core runs the API, background worker, agent runtime, RAG search, and workflows. It uses PostgreSQL with pgvector, Redis, Claude, and Voyage embeddings, and connects to Salesforce, GitHub, Jira, and Slack. Web console Vue, Firebase Hosting Slack Ask, approve, notify Claude Code MCP server Platform core API Flask, Cloud Run Worker Background jobs Agent runtime Tools and agents RAG search pgvector retrieval Workflows Steps and approvals Data and model services PostgreSQL + pgvector Redis Cache, jobs Claude LLM Voyage Embeddings Connected systems Salesforce OAuth, JWT GitHub Repos and PRs Jira Tickets Slack Messages

The platform underneath

The agents share one foundation, so new capabilities arrive as a new agent or tool rather than a new product. Deployment runs on Google Cloud, with the web console on Firebase Hosting.

  • Multi-tenant organizations with role-based access
  • Salesforce (OAuth) and GitHub connections, encrypted at rest
  • Background jobs with progress tracking
  • Retrieval (RAG) over your knowledge with pgvector
  • Agent chat console and analytics
  • Audit log and rate limits on every tenant

See the agents on your own org

Tell us which Salesforce processes you want to speed up, and we'll show you where the agents fit.