Heym helps AI, platform, and automation teams deploy, observe, and govern business-critical agents and workflows on their own infrastructure, with single sign-on, multi-instance execution, and a streamed audit trail. Heym Cloud is coming soon.
Most teams can build an impressive agent prototype in a week. Production is where things stall: nobody can say exactly what the agent did, what it cost, or who approved the action it took. Heym runs agentic workflows and enterprise AI workflow automation as business-critical systems, with the control, visibility, and support that production demands.
Run Heym on-premises, in your VPC, or air-gapped. Self-hosted deployment means customer and revenue data never leaves your servers, and because Heym is source-available, security can audit every line before you ship. You bring your own models and credentials, so there is no lock-in to switch away from.
Run locally
Start Heym locally with the included run.sh script and own the full runtime from day one.
Single sign-on against your own identity provider, execution spread across as many instances as the work needs, and an audit line for every privileged action, streamed wherever your logs already go.
An administrator pastes an issuer URL under Settings → SSO, and Heym reads the authorization, token, and key endpoints from your provider's own discovery document. No provider is hardcoded, so Keycloak, Okta, Entra ID, Auth0, and Google connect through the same fields. A connection test tells you the setup is right before anyone depends on it.
Point a second instance at the same PostgreSQL database and it joins as a worker. Agent runs, cron, webhooks, and chat triggers are then shared between instances by a weight you set under Settings → Instances. The instances never talk to each other, so a worker needs no open port and no route back.
Every sensitive action leaves a record: who did it, what they touched, and whether it worked. There is nothing to switch on and nothing extra to run, so the record keeping starts on your first day. Your team can watch it happen live inside Heym, or send it to wherever your company already keeps its logs, so the history is still there months later.
Every workflow run produces a full trace: each node, each agent decision, each tool call, and each model call with token and cost visibility. When something fails, you see where and why instead of guessing. Read the AI agent observability guide for how teams debug agents in production.
Agents draft, people decide. Add human-in-the-loop checkpoints before emails go out, records change, or money moves. Reviewers see the full context, approve or reject, and the workflow continues or stops. Nothing critical happens unattended unless you decide it should.
Native nodes cover GitHub, Jira, Slack, Telegram, email, Google Sheets, BigQuery, and more. HTTP and webhook nodes reach any internal API, and MCP support connects Heym to the growing ecosystem of tool servers. When you need a connector that does not exist yet, we build, package, and deliver it as a plugin for your deployment.
Three patterns that turn agentic systems into dependable operations.
Agents answer from your documents with retrieval and citations, so policies, contracts, and internal knowledge stay current and queryable.
Legal, finance, sales, and support workflows where agents prepare the work and people approve it before anything is sent or saved.
A lead agent coordinates specialist agents across sources and data systems and returns structured, traceable results.
Bring one valuable workflow into production in four to six weeks. We help your team deploy Heym, connect one or two core systems, add approval checkpoints, and establish tracing and cost visibility. The engagement starts with agreed success metrics and ends with a production rollout plan and a commercial licensing proposal.
Enterprise customers pay for reduced production responsibility, not just software. Engagements can include commercial licensing, deployment and onboarding, migration support, custom integrations, managed upgrades, architecture reviews, and agreed response times for production issues.
The questions that come up in every procurement review, answered with the mechanism behind each one.
Tell us about your team and the workflow you want in production. We will tailor a walkthrough to your stack, or reach us at enterprise@heym.run.
AI workflows don't fail because of prompts. They fail because of orchestration.
One canvas for agents, RAG, human-in-the-loop, MCP, traces, evals, and alerts, self-hosted and observable.
Practical guides for tracing, OpenTelemetry, RAG, and multi-agent orchestration.
A practical guide to tracing, monitoring, costs, and production debugging for AI agents.
Read guideTrace every workflow step with spans, context propagation, and native OTLP export.
Read guideArchitecture, chunking, vector search, and LLM wiring for reliable retrieval workflows.
Read guideOrchestrator patterns, specialist agents, and practical ways to coordinate agent teams.
Read guide