heymrun/heym

Workflow & Automation · tested 2026-07-21 · re-test due 2026-10-19 · by the Hlido desk, not the vendor

In short: A serious self-hosted, no-code AI workflow platform — strong observability and agent features, with a source-available (not OSI) license worth reading before you commit.

4 PASS · 1 FAIL of 5 public-surface claims

Quick answer

heymrun/heym scores 80/100 (STEADY) on Hlido’s independent, hands-on test (reviewed 2026-07-21). STEADY (80) because it delivers a genuinely capable self-hosted workflow platform with the observability, HITL and eval features that separate production tooling from demos, plus a real integration surface (REST/SSE/webh

Heym is a self-hosted, source-available platform for building AI workflows on a drag-and-drop canvas — think of it as an AI-native automation studio you run yourself. What raises it above the crowded no-code-AI pile is the depth on the parts that usually get skipped: full LLM observability with traces and USD token-cost tracking, human-in-the-loop pauses for approval, an evals system for testing workflows, and MCP support as both client and server. The agent story is real too — multi-agent setups with sub-agents and sub-workflows, a portable skills system, RAG against Qdrant or pgvector, and Playwright browser automation with AI auto-healing of broken selectors. For integration it exposes REST execution endpoints, SSE streaming, webhook triggers and a Portal chat UI. At 761 stars, 967 commits and 75 releases it's clearly past the weekend-project stage. The one thing to read carefully before adopting: the license is MIT with the Commons Clause, which means source-available, not OSI open-source — you can self-host and inspect it, but commercial resale is restricted and a commercial license exists. That's a legitimate model, but it's a different bargain than plain MIT, and buyers should know which one they're signing up for.

Why STEADY

STEADY (80) because it delivers a genuinely capable self-hosted workflow platform with the observability, HITL and eval features that separate production tooling from demos, plus a real integration surface (REST/SSE/webhooks/MCP). Held below VITAL by the Commons Clause license (source-available, not OSI open — a real adoption consideration) and the fact that the public surface is a README rather than an evidenced product with independent reliability data.

Public-surface checklist

What we saw

1 screenshot captured by the Hlido engine during the reviewed run (run-b991e9a0f24cde49-github-com). Our own captures — not vendor marketing material.

heymrun/heym — run screenshot 1 (home.png)
home.png

What it does well

What it fails at

Red flags

Best for

  • Teams that need self-hosted AI automation for data-privacy or control reasons
  • Builders wanting observability and cost tracking baked into their workflow engine
  • Multi-agent workflow projects that benefit from HITL gates and evals
  • Orgs comfortable running Postgres/Docker infrastructure

Not recommended for

  • Buyers who require OSI-approved open-source licensing
  • Non-technical users wanting a fully hosted, zero-infrastructure SaaS
  • Teams needing a documented SDK/CLI rather than REST + webhooks

Pricing & access

Derived from Hlido-held evidence only (engine checklist + editorial text); quotes are verbatim from the scorecard; not vendor-supplied; re-derived daily. Verify current prices on the vendor's pricing page. Last verified 2026-06-13.

Compared to

Agent relevance

API MCP Webhook Behavioral-testable

Agentic-Commerce Readiness 69/100 · INTEGRABLE

Independent readiness for agent delegation & transaction. How it’s scored · check live

Strong. Exposes REST execution endpoints, SSE streaming, webhook triggers and an MCP server, so external agents can invoke Heym workflows and Heym can consume external MCP tools. Designed as an orchestration layer other agents can call.

Agent-friendly score: 8/10

Evidence

scorecard.json · transparency passport · registry · methodology

More: compare agents · best of · developer tools · incident registry

Verdict by Hlido Editor, our automated editorial system · Method: public-surface-tier-1+editorial-narrative-v2 · Methodology version 2026.07 · Next review due 2026-10-19

How this page was produced. The scores, claim verdicts and evidence come from automated hands-on testing of the product’s public surface. The written analysis is drafted by an AI system, and pages publish without a person reviewing each one. Hlido publishes this record and answers for it — tell us if anything here is wrong and we will correct it.

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