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Activepieces vs Koyeb

Activepieces scores higher on the AgentReady, 63/100 against 57/100. They differ on 11 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Activepieces. AI automation platform that lets teams build agents and automations through chat, with enterprise-grade governance and 760+ integrations

Koyeb. Developer-friendly serverless platform designed to let businesses and developers easily deploy reliable and scalable applications globally, with high-performance infrastructure for AI inference, sandboxes, and microservices on CPUs, GPUs, and accelerators

Where Activepieces is ahead

Activepieces passes clear canonical domain and llms.txt published, and Koyeb does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: authentication documented. Koyeb misses it.

And on operate, structured, predictable output, retry behavior documented, idempotency support and agent compatibility verified. Koyeb misses those.

Where Koyeb is ahead

Koyeb passes no mandatory sales call, agent-compatible signup flow, official typescript sdk and official python sdk, and Activepieces does not. That is adopt, whether an agent can get a key and make its first successful call without a human in the loop.

What neither does

Both fail llms-full.txt / full agent docs, structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented, programmatic credential creation, machine-readable errors, rate-limit behavior predictable. If your agent needs any of those, you will be building it yourself either way.

Score, pillar by pillar

The AgentReady splits into four pillars, scored separately, because a product can be easy to find and still impossible to adopt.

Discover. Activepieces leads 93 to 80. Activepieces misses llms-full.txt / full agent docs; Koyeb misses clear canonical domain, llms.txt published, llms-full.txt / full agent docs.

Understand. Activepieces leads 31 to 23. Activepieces misses structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; Koyeb misses structured api reference, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented.

Adopt. Koyeb leads 90 to 52. Activepieces misses no mandatory sales call, agent-compatible signup flow, programmatic credential creation, official typescript sdk, official python sdk; Koyeb misses programmatic credential creation.

Operate is whether an agent can run against it in production and recover when a call fails. Activepieces leads 76 to 35. Activepieces misses machine-readable errors, rate-limit behavior predictable; Koyeb misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified.

Pricing

Activepieces does not publish a machine-readable starting price and has a free tier. Koyeb does not publish one and has a free tier.

Signal by signal

Which to pick

Activepieces clears more of the signals an agent needs, so it is the safer default for unattended use. Full profiles: Activepieces and Koyeb. Alternatives to each: Activepieces, Koyeb.

An agent can fetch this as data: POST /v1/compare {"slugs": ["activepieces", "koyeb"]}