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Head-to-head · AI Observability

OpenLIT vs Agenta

Choose OpenLIT for OpenTelemetry-native agent observability; choose Agenta to build task-running AI coworkers for Slack or Telegram.

OpenLIT

7.7/10
VS

Agenta

7.1/10

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Short answer

It's a split decision.

OpenLIT is an OpenTelemetry-native observability and evaluation platform for AI agents, with free Apache 2.0 self-hosting and telemetry export. Agenta is an AI coworker platform for building agents that run tasks through Slack or Telegram, connect to tools and work on schedules or triggers. Pick OpenLIT if your codebase needs tracing, evaluations, prompt management and cost monitoring. Pick Agenta if you need team-facing automations and its larger integration catalog. Their pricing models differ: OpenLIT lists no per-trace fee; Agenta charges for cloud plans and credits.

01Side by side

OpenLITAgenta
Pricing modelFree OSS; Enterprise contact pricing; Cloud coming soon$0 Open source; paid cloud from $29/month
Free tierUnlimited self-hosted usage; no per-trace fee500 signup credits; 75 daily credits up to 10 days/month
Open source and licenceApache 2.0; free self-hosted editionMIT; self-hosted edition
Self-hostingSelf-hosted, unlimited usage under OSSDocker Compose; unlimited agents, users, projects
API and SDKsPython package; OpenTelemetry-native instrumentationSDK/API details not published; Slack/Telegram workflows
Integrations56+ LLM, agent, vector database, GPU integrations1,000+ integrations, including Slack, GitHub, Notion
Deployment modelSelf-hosted now; cloud coming soonCloud tiers and Docker Compose self-hosting
Data exportOpenTelemetry telemetry export to other backendsSelf-managed retention; export path not published

Choose OpenLIT if

  • Choose OpenLIT if you need OpenTelemetry-native tracing across LLM calls, tools and retrieval.
  • Choose OpenLIT if production evaluations, prompt versioning and cost monitoring belong in one platform.
  • Choose OpenLIT if free, Apache 2.0 self-hosting and telemetry export matter.

Choose Agenta if

  • Choose Agenta if teams need AI coworkers in Slack or Telegram.
  • Choose Agenta if agents must run scheduled tasks or react to connected tools.
  • Choose Agenta if its 1,000-plus integrations fit your team’s workflows.

02Pricing at real usage

OpenLIT’s OSS edition is listed at $0 per month, with unlimited self-hosted usage and no per-trace fee. The Enterprise plan is priced by organisation, with the vendor listing “Contact us”; its Cloud offering is marked “Coming soon,” with pricing to be shared at launch. Self-hosting is free, but the pricing page does not give a hosted price.

Agenta’s Open source plan is also $0 per month, with unlimited users, projects, agents and automations. Its Hobby cloud plan is free and includes 500 signup credits, 75 free credits a day for up to 10 days monthly, and two concurrent tasks. Starter costs $29 per month for 2,900 monthly credits; Business costs $299 for 32,000. Starter and Business credit packs cost $10 for 1,000 credits, $25 for 2,500, or $100 for 10,000; the pricing page says there are no overage charges.

03API, SDKs and integration

OpenLIT is designed around OpenTelemetry instrumentation. Its homepage shows a Python install and initialization path: pip install openlit and openlit.init(). The platform traces LLM calls, tools and retrieval, and the homepage lists 56+ integrations across LLMs, agent frameworks, vector databases and GPUs, alongside OpenTelemetry sources. Its documentation is linked from the homepage. Agenta does not publish language-specific SDK or API details on its homepage. It exposes agent workflows through Slack or Telegram and connects agents to tools; examples of integrations include Slack, Notion, GitHub, HubSpot, Google Drive, Linear and Zendesk. The homepage says the catalog has more than 1,000 integrations.

The products solve different integration problems. OpenLIT adds observability and evaluation to an AI application; Agenta connects team tasks to agents and tools. Agenta links to documentation, a changelog and a roadmap. Neither homepage lists a CLI, so teams choosing a command-line workflow should confirm support before adopting either.

04Open source, self-hosting and lock-in

OpenLIT is licensed under Apache 2.0 and can be self-hosted with unlimited usage under its OSS plan. Its OpenTelemetry-native design lets teams export telemetry to other OpenTelemetry backends, which can reduce dependence on OpenLIT for traces. That does not establish that prompts, evaluations or dashboards migrate with the telemetry, so check those paths separately.

Agenta is MIT-licensed and can run on your infrastructure through Docker Compose. Its open-source plan includes self-managed data retention and lets teams bring their own models and credentials. Those controls provide room to manage hosting and model choice, but the vendor does not publish a data-export path. Ask about exporting agent definitions, task history and configuration before building workflows that would be costly to recreate.

Questions people ask

Is OpenLIT or Agenta cheaper?

Both list a $0 self-hosted or open-source option. OpenLIT says its OSS edition has unlimited self-hosted usage and no per-trace fee. Agenta lists cloud plans at $29 per month for Starter and $299 for Business, with credit packs available for extra capacity.

Can I self-host OpenLIT and Agenta?

Yes. OpenLIT offers free self-hosting under Apache 2.0. Agenta is MIT-licensed and supports self-hosting on your infrastructure, with Docker Compose listed as a deployment option. Hosting costs and operational work depend on your own infrastructure.

Which product has more integrations?

Agenta says it works with more than 1,000 integrations, including Slack, Notion, GitHub, HubSpot, Google Drive, Linear and Zendesk. OpenLIT lists 56+ integrations across LLMs, agent frameworks, vector databases and GPUs, as well as OpenTelemetry sources.

Do OpenLIT and Agenta offer SDKs?

OpenLIT’s homepage shows a Python installation and initialization path using pip install openlit and openlit.init(). Agenta’s homepage focuses on agent workflows in Slack or Telegram and does not publish language-specific SDK details. Check the documentation for current implementation options.