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Head-to-head · AI Observability

OpenLIT vs Agenta

OpenLIT is for AI observability; Agenta is for AI coworkers. Both offer free self-hosting, but their hosted pricing differs.

OpenLIT

7.4/10
VS

Agenta

6.5/10

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Short answer

It's a split decision.

These are not direct substitutes. Choose OpenLIT for AI observability: it covers LLM traces, evaluations, prompt management, guardrails, and GPU and cost monitoring, with a free Apache 2.0 self-hosted edition. Choose Agenta to build AI coworkers that act through Slack or Telegram, connected tools, and scheduled or triggered tasks. Agenta's self-hosted edition is free; hosted Starter starts at $29/month. OpenLIT Cloud pricing is not published, so compare the jobs they do, not just sticker prices.

01Side by side

OpenLITAgenta
Starting price$0/month self-hosted; hosted price not published$0 self-hosted; hosted Starter is $29/month
Free planApache 2.0 OSS; unlimited self-hosted useMIT OSS; unlimited users, projects, agents, automations
Best forTracing, evaluating, and monitoring AI agentsBuilding AI coworkers for Slack, Telegram, automations
Core strengthOpenTelemetry-native traces, evaluations, prompts, GPU monitoringAgent workflows, 1,000+ integrations, scheduled tasks
Learning curveEase score 6.2/10; self-hosting is the trade-offEase score 6/10; self-hosting is available
Integrations/dataExports telemetry to other OpenTelemetry backendsConnects to more than 1,000 integrations
Team/seat costsOSS unlimited usage; Enterprise licensed per organizationOSS unlimited users; Starter includes unlimited team members
SupportSupport details not published; review score 6/10GitHub community, live chat, or dedicated support by tier

Choose OpenLIT if

  • You need OpenTelemetry-native LLM tracing and evaluation.
  • You want prompt versioning, guardrails, or GPU monitoring.
  • You can self-host and accept unknown hosted pricing.

Choose Agenta if

  • You need AI coworkers in Slack or Telegram.
  • You want scheduled or trigger-based task automation.
  • You prefer hosted plans starting at $29/month.

02Pricing compared

OpenLIT’s OSS edition is $0 under Apache 2.0, with unlimited self-hosted usage and no per-trace fee. Its Enterprise plan is priced by organisation, but the price is “Contact us.” OpenLIT Cloud is listed as coming soon, with pricing to be shared at launch.

Agenta also offers a free self-hosted open-source edition, with unlimited users, projects, agents and automations. Its hosted Hobby plan is free; Starter is $29/month and Business is $299/month. Starter includes 2,900 monthly credits and 20 concurrent tasks; Business lists 32,000 credits and 50 concurrent tasks. Extra credits cost $10 for 1,000, $25 for 2,500 or $100 for 10,000, with no overage charges. Annual pricing for Starter and Business is not published. The prices aren’t directly comparable: OpenLIT monitors AI systems, while Agenta runs AI coworkers.

03Features and depth

OpenLIT is the fit for teams that need to inspect and improve AI systems. It traces LLM calls, tools and retrieval, with filters for user, session, cost, latency and metadata. Evaluations can use LLM judges, heuristics or human review. The platform also includes prompt versioning and rollback, guardrails, cost monitoring, an API key vault and GPU monitoring for NVIDIA, AMD and Intel hardware. Its OpenTelemetry-native design lets teams export telemetry to other OpenTelemetry backends.

Agenta is for building AI coworkers that take actions. Teams can create custom agents, use them in Slack or Telegram, connect more than 1,000 integrations, and run tasks on schedules or triggers. Approval controls let teams decide which actions run automatically. Self-hosting is available under the MIT license. That doesn’t make Agenta an observability replacement: its listed focus is agent creation and automation, not tracing LLM calls, evaluating traffic or monitoring GPU use. OpenLIT’s agent monitoring, meanwhile, doesn’t make it an equivalent task-automation product.

04Ease of use and learning curve

The learning curve depends on what you’re trying to get done. OpenLIT requires a self-hosted setup for its free OSS edition; teams choosing it should be prepared to operate their own infrastructure. The hosted Cloud option is not yet available, and its pricing is not published.

Agenta offers hosted plans as well as self-hosting. Its open-source deployment uses Docker Compose, and teams bring their own models and credentials. The product involves configuring agents, integrations and task triggers; its pricing also puts limits on credits and concurrent tasks for hosted plans. The available information doesn’t establish which product is easier to learn. Choose based on whether your team needs observability workflows or agents that act in connected tools.

Questions people ask

Are OpenLIT and Agenta direct alternatives?

No. OpenLIT focuses on AI observability, including LLM tracing, evaluations, prompt management and cost and GPU monitoring. Agenta focuses on building AI coworkers that use integrations and run tasks in Slack, Telegram or on schedules. Choose by job, not by name or open-source status.

Which product is cheaper?

Both have a free self-hosted option. OpenLIT OSS lists unlimited self-hosted usage and no per-trace fee. Agenta’s open-source edition lists unlimited users, projects, agents and automations. Agenta hosted Starter is $29/month and Business is $299/month; OpenLIT Cloud pricing is not published.

Can I self-host both products?

Yes. OpenLIT OSS is free under Apache 2.0, and Agenta’s open-source edition is free under the MIT license. Agenta lists Docker Compose deployment. OpenLIT’s listed self-hosted plan has unlimited usage; its Cloud offering is coming soon, with pricing to be shared at launch.

Does Agenta replace OpenLIT for AI observability?

Not based on the listed features. OpenLIT provides LLM traces, evaluations, prompt management, cost monitoring and GPU monitoring. Agenta’s listed capabilities center on building and running AI coworkers through integrations, chat workflows and scheduled or triggered tasks. They address different parts of an AI stack.