Agenta vs OpenLIT
Agenta
agenta.aiOpenLIT
openlit.ioSide by side
| Figure | Agenta | OpenLIT |
|---|---|---|
| Price from | $29/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | Yes |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 8 | 3 |
| Spec score · AI Agent Observability Tools | 9.3 (#1) | 8.5 (#9) |
| Spec score · Llm Monitoring | 9.3 (#1) | 8.4 (#11) |
| Spec score · AI LLM Observability Tools | 9.3 (#1) | 8.5 (#8) |
| Integrations | The documentation describes more than 1,000 integrations through built-in connectors, MCP servers and Composio. | The home page advertises more than 56 integrations spanning LLMs, agent frameworks, vector databases and GPUs. |
| Licence | The public GitHub repository describes Agenta as open source under the MIT License. | The project is licensed under Apache License 2.0. |
| SDKs | The quick-start documentation provides a Python SDK installed with pip and JavaScript/TypeScript API examples. | Official SDKs are available for Python, TypeScript and Go; Python installs with pip and TypeScript with npm. |
| Self-hosting | Self-hosting uses Docker and Docker Compose, with an optional Kubernetes Helm deployment documented separately. | Docker Compose runs the UI on port 3000, OTLP receivers on ports 4317 and 4318, and ClickHouse for traces, metrics and logs; Kubernetes Helm deployment is also documented. |
| Support | The Hobby and Pro plans list community support through GitHub Issues, while Business lists priority support and a private Slack Connect channel. | The OSS plan includes community support on GitHub. |
| System requirements | The local setup requires Docker and Docker Compose; insufficient Docker memory can cause the web container to restart. | The local sandbox requires Docker and Docker Compose; Kubernetes users install the published Helm chart. |
| Tracing | Agenta records model and tool calls with token counts, latency, estimated costs, logs and errors. | LLM tracing can capture calls, tools, and retrievals, with filters for user, session, cost, latency, and metadata. |
| What it does | Agenta is a collaborative workspace for building AI agents and automations through chat, with cloud or self-hosted deployment. | OpenLIT is an OpenTelemetry-native platform for tracing, evaluating, guarding and improving AI agents and coding agents. |
Plans
Agenta
- HobbyFree
- Open sourceFree
- Pro$29 a month
- Business$299 a month
- EnterprisePriced on request
- Enterprise (Cloud)Priced on request
- Enterprise (self-hosted)Priced on request
- Enterprise self-hostedPriced on request
In their own words
Agenta
Agenta is an open-source workspace for teams building and automating AI coworkers. Teams can interact with agents in Slack or Telegram, start from templates for engineering, customer support, sales, company knowledge, and operations, and run them on a schedule or in response to events. Its observability tools include traces, logs, errors, version history, evaluations, and token usage with estimated model costs. Agenta connects with services such as Slack, Notion, GitHub, HubSpot, Google Drive, Linear, Zendesk, and Discord, and supports more than 1,000 integrations. Listed model providers include OpenAI, Anthropic, Gemini, Mistral, and others. Cloud Hobby is free and allows two team members and 5,000 runs monthly; runs stop at that limit. Pro costs $29 a month and includes 10,000 runs monthly, with extra runs priced at $5 per additional 10,000. Model-provider charges are separate. Self-hosting is available, with users operating the application, storage, runner, upgrades, and backups in their own infrastructure. A mobile app supports agent conversations, approvals, and workspace management.
OpenLIT
OpenLIT is an open-source platform for tracing and evaluating LLM activity, managing prompts, and tracking costs. Built on OpenTelemetry, it can capture model calls, tool use, and retrievals, with filters for user, session, cost, latency, and metadata. Evaluations can use an LLM judge, heuristics, or human review on production traffic or experiments. Prompt Hub provides versioning, dynamic variables, API retrieval, unlimited prompt fetching, and AI-assisted improvement. OpenGround supports side-by-side model comparisons for latency, tokens, and cost, including comparisons using a user’s own key. Coding agent monitoring covers sessions, costs, tokens, repository activity, and code impact. The site lists more than 56 integrations across LLMs, agent frameworks, vector databases, and GPUs. OpenLIT accepts OTLP data and can be self-hosted with Docker Compose or Kubernetes Helm. Its Apache 2.0 license and site description note that self-hosting keeps prompts, traces, and secrets in the user’s environment. The OSS plan costs nothing and includes unlimited self-hosted usage, users, projects, and environments.