{
  "schema_version": "openagent.resource.v1",
  "id": "res_openlit",
  "slug": "openlit",
  "status": "published",
  "identity": {
    "name": "OpenLIT",
    "one_liner": "OpenTelemetry-native open-source AI engineering platform for LLM observability, evaluations, guardrails, prompts, and GPU monitoring.",
    "short_description": "OpenLIT is an open-source AI engineering platform for observability, evaluations, guardrails, prompt management, vault workflows, playgrounds, and GPU monitoring. It integrates with many LLM providers, vector databases, and agent frameworks."
  },
  "classification": {
    "resource_type": "tool",
    "primary_category": "tools",
    "subcategories": [
      "automation",
      "workflow",
      "observability",
      "evaluation",
      "guardrails"
    ]
  },
  "positioning": {
    "why_it_matters": "Production agents need traces, metrics, evaluations, guardrails, and operational visibility. OpenLIT brings those layers into an OpenTelemetry-native toolchain.",
    "best_for": [
      "Teams operating production LLM and agent applications",
      "Developers who want OpenTelemetry-native AI observability",
      "Builders comparing evaluation and guardrail platforms"
    ],
    "not_for": [
      "Solo prototypes that only need a small prompt test file",
      "Teams looking for a low-level agent framework"
    ],
    "use_cases": [
      "self-hosted-ai"
    ],
    "target_audience": [
      "developer",
      "agent_builder"
    ],
    "maturity": "active"
  },
  "decision_signals": {
    "deployment_modes": [
      "self_hosted",
      "cloud"
    ],
    "open_source": true,
    "local_first": false,
    "self_hostable": false,
    "has_api": false,
    "has_gui": false,
    "supports_mcp": false,
    "supports_docker": false
  },
  "facts": {
    "license": "Apache-2.0",
    "pricing_model": "open_source",
    "github_stars": 2516,
    "github_forks": 293,
    "github_repo_full_name": "openlit/openlit",
    "last_verified_at": "2026-06-10"
  },
  "capabilities": {
    "core_capabilities": [
      "automation",
      "workflow"
    ],
    "interfaces": [
      "repo",
      "docs"
    ]
  },
  "links": {
    "primary_url": "https://github.com/openlit/openlit",
    "items": [
      {
        "type": "github",
        "label": "GitHub",
        "url": "https://github.com/openlit/openlit"
      },
      {
        "type": "homepage",
        "label": "Homepage",
        "url": "https://docs.openlit.io"
      }
    ]
  },
  "media": {
    "thumbnail_url": "https://github.com/openlit.png",
    "og_image_url": "https://github.com/openlit.png",
    "thumbnail_brief": {
      "resource_type": "tool",
      "visual_motif": "clean utility panel and geometric control surface",
      "background_style": "minimal editorial surface with restrained open-source accent color",
      "title_overlay": "OpenLIT",
      "subtitle": "OpenTelemetry-native open-source AI engineering platform for LLM observability, evaluations, guardrails, prompts, and GPU monitoring.",
      "avoid": [
        "noisy poster layout",
        "large marketing slogans",
        "random gradient blobs"
      ]
    }
  },
  "tags": {
    "category": [
      "tool",
      "open-source"
    ],
    "capability": [
      "automation",
      "workflow"
    ],
    "constraint": [
      "open-source"
    ],
    "scenario": [
      "self-hosted-ai"
    ]
  },
  "relationships": {},
  "machine_readable": {
    "canonical_url": "https://www.openagent.bot/tools/openlit",
    "json_url": "https://www.openagent.bot/tools/openlit.json",
    "markdown_url": "https://www.openagent.bot/tools/openlit.md"
  },
  "seo": {
    "title": "OpenLIT: Open-Source AI Observability and Evaluation Platform",
    "description": "OpenLIT is an OpenTelemetry-native open-source AI engineering platform for LLM observability, evaluations, guardrails, and prompt management."
  },
  "editorial": {
    "trust_note": "Verified from source links and project metadata.",
    "core_strengths": [
      {
        "title": "OpenTelemetry-native observability",
        "description": "OpenLIT focuses on AI observability through OpenTelemetry-native tracing and monitoring.",
        "why_it_matters": "Teams can connect agent behavior to existing observability systems instead of creating isolated AI dashboards."
      },
      {
        "title": "Evaluation and guardrails",
        "description": "The platform includes evaluations and guardrail workflows.",
        "why_it_matters": "Operational visibility is stronger when paired with repeatable quality and safety checks."
      },
      {
        "title": "Broad integration surface",
        "description": "OpenLIT describes integrations across LLM providers, vector databases, agent frameworks, and GPUs.",
        "why_it_matters": "Agent stacks are heterogeneous, so observability tools need broad coverage."
      }
    ],
    "use_case_notes": [
      {
        "title": "Agent tracing",
        "description": "Trace model calls, tools, latency, and failures across production agent workflows."
      },
      {
        "title": "Evaluation monitoring",
        "description": "Connect evaluations and guardrails to ongoing LLM application operations."
      },
      {
        "title": "AI platform operations",
        "description": "Monitor provider usage, GPU behavior, and prompt workflows in one engineering platform."
      }
    ],
    "compare_notes": [
      {
        "title": "When to choose OpenLIT",
        "summary": "Compare it with nearby tools by looking at hosting model, integration surface, license, and whether the official docs show the workflow you need."
      }
    ],
    "getting_started": [
      {
        "label": "Open the GitHub repository",
        "url": "https://github.com/openlit/openlit",
        "type": "github"
      },
      {
        "label": "Read the documentation",
        "url": "https://docs.openlit.io",
        "type": "docs"
      }
    ],
    "seo_article": {
      "intro": "OpenLIT is an open-source AI engineering platform for observability, evaluations, guardrails, and prompt workflows.",
      "what_it_is": "It is a tool layer around LLM and agent applications, not an agent framework.",
      "why_it_matters": "Teams need to see what agents are doing in production and catch regressions before users do.",
      "how_it_works": "Start by instrumenting one agent workflow, then add evaluation and guardrail checks around the highest-risk steps.",
      "faq": [
        {
          "question": "Is OpenLIT open source?",
          "answer": "Yes. The GitHub repository is listed under the Apache-2.0 license."
        },
        {
          "question": "How does OpenLIT fit with MLflow or Langfuse?",
          "answer": "OpenLIT is especially interesting for teams that want OpenTelemetry-native observability and operational monitoring around LLM and agent systems."
        }
      ]
    }
  },
  "timestamps": {
    "created_at": "2026-06-10T00:00:00.000Z",
    "updated_at": "2026-06-10T00:00:00.000Z",
    "published_at": "2026-06-10T00:00:00.000Z"
  }
}