Braintrust vs OpenLIT
Braintrust
braintrust.devOpenLIT
openlit.ioSide by side
| Figure | Braintrust | OpenLIT |
|---|---|---|
| Price from | $249/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 4 | 3 |
| Spec score · Model Monitoring Software | 9.2 (#2) | 8.4 (#13) |
| Spec score · AI LLM Observability Tools | 9.2 (#2) | 8.5 (#8) |
| Spec score · AI Agent Observability Tools | 9.1 (#3) | 8.5 (#9) |
| Spec score · LLM Observability Tools | 9.2 (#3) | 8.5 (#10) |
| Spec score · Llm Monitoring | 9.0 (#4) | 8.4 (#11) |
| Company size | LinkedIn lists Braintrust as a privately held software-development company with 51–200 employees. | Crunchbase lists the company size as 1–10 employees. |
| Deployment | Braintrust offers SaaS, bring-your-own-cloud and self-hosted deployment models. | The platform can be self-hosted using Docker Compose or Kubernetes Helm and accepts OpenTelemetry data through OTLP. |
| Documentation depth | The documentation is organized into guides, integrations, SDKs, API reference, cookbook, troubleshooting, changelog and administration sections. | The documentation includes provider-specific SDK guides, observability pages, controller deployment material, CLI configuration and an indexed documentation file. |
| Evaluations | Teams can run experiments against datasets and score outputs with language models, code or human reviewers. | OpenLIT includes built-in evaluations, programmatic evaluations and LLM-as-a-judge workflows that can run locally or in CI. |
| Integrations | Braintrust describes its product as framework agnostic and lists native SDKs for Python, TypeScript, Go, Ruby, C#, and more. | The home page advertises more than 56 integrations spanning LLMs, agent frameworks, vector databases and GPUs. |
| Public API | The REST API manages projects, experiments, datasets, traces, prompts, tools, scorers, access controls and results; its OpenAPI specification is published on GitHub. | The sandbox exposes an OpenAPI description and API-key scopes covering ingestion, telemetry, prompts, vault, evaluations, chat, controller and database configuration. |
| Rating on G2 | 4.3 out of 5 from 58 reviews | 5.0 out of 5 from 1 review. |
| Support | The pricing page lists community support, priority support, and shared Slack channel support across its plans. | The OSS plan includes community support on GitHub. |
| Tracing | The platform lets users inspect agent traces and tool calls and track latency, cost, and quality in real time. | LLM tracing can capture calls, tools, and retrievals, with filters for user, session, cost, latency, and metadata. |
| What it does | Braintrust is an observability and evaluation platform for instrumenting, understanding and improving AI agents in production. | OpenLIT is an OpenTelemetry-native platform for tracing, evaluating, guarding and improving AI agents and coding agents. |
Plans
In their own words
Braintrust
Braintrust is an observability platform for teams running AI agents in production. It lets teams inspect agent traces and tool calls while tracking latency, cost, and quality in real time. Users can evaluate datasets, compare prompts and models, and score outputs with LLMs, code, or human reviewers. Discovery tools surface patterns in production traces to help investigate agent behavior, and the Loop agent can run evaluations, generate test cases, and iterate on prompts autonomously. Braintrust lists native SDKs for Python, TypeScript, Go, Ruby, C#, and more, and its MCP server lets coding agents query logs, run evaluations, and update prompts from an IDE. Security options listed include SSO, RBAC, and hybrid deployment; Braintrust states that it is SOC 2 Type II certified and GDPR and HIPAA compliant. Starter is free, with 1 GB processed data, 10,000 scores, and 14-day retention. Pro costs $249.00 per month; Enterprise pricing is custom.
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.