Latitude
Latitude is an open-source AI agent monitoring platform that traces agents in production, detects failures, and helps write evals for reliable AI products.
Last verified:
What is Latitude?
Latitude is an open‑source AI agent observability and prompt‑engineering platform that helps product teams detect, debug, and automatically improve LLM‑driven features in production. It ingests production traces from your AI agents, clusters failures into human‑interpretable issues, and uses those issues to generate ongoing evaluations so regressions are caught early. The tool is designed for engineers, product managers, and domain experts who want a reliability layer on top of their AI products, turning raw logs into structured issues with clear paths to fix.
Key features include production‑trace ingestion with rich filtering by model, user, and error type, as well as automatic failure clustering that groups similar failures into issues without manual rules or regex. Latitude surfaces these issues in a project dashboard, where each issue can be reviewed, annotated, and turned into a reusable evaluation dataset. It also supports golden datasets and human‑labeled signals, so teams can iteratively refine prompts and logic based on real‑world behavior.
The platform is optimized for teams building agent‑style workflows, such as chatbots, automated assistants, or complex reasoning pipelines, where failures are subtle (hallucination, wrong tool calls, context drift) rather than simple crashes. By linking production traces to evals and experiments, Latitude enables data‑driven prompt improvement and A/B testing, allowing teams to ship more reliable AI features and maintain them over time.
Latitude pricing
Pricing model: Freemium
Latitude offers a free tier that lets users ingest production traces, explore the traces view, and see basic issue clustering without certain limits in the early documentation; paid plans unlock higher trace volumes, more advanced monitoring, and enterprise features. The exact pricing grid is not fully disclosed on the main landing page but is gated behind a sign‑up or demo request, indicating that detailed pricing varies by workspace size, trace volume, and whether you choose the hosted SaaS version or self‑host the open‑source core. Enterprise plans include additional support, SLAs, and custom deployment options.
Latitude pros
- Tracks production traces of AI agents end to end
- Automatically clusters similar failures into issues
- Generates evals directly from real production failures
- Supports filtering traces by model, user, and error type
- Visualizes issues with counts and states such as pending review or escalating
- Enables fast setup with minimal configuration required
- Integrates with existing agent code via a lightweight SDK or skill
- Provides a project dashboard for overall issue health
- Supports human review and annotation of issues
- Creates reusable golden datasets from annotated failures
- Runs continuous evaluations against known failure modes
- Links issues back to specific production traces for debugging
- Identifies subtle failure patterns like hallucination or wrong tool calls
- Allows teams to iterate prompts based on real‑world data
- Scales to thousands of traces without manual regex rules
Latitude cons
- Still in active development and evolving rapidly
- Limited public documentation compared to some larger platforms
- Mainly focused on agent‑style workflows, not simple single‑turn prompts
- Requires some engineering work to integrate tracing into existing agents
- Pricing and feature differences between self‑hosted and hosted options are not fully transparent
- Fewer third‑party integrations listed compared to some competitors
- May be overkill for very small or experimental projects
- Support for non‑OpenAI or non‑standard providers can be constrained
Frequently asked questions about Latitude
What is Latitude?
Latitude is an open‑source AI agent observability and prompt‑engineering platform that helps product teams monitor, debug, and improve LLM‑powered features in production. It takes production traces from your agents, clusters failures into issues, and turns those issues into automated evaluations so teams can maintain reliability over time.
How does Latitude differ from regular logging?
Regular logging gives you raw events and payloads, while Latitude interprets those logs into human‑readable issues, such as hallucination or wrong tool calls, and surfaces them with metadata like frequency, user impact, and state. It also automatically generates evals from those issues so new traffic is continuously tested against known failure modes.
Do I need Latitude if my LLM app is working fine?
Even if your LLM app seems to work, subtle failures like context drift, hallucination, or incorrect tool usage can erode trust over time. Latitude helps catch those issues early, quantify their impact, and iterate on prompts or logic so problems are caught before they become widespread.
How is Latitude different from Langfuse or similar tools?
Latitude focuses specifically on agent‑style workflows and automatic failure clustering that turns raw traces into issues without manual rules. It also emphasizes issue‑driven evals and golden datasets derived from real production failures, whereas many other tools lean more toward general LLM observability or experiment tracking without the same issue‑centric workflow.
How quickly can I see my first production traces in Latitude?
The website states you can set up Latitude in your project and discover your first issues in less than five minutes once tracing is enabled in your agent code. After installing the SDK or skill, you start sending traces, and Latitude immediately begins processing them and surfacing issues.
What kinds of issues will Latitude help me catch?
Latitude is designed to surface issues like hallucination, loss of context, incorrect tool or API calls, wrong answers given with high confidence, and patterns of user frustration that show up across many traces. It groups these into named issues that you can track over time and turn into automated tests.
Why do I need Latitude if I already use OpenAI’s dashboard?
OpenAI’s dashboard gives you model‑level metrics and logs but doesn’t interpret them into product‑level issues or connect them to your specific agent behavior. Latitude layers on issue discovery, automatic eval generation, and project‑wide monitoring so you understand how your own features are failing and why.
Once I see issues, what happens next?
From the issue view, you can inspect the underlying traces, annotate good and bad examples, and turn those into a golden dataset. That dataset then backs an eval that runs against new traffic, letting you measure improvements and prevent regressions as you iterate prompts or code.
What agents or frameworks does Latitude support?
Latitude is built to integrate with custom AI agents via a lightweight SDK or skill, currently demonstrated with agents that can send traces to the platform. The examples emphasize general agent architectures that generate multi‑step reasoning, tool calls, and complex outputs rather than a narrow framework‑specific list.
Can I self‑host Latitude or is it SaaS only?
Latitude is open source at its core, so you can self‑host the observability and evaluation components if you want to run them on your own infrastructure. The company also offers a hosted SaaS version with additional tooling, support, and managed deployment options for teams that prefer not to manage their own instance.