The Enterprise Agent Build & Runtime for the work your business runs on
Open Source Agent Evals & Observability
Stage
Not given
Established
Founded
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Based in
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DE
Pricing model
freemium
freemium
Pricing
Free plan with 50 workflow executions per month and visual editor. Enterprise plan with custom pricing includes governance, dedicated VPC, and comprehensive support.
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Key features
Visual editor and AI copilot
No-code visual editor, exportable to Python
Code-first API built for total control
Real-time tracing of every LLM call, tool call, and memory read
RBAC and audit with immutable audit trails and Enterprise IAM
Human-in-the-loop approval gates and intervention during execution
Runtime hooks inject PII redaction and policy checks
Automated and human-guided training for continuous improvement
Multi-LLM testing for model swapping at runtime
GitHub integration
Hierarchical traces capture every LLM call, tool invocation, and retrieval step
LLM-as-a-judge, heuristic functions, or human review evaluations
Prompt management with one-click deployments and rollbacks
Playground to test prompts on real production inputs and compare models
Experiments with test cases and side-by-side comparison
Human annotation and collaborative human-in-the-loop workflows
Cost and latency monitoring with dashboards and alerts
REST APIs and Query SDK for data access
Langfuse Assistant to automate the AI engineering loop
What makes it different
Agentic use case generator powered by billions of agent runs
Intelligently guided by 700k agent workflow patterns
Control Plane sits in execution path ensuring every agent interaction is observable, compliant, and reversible
Every production run turns into training data to sharpen accuracy and save money
MIT licensed open source platform with no data lock-in
Enterprise scale architecture handling billions of monthly events
Works with any language and framework with no framework lock-in
Async by default so tracing never blocks your application