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207 tools · 25 stacks

AI tools are all over the place. This is the full landscape — 207 tools across 17 categories, mapped and connected. Ready to narrow it down? Build your stack →

Team size

Budget

Use case

Stage

Cluster

Stack Layers
What are you building and how is it defined?
How do you write and ship code?
How does your AI think and act?
Which models and infrastructure power it?
How do you build, observe, and extend it?
These tools competes with
Traceloop
vs
Helicone

Choose Traceloop when…

  • •You want OpenTelemetry-native LLM observability
  • •Vendor-neutral tracing that plugs into your existing stack
  • •You need observability across many LLM providers

Choose Helicone when…

  • •You want one-line LLM observability setup
  • •Caching LLM responses to cut costs matters
  • •You're an early-stage startup optimizing quickly
Field
Traceloop
Helicone
Category
Prompt & Eval
LLM Infrastructure
Type
OSS
OSS
Free Tier
✓ Yes
✓ Yes
Plans
Cloud: Usage-based
Pro: Usage-based
Stars
⭐ 2,000
⭐ 2,500
Health
●75 — Active
●80 — Active
Trajectory
— not enough data
— not enough data
Synced
today
today

Traceloop

Open-source LLM observability using OpenTelemetry standards. Automatic instrumentation for LangChain, OpenAI, and other frameworks with zero code changes.

Helicone

Open-source LLM observability platform. One-line integration to log every LLM request, track costs, and debug slow or failing calls.

Traceloop Website ↗GitHub ↗
Helicone Website ↗GitHub ↗

Shared Connections (1)

Langfuse

Only Traceloop (1)

Helicone

Only Helicone (7)

LiteLLMLangSmithArize PhoenixOpenAI APIAnthropic APITraceloopLogfire
See full comparison in Explore →