Oberhahn vs. LangSmith
LangSmith helps engineers debug and evaluate the apps they instrument. Oberhahn gives the whole organization real-time visibility into all AI usage, spend, and individual impact.
LangSmith is built for the developer loop: trace a chain, evaluate prompts, and improve an LLM application before and after it ships. Oberhahn operates at the organizational layer, real-time spend and per-person attribution across every team and provider. Here is how they compare.
and climbing, usage now spans far more than the one app you instrumented
of AI usage runs agent-driven and unattended
using AI, not just the app your developers trace
| Feature | Oberhahn | LangSmith |
|---|---|---|
| Coverage & reach | ||
| Coverage beyond instrumented apps & routed traffic | Yes | |
| Real-time | ||
| Streaming updates | Yes | Yes |
| Security | ||
| Session-level tracing | Yes | Yes |
| Audit logs | Yes | |
| Context intelligence | ||
| Tracks repeated context | Yes | |
| Cache & efficiency insight | Yes | |
| Attribution | ||
| Per-person attribution, every tool, no manual tagging | Yes | |
| Per-team & per-model attribution | Yes | |
| Agentic & autonomous work | ||
| Autonomous & background agent visibility | Yes | |
| Unattended vs. interactive classification | Yes | No |
| Real capacity incl. background agents | Yes | No |
| Runaway-agent loop detection | Yes | |
| Key-person / concentration risk | Yes | No |
| Open & extensible | ||
| Full export, no lock-in (JSON/CSV) | Yes | |
Straight talk for engineers: Oberhahn reports billed cash only, status means completion not quality, and interactive-vs-automated is a classification, not a judgment. No individual-hour surveillance, and no capacity baseline unless you set one.
From one app's traces to the whole org
LangSmith is where a developer debugs and evaluates a specific application. Oberhahn is where a leader sees the whole company: the Floor, the Rhythm, and the Organizational Map render a live model of which people, teams, and agents use AI across every provider and tool, not the calls inside a single instrumented codebase.
Then let individuals prove their impact
Traces belong to an app; impact belongs to people. Oberhahn attributes AI usage to individuals and teams, so people surface what they shipped and managers find champions and unowned workflows, the layer LangSmith's developer loop was never meant to cover.
- Individuals surface the work they shipped with AI
- Managers find champions and unowned, high-value workflows
- Attribution rolls up to teams, projects, reviews, and OKRs
And build on an open layer, not a black box
LangSmith is open to developers via its SDK and OpenTelemetry. Oberhahn is open at the org layer: send custom events from any agent or pipeline, query your data via API, and build your own attribution views, with no lock-in.
- Framework-agnostic, works with any SDK or agent stack
- Send custom events and query your data via API
- Build your own views; export everything, no lock-in
Choose Oberhahn if you
- Agents run unattended across teams and no one can size the work
- You want org-wide AI visibility, not one app's traces
- You want interactive vs. unattended usage classified out of the box
- Individual and team attribution roll up to reviews and OKRs
- AI usage spans many teams, providers, and tools
Choose LangSmith if you
- You are building and debugging a specific LLM app
- You want the tightest first-party fit with LangChain/LangGraph
- Prompt evaluation and dataset testing are the priority
- The developer inner loop is the main use case
- Do Oberhahn and LangSmith overlap?
- Lightly. LangSmith is for developing and evaluating an app; Oberhahn is for organization-wide usage, spend, and attribution. Teams often use both.
- Does Oberhahn require LangChain?
- No. Oberhahn is framework-agnostic and works across providers and SDKs. (LangSmith is also framework-agnostic via OpenTelemetry.)
- Can Oberhahn evaluate prompt quality?
- Oberhahn focuses on usage, cost, and attribution rather than prompt/response evaluation. For eval loops, LangSmith is purpose-built.
Compare it live
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