Oberhahn vs. Datadog
Datadog watches your whole cloud, with AI monitoring built in. Oberhahn is the organizational intelligence layer for AI, it shows how every person and agent actually works, attributes it in real time, and flags the unattended loops quietly running up the bill.
Both Oberhahn and Datadog can show you an AI number. Datadog is a general observability platform that monitors every service you run and now traces LLM calls alongside them. But when your token bill is climbing past $10k a month, agents are running unattended, and no one can say who or what is driving it, a line on a dashboard is not enough. Oberhahn is built for exactly that: a real-time, attributed picture of every person and agent using AI, with real-time attribution and an open layer you can build on. Here is how they compare.
and climbing, the point where AI spend hits a board line item
of AI usage is agent-driven and running unattended
to a live picture, no agents to roll out across hosts
| Feature | Oberhahn | Datadog |
|---|---|---|
| Coverage & reach | ||
| Coverage beyond instrumented apps & routed traffic | Yes | |
| Real-time | ||
| Streaming updates | Yes | |
| Security | ||
| Session-level tracing | Yes | |
| Audit logs | Yes | Yes |
| Context intelligence | ||
| Tracks repeated context | Yes | |
| Attribution | ||
| Per-person attribution, every tool, no manual tagging | Yes | |
| Agentic & autonomous work | ||
| Unattended vs. interactive classification | Yes | No |
| Real capacity incl. background agents | Yes | |
| 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: we report billed cash only, status means completion not quality, and interactive-vs-automated is a classification, not a judgment. There is no individual-hour surveillance and no capacity baseline unless you set one.
See how your people and agents actually work
This is Oberhahn's home turf: it maps AI activity across people, teams, projects, and tools in real time, the Floor, the Rhythm, the Organizational Map. You stop reading a number and start reading a live model of the org: which workflows spread, which agents run unattended, and where the next dollar goes.
Then let individuals prove their impact
Oberhahn is a tool people want to be seen inside, not a top-down finance report. Individuals show what they shipped with AI; managers spot their champions and their unattributed workflows. That is how adoption and attribution compound.
- Individuals surface the work they shipped with AI
- Managers find champions and unowned, high-value workflows
- Attribution rolls up to teams, projects, and reviews
And build on an open layer, not a black box
The strongest signal from platform teams is a question about the API. Oberhahn is built to be extended: send custom events, query your own data, and build your own views on top. You are not stuck inside someone else's dashboard.
- Send custom events from your own agents and pipelines
- Query the underlying data via API
- Build your own views; export everything, no lock-in
Choose Oberhahn if you
- Agents run unattended and no one can see or size the work
- AI spend is past $10k/mo and you cannot attribute it
- You need who-and-what is using AI, mapped in real time
- You want interactive vs. unattended usage classified out of the box
- You want an open, API-first layer to build on
Choose Datadog if you
- You already run Datadog for cloud observability
- You need full cloud spend: compute, storage, networking, and AI
- Cloud Cost Management already governs your cloud and AI spend
- Infrastructure monitoring is the primary job
- Datadog has LLM Observability, why do I need Oberhahn?
- Datadog's AI suite (LLM Observability, agent monitoring, AI cost management) watches AI as part of full-stack monitoring. Oberhahn is narrower and people-first: a live map of every person and agent, attribution that rolls up to teams and reviews, and out-of-the-box classification of interactive vs. unattended work. Many teams run both.
- Can Oberhahn see agents running unattended?
- Yes. Classifying interactive versus automated usage and surfacing background-agent activity is core to Oberhahn. It is the pain we resolve: unattended work no one can see or size.
- Is Oberhahn open and extensible?
- Yes. You can send custom events, query your data via API, and build your own views. It is an open layer you build on, not a closed dashboard, and you can export everything with no lock-in.
- Does switching require a migration?
- No. Oberhahn is a one-line setup with no per-host agents. Historical data stays in Datadog; Oberhahn starts collecting from the moment it is connected.
- Does Oberhahn replace infrastructure monitoring?
- No. Oberhahn is not a general observability platform. For servers, containers, and network monitoring, Datadog remains the right tool.
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