Orbit AI

Hello Product Hunt 👋

I’m excited to share Orbit, an AI observability tool built for teams running AI features in production.

Orbit started from a common problem we ran into while shipping AI-powered products:
vendor dashboards show usage by model or API key, but they don’t show how AI actually behaves inside a product.

Once AI is embedded across multiple features, it becomes difficult to answer practical questions like:

• Which product features are driving AI cost?

• Where does AI latency impact user experience?

• Which features are failing or degrading in production?

Why we built Orbit

Existing tooling focuses on providers and models, not on product features.
As a result, teams often lack feature-level visibility into AI cost, performance, and reliability.

Orbit was built to close that gap by capturing real runtime data from production and tying AI behavior directly to product features.

How Orbit works

SDK-based instrumentation
Capture AI metrics directly from application code — no proxies, traffic interception, or scraping.

Feature-level visibility
See cost, latency, error rates, and usage broken down by feature, environment, and model.

Real production data
All metrics are derived from actual runtime events, not estimates or sampling.

Free to get started
No credit card required.

Thanks for checking out Orbit.

Feature-level slicing is exactly what most teams are missing because “per model” doesn’t map to product decisions

interersting use case. grafana of ai agents basically