Production context
for software factories
Hud runs alongside your app, continuously learning how your backend services behave in the real world. It gives you and your coding agents the context to automate the path from PR to production, reduce manual bottlenecks, and solve issues faster.
Agents know your code. They’ve never seen it run.
Coding agents plan, write and test a change in minutes, but they can’t see how the code behaves in production. So people review, deploy and watch every change by hand, and shipping it can take days.
Without Hud
The agent sees the code, never the traffic.
With Hud
Production context at every step.
Why Hud?
Production context from PR to fully deployed.
The same production context goes wherever your code changes: the PR before the merge, the rollout as the new version takes traffic, and the fix when something breaks.
See it in action
01 · PR
The diff shows what changed.
Hud shows what it will touch in production
The functions it touches, their traffic and their callers.
A risk rating: safe, requires review or not safe.
02 · ROLLOUT
The current deploy, checked
against the base version.
New kinds of exceptions flagged, even caught ones.
Rolled back through your CD, or after your approval.
03 · Fix
The agent that writes the fix
needs to see what happened.
Forensics already captured: call graph, request, exception.
Your coding agent gets them over MCP and opens the fix.
Hud counts every call to every function.
Traces only sample your service. Hud’s sensor runs in your backend services, so the data exists before anyone thinks to ask for it.
The Impact Map: a real-time map of how your code behaves in production.
On an error or a spike, captures forensics: call graph, request URI and parameters, exception and stack trace.
Runs in your pod. A PII scrubber removes 50+ sensitive keys, plus emails, tokens and card numbers.
Learns a baseline on a separate thread, with bounded buffers. Turns itself off on anomalies.
Keep your stack. Hud adds what it can’t see.
Your APM samples traces and alerts on the services you instrumented. Hud runs alongside it, with nothing to define and no sampling.
AI code reviewers read the diff. Hud adds what the diff can’t show: how the code it touches runs in production.
AI SREs start from the incident. Hud starts from the change, and catches the regression while it’s still rolling out.
Your coding agent knows the repo. Over MCP, it gets production context while it writes, and the forensics when it fixes.
Give your software factory production context.
See Hud in Action
Trusted by engineers.
Human & artificial alike.
Hud runs on millions of services across massive production environments, with negligible overhead.
“Hud eliminated our voodoo incidents. AI-powered root cause analysis turned days of drilling through tools into minutes.”
“Hud completely changed how early we detect, and how quickly we solve issues long before they impact the business.”
“AI helps us move faster only when it’s grounded in reality. Having accurate runtime context means our engineers, and our AI workflows, can reason about real production behavior and act on it safely.”
“We knew the crashes were caused by an ELU spike, but the question was what caused that spike. Using Hud, we found the answer in minutes with an AI-ready fix.”
“When engineering decisions are grounded in real execution data, it changes how confidently we ship, scale, and invest. That level of certainty directly supports the business as the platform continues to grow.”
