87%
faster time to root cause, 2x accuracy vs. the alternative they evaluated
“We pull fewer engineers into war rooms, on-call is materially better.”
Shahrooz AnsariSr. Director of Engineering
Put agents on your on-call rotation and your incident investigations
Handing on-call and incidents to agents takes more than models and MCP connectors. The rest is architecture.
4 common ways DIY builds break
Where in-house AI for production breaks down
AI gives confident, wrong answers
The hypothesis comes back well-formatted, cites real logs, and reads as authoritative, but the actual cause was three services upstream. Models optimize for a coherent answer, and coherent and correct drift apart under pressure.
A team of AI agents for production
Costs add up quickly and compound over time
Two kinds of cost, both to build it and to keep it running.
Engineering
Building this takes a rare mix of AI and systems engineers, roughly 10-15 of them over about two years to reach parity. Then it never really ends: every model release reworks the orchestration, evals need an owner, and someone stays on-call for the AI itself. A standing team, not a one-time build.
Systems
A frontier model on every task at production volume, with agents querying massive logs. Model and token costs climb with every investigation, and today's subsidized pricing turns into real invoices as volume grows.
Maintenance costs
Per-investigation cost stays flat from ten a week to thousands, because the architecture routes each step to the right model and retrieves only what the hypothesis needs. Put in your own numbers with the TCO calculator.
What teams see in production
75%
faster incident investigation, at 150K alerts a month
“I don't need more numbers or more data. What I need is a root cause.”
Chris UmbelAIOps Lead & SRE
72%
faster to accurate root cause than their own teams — root cause in under 10 minutes
“It surfaced accurate root causes 72% faster than our teams, integrating cleanly into our existing stack.”
Angelo MarlettaStaff Software Engineer
More on AI for production
Calculator
Calculator
TCO calculator
Put in your own numbers and see what it would cost to build and run this in-house.
Ebook
Ebook
Build vs buy ebook
The full build-vs-buy decision, piece by piece.
Blog
Blog
Blog
The six pillars an agentic harness needs to run production investigations.
Webinar
Webinar
Build vs buy webinar
Resolve AI's Dave Lawson and Ed Li walk through the build-vs-buy decision, the five pieces you need, and the cost of running each stage in-house. On demand.
Talk to a Resolve AI engineer
We'll talk through what you're building, what it takes to reach real root cause at your scale, and where Resolve AI fits.
Book a demo
