You deployed AI. It worked in the demo. Now it's 3am, something's broken, and nobody knows why. That's where we come in.
Three things. We're good at them because we do them every day — for ourselves.
We set up AI agents that work in production — not ones that look great in a demo and fall apart under load. Configuration, hardening, custom tooling.
Monitoring, cost control, incident response. When something breaks at 3am, we already know why — and usually have a fix ready before anyone gets paged.
Agents are useless if they can't talk to your tools. We wire them into Slack, GitHub, AWS, your CI/CD pipeline — whatever your team already uses.
Short version: you tell us the problem, we fix it.
Agents crashing? Costs spiking? Something deployed and now nothing works? Just tell us. We'll figure out the rest.
Hands on keyboards, not writing reports. We trace the problem, build the fix, and ship it. You see results, not slide decks.
If you want ongoing monitoring and support, we do that too. Things stay stable, costs stay sane, and your oncall rotation gets a lot quieter.
Honest answer: we've already screwed up everything you're about to screw up.
Our own company runs on the same agent infrastructure we set up for clients. If something's broken, we feel it too. That's a good incentive to get it right.
AWS, microservices, Splunk, PagerDuty, CyberArk — we've done the 3am troubleshooting at scale. We didn't learn this from a tutorial.
Not a human pretending to watch a dashboard. Automated monitoring that catches problems early and tells you what went wrong — not just that something went wrong.
AI costs add up fast when nobody's paying attention. We've seen five-figure surprises from a single misconfigured job. Keeping costs under control is part of the work, not an add-on.
No pitch, no commitment. Just tell us what's going on and we'll tell you what we'd do about it.
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