In mid 2025, we spent four months watching the same thing happen across different teams. A product manager would have a great idea for an AI agent. Engineers would get excited. Then, about two weeks in, the enthusiasm would quietly fade. Not because the idea was bad. Because building agents is genuinely hard in ways that aren’t obvious from the outside.

The hidden work before the real work

Before you can even test whether your agent idea works, you have to build infrastructure that has nothing to do with the agent itself. You need a way to manage conversation memory across sessions. You need to handle tool calls reliably, with retries and timeouts. You need observability so you can debug why an agent went wrong. You need to version your prompts. You need auth, rate limiting, and a deployment model.

By the time most teams finish that scaffolding, they’ve spent weeks and still haven’t written a single line of actual agent logic.

We saw this happen too many times

One team spent six weeks building an orchestration layer before their first agent went live. Another team rebuilt the same memory management code three times across different projects because there was no shared infrastructure. A solo developer gave up entirely because the setup overhead made iteration too slow to be worth it.

The problem wasn’t lack of skill. It was a missing layer of abstraction.

What Korelos is, and why it exists

Korelos is the infrastructure layer that lets you skip straight to the agent logic. You define your agent in plain English, connect your tools via our integrations library, and deploy with a single API call. Memory, retries, observability, versioning, all of it is handled for you.

We built it because we kept running into teams who had great agent ideas and were being blocked by plumbing. That felt like a solvable problem.

The best infrastructure is the kind you don’t have to think about. Korelos is our attempt at that for AI agents.

What’s next

We’re in early access right now, and the feedback has shaped almost everything about how the platform works today. If you’re building agents and spending more time on infrastructure than on the actual problem you’re solving, we’d love to show you what Korelos can do.