IntelMesh builds a data-agnostic agent observability platform in weeks

The gap between automating a process and proving it paid off

IntelMesh is a consultancy that helps medium and large enterprises automate their business processes with agentic AI. They live in tools like UiPath and the rest of the RPA and workflow stack, cutting manual work and taking cost out of operations for their clients.

Across those engagements they kept hitting the same wall. The workflow tools could automate a process. The business intelligence tools could chart the data. But nothing sat in between to answer the question every executive actually asks: what did this automation do to our revenue?

They wanted to own that gap, so they came to us to build the product that fills it. There was one catch. IntelMesh had never built software of their own. No AWS account, no GitHub, no engineering team. Just a sharp idea and a deadline.

What we built

We built IntelMesh a platform that turns automated processes into revenue you can see. It ingests data from whatever source systems a client runs, applies IntelMesh's proprietary algorithms, and calculates revenue-driven metrics on top. The goal was observability, not another dashboard: a live view of what an automation is actually worth.

One data model for any input

The real differentiator is that the platform doesn't care what shape your data is. Inventory and stockouts, healthcare, advertising, it all flows through the same ingestion layer and the same flexible metric engine. A client sends their data as it already exists, and IntelMesh runs the same set of algorithms to produce revenue metrics tuned to their specific automations. That is what lets IntelMesh walk into any client and say "send us your data," then show value in days.

Revenue metrics, not vanity metrics

Take stockout reordering, one of the automations IntelMesh runs for warehouse clients. Most tools would show you how many products got reordered. IntelMesh pulls data from across the client's systems and shows the revenue at risk and the revenue lost shrinking over time as the reordering gets smarter. It turns an automation from a line item into a number the business actually cares about.

On-prem by design

IntelMesh is going after healthcare, banking, and other regulated industries, and they operate heavily in the EU, so data privacy and GDPR were not negotiable. We adapted our Blocks stack to drop every cloud-native dependency, so the entire product, microservices included, is fully containerized and runs on a client's own infrastructure. No managed services, no data leaving the client's environment.

Zero to production in five weeks

Here is the part that still surprises people. IntelMesh started with nothing, and we stood up their cloud, their repositories, and a production-grade platform in five weeks.

That pace is the whole point of how we build now. Blocks gave us the entire foundation on day one, and our Agent Teams let us reshape that foundation, all the way down to a cloud-free on-prem build, without the timeline blowing up. Work that used to take a team the better part of a year happened in a month.

Keeping it running

Now that IntelMesh is moving into production, Parakeet watches it. It monitors the deployed environment, triages what matters, and lands tested fixes on its own, so IntelMesh can keep selling and building instead of babysitting infrastructure they only just acquired.