How I Built an AI Native SRE Company Without Being the Engineer in the Room

How I Built an SRE Company Without Being the Engineer in the Room

Most AI startups don't fail because the model was bad. They fail because infrastructure couldn't keep up when it mattered most.

I'm Krati Gaur, Founder of Coneixedor Technologies. I've watched this pattern repeat across nearly every founding team conversation we have. Brilliant teams spend months building something incredible, only to watch it fall apart under production load at the worst possible moment: a demo to an enterprise buyer, a product launch, the week after a Series A closes.

The problem was never the product. It was always the infrastructure.

The Gap No One Was Filling

Before founding Coneixedor, the pattern kept surfacing in conversations close to me. The same story over and over. A DevOps engineer, usually the most overloaded person on the team, drowning in 3AM alerts. LLM costs spiraling from $5k to $50k a month with zero observability. And the usual options were broken:

Hiring a senior SRE takes 4 to 6 months and costs $250,000 to $300,000 a year.
Generic DevOps agencies hand you a Terraform template and disappear.
Cloud provider professional services move at enterprise speed while your runway burns

That's why I founded Coneixedor Technologies, to bring Google-grade SRE thinking to funded AI startups, seed through Series B.

A Different Kind of Infrastructure Partner

At Coneixedor, a Senior Partner leads every engagement. We don't hand off to junior engineers. We don't disappear after the build. We work with AI-native companies building AI SaaS, FinTech AI, and Healthcare AI, everything from production-ready cloud architecture to MLOps pipelines to managed SRE retainers.

One of our most meaningful early engagements was with BSEduworld. Their team had lost trust in their own deployment process. Engineers avoided Friday releases. The infrastructure wasn't broken, but the confidence was.

We didn't rebuild everything. We asked one question: what does a safe deployment actually look like for this product?

The result: 45% faster deployments, 60% lower infrastructure costs, and zero failures since go-live. But the metric that mattered most was cultural. As Ravi Mohan, Director at BSEduworld, told us: "We ship on Fridays now and nobody loses sleep over it."

The Lesson That Drives Everything

Infrastructure isn't just about servers and pipelines. It's about giving teams the confidence to move fast without fear.

I founded Coneixedor because I believe every AI startup deserves the kind of infrastructure reliability that used to be reserved for companies with Google-sized engineering teams. You shouldn't have to choose between building your product and keeping it running.

If your AI product is approaching production and you're not sure your infrastructure is ready, that's the conversation I want to have.

coneixedor.com/contact