Cupertino, California

Observability was never meant to work against you.

Kloudfuse unifies every signal into one data lake, runs it inside your own cloud, and puts AI to work where it matters most: keeping production up. One platform. Your environment. No compromises.

See the platformSee open roles
Why we built it

The stack was fragmented. The bill wasn’t.

Teams were paying for five tools that didn’t talk to each other, sampling away the data they needed most, and shipping every byte of their telemetry to someone else’s cloud to do it.

We started Kloudfuse to end that trade-off. One platform brings every signal together in a single observability data lake, so a metric, a log line and a trace are correlated by design rather than stitched together after an incident. It’s built to be efficient and built to scale to as much data as you can put in front of it.

It runs inside your own environment through a Self-SaaS deployment, which means full visibility without handing your production telemetry to a third party. And we treat AI and ML as a force multiplier for the people on call, not a line on a slide. Precision over hype.

What we believe
Observability should never ask you to choose between visibility, control and cost. The best platform stays out of your way until the moment you need it, then shows up with everything in one place.

Three principles that guide how we work.

How we build, how we make trade-offs, and how we treat the customers who let us run inside their infrastructure.

Customer first.

Customer impact is our clearest guide. We make trade-offs with their reliability, security and long-term success in mind, and more than once that has meant not shipping something we wanted to. Customers deploy Kloudfuse inside their own cloud, and we treat that access as earned, never taken for granted.

Build the right thing.

We take on the hard problems, especially when the answer isn’t obvious. We build for the long term without waiting for perfect, then ship, learn and improve. Precision over hype: we use AI where it makes engineers meaningfully more effective.

Act like an owner.

We take ownership from the first engineering decision all the way to the customer, and we stand behind what we ship. This is the kind of problem most engineers never get to work on, and we treat it that way.

Built by people who have run this at scale before.

Two decades of distributed systems between them, most of it spent operating the thing rather than diagramming it.

Pankaj Thakkar

Pankaj Thakkar

Co-founder & CEO

Previously Principal Engineer at VMware, where he worked on the network virtualization platform that became NSX — first at Nicira, then through the VMware acquisition. Deep roots in distributed systems and the operational reality of running infrastructure at scale.

Ashish Hanwadikar

Ashish Hanwadikar

Co-founder & CTO

Previously Principal Engineer at Cisco on the HyperFlex product line, via the Springpath acquisition, and Staff Engineer at VMware on vCenter Server. Two decades building large-scale distributed systems and cloud-native infrastructure.

Founded
2020
Headquartered
Cupertino, CA
Teams in
U.S. & India

Backed for the long build.

Investors who understand infrastructure and stay patient through the hard parts of building it right.

Aspenwood Ventures

Series A

Blumberg Capital

Series A

Highsage Ventures

Series A

We’re building the observability platform we always wished existed.

If hard, useful infrastructure problems are the kind of work you want to do, we should talk. And if you’re evaluating observability, put us to the test in your own environment.

See open rolesRequest a demo