A practice built on depth rather than headcount
Kaundinya Labs LLC is an enterprise architecture and platform engineering practice registered in Michigan. It has two halves: advisory work for organisations, and software products built through our studio. It is deliberately small, and takes on a limited number of engagements at a time so the work stays deep rather than wide.
The name
The diya — an oil lamp — is the studio mark. It is a small, deliberate light: enough to work by, maintained by hand, and useful precisely because it is not trying to illuminate everything at once.
What we take on
Systems where the cost of getting it wrong lands on people who did not choose the system. Regulated environments, long-lived platforms, integration layers nobody currently owns, and infrastructure that quietly assumes everyone reads well, sees clearly, and has a good connection.
The studio
The studio is the product side of the practice. Seven products are in it: one live, three in build, two in alpha, one coming soon. They exist because advisory work keeps surfacing the same unmet needs, and at some point the honest response is to build the thing rather than recommend it.
How we price
Fixed scope, fixed fee, defined deliverables. If the scope changes we say so before the invoice does.
Founder
Siva has spent 36 years as an enterprise architect across financial services, healthcare, automotive, aerospace, retail, and software. His work spans platform engineering, observability and telemetry, cloud modernisation, connected ecosystems, and — most recently — AI-governed engineering. He founded Kaundinya Labs to put the advisory practice and the product studio under one roof.
The model is the commodity; the scarce work is shaping it. Scope, boundaries, outcome — in the user’s hands.
Four generations of computing
1989–1999
Building systems
Systems written from the ground up, where the constraint was the machine and the discipline came from how expensive it was to be wrong.
2000–2010
Connecting systems
Integration became the work. Systems built in isolation had to talk to each other, and the hard problems moved into the space between them.
2011–2020
Scaling systems
Cloud, distribution, and operating at volume. Reliability stopped being a property of a machine and became a property of a design.
2021–present
Augmenting human capability
AI-assisted engineering, where the model is available to everyone and the differentiator is the governance around it: scope, boundaries, and who holds the outcome.