— A note from Revoleap July 2026

Built for the work after the AI pilot.

A note from the founders — on why this firm exists, who is building it, and what we commit to.

Between us, we have spent the past two decades inside technology firms — building and selling them, co-founding and running cloud consultancies through to acquisition, and shipping AI engineering into production at the moments where the field was being figured out, not described. We have worked together for most of the last ten years, in the same room on the same firm — long enough to know what the others will say, short enough that we still argue about it.

From those seats, we watched the same conversation play out at hundreds of leadership tables. They had agreed AI was real. They were trying to figure out what to do about it. They had a Director of AI, a steering committee, two hundred pilots, three in production. They had a vendor's deck that ended with the words scale next quarter. Very little of it was compounding.

What was missing — almost everywhere — was a firm that would sit on the inside with them. Not run pilots. Not author roadmaps. Do the work that gets a system into production, then stay long enough for the system to compound. That firm exists in pieces — at the hyperscalers, at the frontier model providers, at the better consultancies, scattered across the alumni networks of all three. We started Revoleap to gather those pieces, and to do that work for a small portfolio of consequential firms each year.

We do five things — AI Engineering, Cloud Engineering, Data Engineering, App Engineering, and Platform Operations — and we do them as a single piece of work. The five practices are how we organise the firm internally. They are not how we organise the engagement. The engagement is one team, with a named partner accountable, end-to-end.

If you are at the moment in this letter — past "AI is real" and into "what now?" — we should talk.

Umesh Kumar CEO & Co-Founder
July 2026

For specifics, our work to date — Work →

The names below are the core team. There are practitioners around them — there have to be, for the work to ship — and the firm is built so that these partners stay close to the work, not distant from it. The bios are deliberately short. They are not the whole story. They are the part of the story you should not have to read on LinkedIn.

— 01 / 05 UMESH KUMAR CEO & Co-Founder

Runs the firm. Two decades in enterprise systems and cloud — NetApp through the storage years, Redington through India's largest technology distribution business, and Searce at the hyperscaler edge — before co-founding Cloudside and running its engineering from first contract through to acquisition, building the cloud practice from zero. Came up through systems, not slides. Culture is the only moat a services firm gets. It cannot be pasted in later.

— 02 / 05 JITENDER SINGH (Jitu) Head of Growth & Partnerships · Co-Founder

Owns growth and partnerships at Revoleap — the customer relationship from the first conversation to the long one years later. Built and ran the alliance, sales, and partnership function for India at Cloudside, trusted equally by the hyperscaler partner teams on one side and the CIOs writing the cheques on the other. Before that, eight years across enterprise technology sales and program management for a private-equity and angel-investor network whose job was making portfolio companies actually compound.

— 03 / 05 KARTHIK K Director of Engineering · Co-Founder

Owns delivery at Revoleap — the place where strategy survives contact with a real lakehouse, a real deadline, and a real risk committee — and files what worked into the playbook on Monday. Eight years in engineering: three in production software, five in data engineering and applied AI/ML at the moving edge of the field, including a run at Vue.ai, where retail computer vision was being figured out in production. Founding data engineer at Cloudside. Ran its data practice end-to-end through the acquisition.

— 04 / 05 HARSH GOENKA Platform Architect & Founding Team

Owns platform automation at Revoleap — the kind that makes manual work disappear — and points it straight at AI, using models to run the platform and building the AI systems clients put into production. Comes from four years architecting enterprise cloud at Cloudside, rising to Cloud Architect and leading the teams that kept mission-critical systems resilient. Always hunting the cleaner way to solve it.

— 05 / 05 AVI AGARWAL Platform Architect & Founding Team

Holds the platform layer for Revoleap's most demanding accounts — the enterprise systems that have to stay up under real load — and puts AI to work on it, from agents that watch and remediate to the applied-AI engagements where that platform carries real models in production. Cloud Architect at Cloudside before this, leading multi-cloud modernisation for global enterprises after a grounding in large-scale systems delivery at DXC Technology. Enterprise complexity, handled without drama.

The covenant.

These are the decisions we do not relitigate. Two columns — what the firm will do, and what it refuses to do — set down here so neither side has to ask later.

— We will

  1. 01Have a named partner accountable on every engagement — from first conversation through delivery.
  2. 02Refuse work where we are not the people who can do it.
  3. 03Publish what we learn — anonymised where the client requires, named where they do not.
  4. 04Keep at least one named partner in the room on every engagement of consequence — whatever the firm's size.
  5. 05Tell you when an idea is wrong — even when it is yours.
  6. 06Walk away from work that would corrode the firm's culture.

— We will not

  1. 01Sell pilots. We work on engagements — not POCs running in parallel with five other firms.
  2. 02Treat AI as a feature. We treat it as an operating principle.
  3. 03Hand off the spine of the engagement. We bring in specialists at the edges when the work calls for it — the accountable Revoleap partner stays on the job, end-to-end.
  4. 04Use one client's engagement to demo to the next.
  5. 05Bill for the hour in which you tell us we got it wrong.
  6. 06Take on more clients than the partners can actually stay close to.

Two centres.
One practice.

Engineering happens in two cities — built from places with complementary histories. One designed from first principles three centuries ago. The other a century-old workshop that has always preferred shipping to demonstrating. We choose the people, and inherit the temperaments of the places they come from.

— Headquarters & engineering hub 26.92° N · 75.82° E

Jaipur.

— Rajasthan, India. The pink city.

Three hundred years ago, Jaipur was designed on paper before a single stone was placed — one of the first cities in the world built to a deliberate plan. Hawa Mahal's 953 lattice windows are not ornament alone. They are an 18th-century passive cooling system disguised as a crown. We inherit that tradition: design it with intent, build it with precision.

— Office Mansarovar
— Engineering hub 11.01° N · 76.95° E

Coimbatore.

— Tamil Nadu, India. A city that builds.

For more than a century, Coimbatore has been where things get made — textiles, precision engineering, motors, software, and increasingly AI. It sits inside one of the densest concentrations of engineering talent on the subcontinent, anchored by institutes whose graduates have always preferred the workshop to the whiteboard. The tradition here is plain: shipped, not demonstrated.

— Office Kalapatti
— Also present in
Bengaluru
Client
Karnataka, India
Gurgaon
Client
NCR, India
Mumbai
Client
Maharashtra, India
Singapore
Regional
South-East Asia
Hong Kong
Regional
East Asia
— Where we sit, plotted

Seven cities,
one grid.

Two centres of build, five cities of conversation — and a working posture for anywhere else. These are the cities where we sit, not where we stop.

Gurgaon · Mumbai · Bengaluru CLIENT CITIES Jaipur Coimbatore Singapore Hong Kong — THE FIRM, PLOTTED ON ITS OWN GRID Principal Regional Client Everywhere else — we travel

The partners we build with.

Three layers underpin almost every production AI system we ship — the models that reason, the platforms they run on, and the data they learn from. We are technology-agnostic in posture, and opinionated about the partnerships that make production AI real.

Model providers
— the frontier of reasoning
Anthropic·OpenAI·Gemini
Anthropic OpenAI Google Gemini
Hyperscalers
— the cloud everything runs on
Google Cloud·Microsoft Azure
Google Cloud Microsoft Azure
Data platforms
— the lakes and warehouses
Databricks·Snowflake
Databricks Snowflake

— Selected for capability, not for marketing. The list grows as the work demands.

If you have read this far, we should probably talk. The way in is here.

— The leap is the strategy.