About
We build production AI systems and we are unusually willing to say when the thing you want should not exist. Both of those are commercial positions, not modesty.
What is Leverge?
Leverge is an AI engineering company founded in 2024, building production AI systems for companies in India, the United States and Europe. Delivery is led from Bengaluru with a US entity for contracting. We work on a fixed-price scoping model, hand over code in the client's own repository, and decline work where the process has no defined correct outcome — because there is nothing for a system to optimise toward.
How we work
Every engagement starts with a fixed-price scoping sprint, and the architecture, evaluation plan and estimate are yours whether or not you continue. A scope only one vendor can execute is not a scope, it is a lock-in mechanism.
We build the evaluation set from your real historical cases before writing system logic. Without it no change can be shown to be an improvement, which is the single most common reason AI projects decay after launch.
Code lands in your repository under your licence, behind a provider abstraction so any model can be swapped with a configuration change. There is no runtime dependency on us after handover.
A material share of our consulting engagements conclude that some proposed use cases should be dropped, or that a platform would serve better than a build. Clients consistently tell us that section saved more money than the recommendations did.
Scope
Published because it saves everyone a call. If your project is in this list, we will tell you on the first conversation rather than after a proposal.
Team
Principal AI Engineer
REPLACE with a real bio. Aditya leads agent architecture at Leverge and has spent the last four years moving LLM systems from notebooks into production, mostly in regulated environments where a wrong answer has consequences. He writes about evaluation, failure modes and the unglamorous parts of agent reliability.
Head of AI Delivery
REPLACE with a real bio. Meera runs delivery at Leverge, which mostly means deciding what not to build. She works with operations and compliance teams to scope AI systems that survive procurement, audit and the first month of real usage.
Where we are
Next Step
A 30-minute technical call with an engineer who has shipped this before — not a sales qualification round. You leave with a feasibility read, a rough shape for the build, and an honest answer about whether it is worth doing at all.