Founder-led · Not a team of contractors
About AdaptiveMind
AdaptiveMind is a founder-led AI engineering studio built by Meharban Singh, an engineer whose background is in heavy-machinery R&D and enterprise engineering workflows. That background now informs how AdaptiveMind designs AI software: explicit requirements, tolerance for real-world complexity, independent verification, and honest release status.
There is no account team, no bench of contractors, and no layer between the person who scopes the work and the person who delivers it. When you talk to AdaptiveMind, you are talking to the person building the system.
Photo pending
A founder photo will go here once one is supplied. No stock imagery is used on this site.
Before the studio
A design engineer in heavy-machinery R&D.
Driveline systems for agricultural and heavy machinery — the mechanical chain that connects engine torque to the wheels that move earth. Real systems there have hundreds of configurations and zero tolerance for ambiguity.
Bills of Material
183+ configurations
Managed BOMs for driveline systems across 183+ configurations — the mechanical chain that connects engine torque to the wheels that move earth.
Change management
Teamcenter PLM
Built engineering change workflows inside Teamcenter PLM: how a part revision travels from an engineer's desk, through manufacturing, to the shop floor.
Traceability
106 configs · 71 codes
Designed a punch-code traceability system tagging every driveline assembly with a unique identity — 106 configurations, 71 unique codes, readable by machines and humans.
Tolerance optimisation
70% → 91%
Optimised tire-slip tolerances across the BOM landscape, pushing acceptable configurations from 70% to 91%.
Manufacturing changes
Bulk Effectivity utility
Designed the Bulk Effectivity utility so manufacturing engineering could apply date-driven changes without creating phantom revisions.
That work is not named to a specific employer here — it is the method, not the letterhead, that carries forward into how AdaptiveMind builds software.
What carried over
Four habits from the shop floor.
Driveline engineering taught a specific lesson: if your architecture breaks past three configurations, it was never architecture. The same discipline now shapes how software gets built at AdaptiveMind.
Explicit requirements
A gearbox doesn't get built from a wish list. Every AdaptiveMind engagement starts with a written blueprint — capabilities, constraints, and an explicit out-of-scope list — before implementation begins.
Tolerance for real-world complexity
Real systems have hundreds of configurations, not three. Software built to survive only the demo path is the same failure mode as a BOM that only survives the sample run.
Independent verification
A change to a driveline part doesn't ship on the say-so of the person who drew it. The same separation — the author doesn't certify their own work — carries into how AdaptiveMind reviews before release.
Honest release status
A part revision is either released or it isn't; there's no in-between status that quietly means 'mostly.' AdaptiveMind labels every system delivered, live preview, validated, piloted, or internal — never all as finished.
Also building
Meharban built the Autonomous Factory — the multi-LLM delivery pipeline behind every system on the work page — and continues io-gita’s semantic-gravity research as an active, ongoing project.