India
AI consulting in India
We are headquartered in Chennai and work with enterprises across India, and with US organisations who want senior delivery in an Indian timezone. Location is usually hidden in this category. We state it, because delivery structure is a buying criterion and pretending otherwise wastes the first call.
- Headquarters
- Chennai, Tamil Nadu, India
- Delivery
- Senior-led, small teams
Local context
What we see in India
- 01Indian mid-market boards have moved from asking whether to adopt AI to asking what was actually delivered last quarter. The evidence gap, not the ambition gap, is the live problem.
- 02Most enterprises we meet already have three to six pilots running in different functions with no shared gate and no inventory of what data has left the boundary.
- 03Capability is rarely the constraint. Decision rights are. The pilot that stalls usually stalls between two functions, not inside one.
Sectors we work with here
- Banking, NBFCs, and financial services
- Manufacturing and industrial groups
- Healthcare providers and diagnostics networks
- Global capability centres serving international parents
Regulatory design inputs
Engagements in India are designed against the Digital Personal Data Protection framework, sector regulator expectations for regulated workloads including outsourcing and model governance obligations, and contractual data residency commitments where a global parent is involved.
Delivery model
How the work actually runs
Senior-led, small teams. Onsite for the sessions that need one room, which are the readiness scoring session, the decision-rights workshop, and the day 90 evidence review. Remote for the rest.
AI Strategy and Operating Model
AI Readiness Diagnostic
A scored assessment across leadership commitment, data usability, workflow clarity, and governance, with a named owner assigned to the weakest pillar
AI Strategy and Operating Model
AI Operating Model Design
Decision rights, governance cadence, funding model, and the choice between a central centre of excellence, federated pods, or both
AI Strategy and Operating Model
Fractional Chief AI Officer
Senior AI leadership on a defined monthly commitment, owning the loop rather than advising on it
AI Governance and Risk
AI Governance Framework
A standing governance discipline with approval, override, and escalation named per workflow, not per company
AI Software Development
Prototype Sprint
Two to three weeks from workflow to a working prototype on your own process language and sample data
AI Software Development
Custom AI Application Development
Production applications with authentication, data boundaries, audit trails, and an evaluation harness
Other locations
Where else we work
Next step
Start with a baseline, not a proposal
Take the NATIVE Audit in fifteen minutes, or book a scoping call and bring the pilots you already have running.