India
AI consulting in Bangalore
Bangalore has the densest concentration of global capability centres and funded scale-ups in India, and both buy differently from a traditional enterprise. GCC leadership needs evidence a parent will accept. Scale-ups need a product surface faster than their roadmap allows.
- Headquarters
- Chennai, Tamil Nadu, India
- Delivery
- Remote-first with onsite blocks in Bangalore for the sessions that require one room
Local context
What we see in Bangalore
- 01The GCC mandate to demonstrate AI capability to a parent creates a specific failure mode: a showcase with no operational owner. We refuse that engagement shape and say so early.
- 02Engineering-heavy organisations here often have strong build capability and weak decision rights, which means the missing artefact is a value map, not a developer.
- 03Platform sprawl is higher than average, so vendor portability and exit cost tend to be live commercial questions rather than theoretical ones.
Sectors we work with here
- Global capability centres
- Technology and SaaS
- Funded scale-ups
- Financial services technology
Regulatory design inputs
Engagements are designed against India's DPDP framework, the parent organisation's security and model-use policy where applicable, and cross-border data transfer terms.
Delivery model
How the work actually runs
Remote-first with onsite blocks in Bangalore for the sessions that require one room. Travel is at cost and stated in the proposal.
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.