Agent Readiness Diagnostic
A team with one stuck or expensive workflow and no clear build decision.
- Named workflow, control points, and data readiness
- ROI map and a build / no-build recommendation
- A build brief your team or ours can execute
Engagements
Work with us
Six ways in, sized to where you are: a single stuck workflow, an enterprise platform, or a full AI Centre of Excellence built, operated, and transferred to you. Every option ends in something running in production, not a deck.
Not sure which fits? Write two lines about the problem and we will point you at the smallest option that works.
01
Start small
One workflow, one owner, a direct path to production. The right entry if you are testing whether agents work for you.
Single Workflow Agent
An operations owner with a named queue: claims, KYC, ITSM, collections, or equivalent.
- One agent live in production, with human-in-the-loop
- Evaluations, runbooks, and audit trail
- An owner in your business, not a sandbox
02
Scale across the enterprise
Platform and compute foundations so the second, third, and tenth workflow are not greenfield projects.
Multi-Agent Platform
Enterprises past the first workflow that want the next ones to ship faster and safer.
- Shared tools, state, and evaluation harness
- Governance and failure modes designed in
- Two or more workflows running on one platform
AI Factory & Compute Platform
CIOs and platform heads facing GPU sizing, residency, and a growing inference bill.
- Model mix, serving topology, TCO, and DPDP residency
- LLMOps: serving, evals, observability, cost controls
- Hybrid inference chosen on unit economics, not vendor quota
03
Own the capability
For GCCs and enterprises building a lasting AI function, up to a full Build-Operate-Transfer CoE.
Managed AI Operations
Teams with live agents or platforms that need monitoring, evaluation, and change control.
- Production monitoring and evaluation cadence
- Change control and incident response
- Capacity planning each budget cycle
AI CoE: Build, Operate, Transfer
Global parents and GCC leaders standing up an India AI centre they will eventually run themselves.
- CoE blueprint: operating model, skills matrix, platform, governance
- We hire and run the pod: delivery, standards, and cadence
- Transfer on a scheduled date: people, platform, and playbooks move to you
- Optional fractional technical leadership after transfer
The full mandate
How Build-Operate-Transfer works
01
Build
A blueprint covering operating model, skills matrix, platform, and governance, then we hire the pod against it, from 8 to 30 people.
02
Operate
We run delivery, standards, and cadence until the agreed handover. The CoE ships production workflows during this phase, not after it.
03
Transfer
On a date agreed up front, people, platform, and playbooks move to you. Optional fractional technical leadership stays as a thin overlay.
Transfer is in the contract from day one. You are buying a capability with a handover date, not permanent dependence on our headcount.
Every engagement starts with one email.