About
A department, not an agency
AI Digital Hub is the AI and infrastructure engineering department of Exinary Technologies Private Limited. One contracting entity, one accountable team, and no wall between the people who build the automation and the people who run the platform underneath it.
Why the department structure matters
Exinary Technologies Private Limited is the legal entity — it holds the certifications, signs the contracts and issues the invoices. AI Digital Hub is the engineering team inside it that does the AI, automation and infrastructure work.
That is not a branding exercise. It means when an AI project needs a deploy pipeline, a monitoring stack and someone on call, you do not procure a second vendor and mediate between them. The most common reason AI pilots never ship is that the model works and nobody owns everything around it.
What we actually do
Two things, deliberately together. We build AI automations and agents that complete real business processes — document workflows, support resolution, back-office reconciliation. And we build, migrate and run the infrastructure they depend on, from CI/CD through to 24x7 on-call.
Most engagements start with a two-week readiness audit, because the highest-value thing we can do early is tell you which of your candidate processes are worth automating and which are not.
Where we work
We are based in Bengaluru and work with clients across India, the Middle East, the UK and North America. Indian engagements are billed in INR; international ones in USD. We design around the DPDP Act 2023 by default and GDPR where it applies, and for workloads that cannot leave a jurisdiction we architect for in-region processing rather than hoping nobody asks.
How we are different from an AI consultancy
Most of them stop at the prototype and hand you a slide deck. We are measured on whether the thing is still running accurately in a year, because for most of our clients we are the ones running it. That changes what gets built: evaluation harnesses, cost instrumentation, audit trails and runbooks, rather than an impressive demo and an invoice.
What we believe
Opinions we will defend
Not values on a wall. These are positions that change what we build and occasionally cost us work.
Narrow and deep beats broad and shallow
One workflow automated completely, including the awkward 15% of cases, is worth more than five pilots that each handle the happy path. The second approach demos better and delivers nothing.
If you cannot measure it, you have not finished
Every AI system we build has an evaluation suite before it has a demo. Without a number, nobody can say whether a change helped, and nobody else can safely maintain it.
The unglamorous work is the work
Retrieval quality, cost per request, error handling, audit trails, on-call runbooks. The model is a commodity you rent. Everything that makes it survive real users is engineering.
Saying no is part of the job
Roughly a third of our audits conclude that AI is not the highest-return action. We put those findings first. An audit that only ever recommends work we sell is a sales document wearing an audit's clothes.
You should be able to leave
Code, infrastructure-as-code and documentation are yours from the first commit, deployed in your cloud account. Exit assistance is contractual. A managed service that is hard to leave is a hostage situation.
Build it and then live with it
The same team carries the pager for what it built. It is the only feedback loop that reliably produces engineers who design for 3am rather than for a demo.
How the team works
Structure you will notice
These are operational choices rather than aspirations — you will see the difference in your first week.
Engineers talk to clients directly
There is no account manager translating between you and the people doing the work. The engineer who builds your automation is the engineer in your kickoff call and on your review calls.
One accountable lead per engagement
A named delivery lead owns the outcome and the communication. Escalation goes to a person, not a queue, and their contact details are in your onboarding pack.
AI and platform engineers sit together
Deliberately not separate teams. The most common reason AI projects stall is that nobody owns the deploy, the pipeline or the on-call once the model works.
Small, senior, and staying that way
We would rather turn work down than staff it with people who need supervision. That caps how fast we grow, which we consider a feature.
- Bengaluru
- Where we are
- 12
- Services, one team
- 1 in 3
- Audits that recommend against AI
- 100%
- IP handed to the client
Working across India, Middle East, UK and North America
AI engineering and infrastructure ops together
Reported prominently rather than buried
Code, IaC and docs, in your cloud account
Let's find out what is actually automatable
Bring a process that annoys you. In 30 minutes we will tell you whether AI helps, what it would cost, and where it would fail — even if the answer is don't bother.
Or email [email protected] · we reply within 1 business day