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FOR ENTERPRISE // AI TRANSFORMATION

We build the AI, and train the people.

We tell you where AI pays before we build anything, put it inside the systems your teams already open, and train those teams to use it. No pilot left stranded at the demo.

Talk to an expert → See how the training runs ↓

TEAM OF 150+ · 16+ YEARS · ISO 9001:2015 · CMMI L5

CERTIFIED EXPERTS MICROSOFT · AWS · GOOGLE · ORACLE · SERVICENOW · SALESFORCE

  • Your cloud Models and pipelines run inside your own accounts
  • You own it Code, models and data land in your repositories
  • Evidence first Proved on your data before anything is integrated
  • Trained to run it Handover and training built into the engagement
  • No commission Not a reseller, so no tool we name earns us a fee
  • An honest no We say plainly where AI does not pay

THE TRANSFORMATION LEDGER

Five stages, in order.

Each stage ends in something you can check, and any stage can be the last one if the evidence says stop.

  1. 01 / ASSESS

    Where AI pays, and where it does not

    We look at the workflows your teams actually run, then say which ones AI improves enough to justify the work and which ones it does not. The list of things we talk clients out of is usually longer than the list we build.

    AI services ↗

  2. 02 / PROVE

    One workflow, on your own data

    The narrowest useful version, built against your real data rather than a sandbox, so what you get back is evidence instead of a demo. If it does not hold up here, it stops here and you have spent one stage finding out.

    See a build ↗

  3. 03 / INTEGRATE

    Into the systems you already run

    The model goes inside the tools your teams open every day, not beside them. Adoption that needs a new tab, a new login and a new habit is adoption that quietly does not happen.

    Digital transformation ↗

  4. 04 / OPERATE

    Accurate after launch, not just at launch

    Monitoring, evaluation, retraining and the machine learning operations underneath them. A model that was right in March is not automatically right in September, and nothing tells you it has drifted unless something is watching.

    MLOps ↗

  5. 05 / ENABLE

    Your teams run it without us

    Training, runbooks and handover built into the engagement rather than sold back to you afterwards. The exit is designed at the start, which is the point of the next section.

    The training rooms ↗

// STAGES AS WE RUN THEM, NOT A MATURITY MODEL

CORPORATE AI TRAINING // AI ENABLEMENT

Three rooms, three different conversations.

Corporate AI training that runs everyone through the same session is why most AI rollouts stall. A finance manager and a backend engineer need opposite things from the same tool.

  • Room 01 / 03

    Everyone in the business

    SALES // MARKETING // HR // FINANCE // OPERATIONS

    The tools your teams will open on Monday, applied to the work they already do: drafting, summarising, researching, cleaning up the data nobody wants to clean up. We teach the judgment alongside the prompts, including what to check before trusting an answer and what should never be pasted into a chat window in the first place.

  • Room 02 / 03

    Engineering and technical teams

    DEVELOPERS // DATA // PLATFORM

    AI-assisted development as a daily working habit, building with language models, retrieval over your own documents, and the evaluation discipline that stops a clever prototype turning into something nobody can maintain. Taught on the same patterns we ship for clients, which you can read in full in the case studies below.

  • Room 03 / 03

    Leadership and decision makers

    EXECUTIVE // FUNCTION HEADS

    Where AI pays, where it burns budget, how to read a vendor claim, which decisions stay with a human, and what has to be governed before a rollout rather than after an incident. Enough depth to challenge a proposal properly, including one of ours.

HOW THE AI TRAINING RUNS

  1. Workshops, a day or a few days

    On site or remote, one group at a time, built around your tools and your real work rather than a generic deck.

  2. A programme across several weeks

    Sessions spaced out with real work in between, because a skill practised once in a room decays before it reaches anyone's job.

  3. Embedded in a delivery project

    We train your team while building with them, on your own system. This is how the rest of our service pages already describe handover, and it is the format that sticks best.

// CURRICULUM IS BUILT AROUND YOUR TOOLS AND YOUR WORK, NOT A FIXED SYLLABUS

FROM THE FIELD

AI we have already shipped.

Three builds you can read in full, rather than a logo wall.

// LINKED IN FULL // READ THE ENGINEERING, NOT A SUMMARY

All AI services ↗

WHAT WE DO NOT CLAIM

The gaps, stated plainly.

An AI pitch is the easiest thing in this industry to inflate, so here is what this page is not telling you.

  • No guaranteed productivity percentage. Anyone quoting you a number before they have seen how your teams work is quoting it from somebody else's business.
  • No published training record yet. The training practice is new, so this page carries no cohort counts, no alumni numbers and no course certifications. What stands behind it is the delivery work linked above.
  • No proprietary model of our own. We build on the frontier models and tools you could license yourself, and we will say so when the cheapest option is also the right one.
  • We are not a reseller. Our engineers hold platform certifications, but we take no margin and no commission on any tool, model or cloud named on this page.

// IF ANY OF THIS CHANGES, THIS PAGE CHANGES WITH IT

FAQ // QUESTIONS

Before the first call.

Direct answers on scope, training, tooling and who owns what at the end.

What does enterprise AI transformation actually involve?

Five stages in order: assessing which of your workflows AI genuinely improves, proving one of them on your real data, integrating it into the systems your teams already use, operating it so it stays accurate after launch, and training your teams to run it without us. Any stage can be the last one if the evidence does not support going further.

Do you train non-technical staff, or only engineers?

Both, in separate rooms. One track is for everyone in the business, covering sales, marketing, HR, finance and operations. A second is for developers, data and platform teams. A third is for leadership and function heads. They are taught differently on purpose, because a finance manager and a backend engineer need opposite things from the same tool.

What corporate AI training formats do you offer?

Three. Workshops running a day or a few days, on site or remote. A programme spread across several weeks with real work between sessions. Or training embedded in a delivery project, where we teach your team while building with them on your own system. The embedded format is the one that sticks best.

Which AI tools do you train our teams on?

The ones you have already chosen or licensed. If you have not chosen yet, we help you evaluate them first. We are not a reseller and hold no vendor certification, so nothing we recommend earns us a commission, and the curriculum is built around your tools and your actual work rather than a fixed syllabus.

How do you decide where AI is worth applying?

We look at the workflows your teams actually run and measure where a model would change the outcome enough to justify building, operating and maintaining it. The honest result is often that some workflows are better served by ordinary software, and we say so at the assessment rather than after an invoice.

Who owns the code, the models and the data?

You do. Code, model artefacts, pipelines and data are delivered into your cloud and your repositories as the work proceeds. Documentation and handover are part of the engagement, so continuing with us is a choice rather than a dependency.

Can you train our team on a system you did not build?

Yes. Training does not require us to have written the system, only access to it and to the people who use it. Where the system is one we did not build, the assessment stage takes a little longer because we are learning your estate rather than recalling it.

How quickly will we see results?

The assessment produces a decision you can act on, and the prove stage produces a working result on your own data rather than a demo. We do not publish a fixed timeline on this page, because the honest answer depends on how many systems the workflow touches and how quickly we can get access to them.

THE REVIEW SHEET // 8 FACTS

Answered before the questionnaire.

What security, legal and procurement ask for once the business side is convinced. The same commitments as the rest of this page, in the form a vendor review needs them.

Who you contract with
JABASU, Inc., Santa Clara, California. The work is delivered from the group's development centre in Bhubaneswar, India.
CONTRACTING ENTITY
Where the work runs
Inside your own cloud accounts and tenancy. Models, pipelines and the data they touch stay in the environment your security team already governs, rather than moving to one of ours.
YOUR CLOUD, YOUR KEYS
What you keep
Code, model artefacts, pipelines and documentation land in your repositories as the work proceeds, not in a handover at the end.
YOURS FROM THE FIRST COMMIT
What happens to your data
It is used for your engagement and nothing else. We hold no proprietary model, so there is nothing of ours your data could be trained into.
NO MODEL OF OURS TO FEED
Independent certification
ISO/IEC 27001:2022 for information security, ISO/IEC 20000-1:2018 for service management, ISO 9001:2015 for quality, and a CMMI Level 5 appraisal. Issued to NetTantra Technologies (India) Private Limited, the delivery entity.
CERTIFICATE SCANS PUBLISHED
Who does the work
A team of 150+, employed rather than subcontracted out, so the people in your reviews are the people writing the code.
EMPLOYED, NOT BROKERED
Which models and tools
The frontier models and platforms you could license directly. Where your organisation has already standardised on one, we build on that rather than argue you off it.
NO COMMISSION EITHER WAY
How it ends
Runbooks, documentation and the training above sit inside the engagement rather than being sold back to you, so continuing with us stays a choice rather than a dependency.
EXIT DESIGNED AT THE START

// EVERY ROW NAMES WHERE IT IS BACKED, NOT JUST THAT IT IS TRUE

See the certificates ↗

Tell us what your teams do all day. We will tell you where AI helps.

If the honest answer is that AI does not help much in your case, you will hear it on the first call rather than three months into an engagement.

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