Generative AI Development Services | ONAQO
SERVICE 03 · BUILD

GENERATIVE AI THAT
CITES ITS SOURCES.

Assistants, document pipelines and extraction systems grounded in your own permissioned content — with an evaluation set, a citation trail and a measured cost per request before anything reaches a user.

AT A GLANCE Typical first deploy — 8 to 14 weeks Works with — hosted or open-weight models Deployment — cloud, private cloud or on-premise Pairs with — Data Intelligence, AI Product & UX
THE PROBLEM

A demo is not a system.

Two weeks of prompt engineering produces something impressive in a meeting. Then it meets a thousand real users and the gaps show: answers with no source, confident output on questions outside its competence, no way to tell whether last week's change made it better or worse, and an invoice nobody forecast.

The hard parts of generative AI are not generative. They are retrieval quality, permission scoping, evaluation, and knowing when to refuse.

THE OPPORTUNITY

Where language models genuinely pay.

Anywhere your organisation spends hours moving meaning between formats: reading a contract to fill in a form, searching six systems to answer one question, summarising a case file, turning a spec into a first draft.

These tasks share a shape — high volume, tolerable error rate, cheap verification. That is the profile worth automating first, and it is where we start.

WHAT WE BUILD

Four system shapes, chosen by the problem.

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HOW IT WORKS SELECT A STAGE
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WHAT EXISTS AT THE END
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TECHNOLOGY

Model choice is an engineering decision, not a preference.

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USE CASES

Shapes we have built before.

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OUTCOMES WHAT WE MEASURE — NOT A PROMISE OF RESULTS
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RELATED WORK [PLACEHOLDER — REAL CASE DATA PENDING]
FAQ

Generative AI, asked properly.

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BRING US A
REAL DOCUMENT.

The fastest way to find out whether this works for you is one of your actual files and one of your actual questions. We will tell you what it would take — and if retrieval is the wrong tool here, we will say that instead.