Generative AI that
stays grounded.
Generative features that are grounded in your content, measured, and safe to ship.
Ask AI about this service
A demo is easy. Reliable generation needs grounded retrieval, evaluation against real cases, and controls on what the model can say and see. We build generative features as engineered systems, with private deployment as a first-class option.
What we build.
Copilots and assistants
Task-focused assistants embedded in the tools your teams already use, with source citations.
Document intelligence
Summarisation, extraction, drafting, and comparison across contracts, reports, and manuals.
Retrieval and search
Hybrid search over internal knowledge so answers trace back to a source document.
Evaluation and guardrails
Test sets, red-teaming, output filters, and access controls before anything reaches users.
Typical applications.
Generative AI earns its place where people spend hours reading, writing, or searching.
Proposal and report drafting
First drafts assembled from templates and prior work, reviewed by the expert.
Policy and SOP assistants
Staff ask in plain language and get the governing clause with its source.
Engineering knowledge search
Find the right drawing, test report, or fix across years of documents.
A grounded prototype on your data in 10 days.
From the day you engage us, not from a kickoff weeks later. Every milestone is a result you can see.
- Day 3
Use case, sources, and quality bar agreed
- Day 10
Working prototype with source citations
- Day 35
Evaluated, guard-railed release to a pilot group
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Fixed scope
Scope, price, and milestones are agreed before work starts.
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No surprises
Weekly demos and plain-language status. Changes are priced before they are built.
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Compliance from day one
Content filters, access rights, and data-handling rules are enforced in the prototype, so what is demonstrated is what ships.
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You own the IP
Code, models, and documentation transfer to you on successful handover.
Know the price, the date,
and the exit before we start.
Fixed-scope project. A defined deliverable at a fixed price and date. Payment is released as each milestone is accepted. The same terms are written into every statement of work for generative ai development, so there is nothing to discover later.
- Quote Within 5 working days Price per milestone, dates, and named architect
- Priced One price per milestone Third-party costs listed separately, at cost. Invoiced in USD for international clients
- Paid On accepted working software Not on calendar dates or hours logged
- Changes Written and priced first Cost and date impact before work starts
You fund accepted work, never a promise.
Drag to move through the engagement. Money is released only as each gate is accepted, so what you have paid never runs ahead of what you can use.
- Milestone 1Day 3
Use case, sources, and quality bar agreed
Accepted whenWorking software demonstrated against the written acceptance criteria.
Releases 20% - Milestone 2Day 10
Working prototype with source citations
Accepted whenWorking software demonstrated against the written acceptance criteria.
Releases 30% - Milestone 3Day 35
Evaluated, guard-railed release to a pilot group
Accepted whenWorking software demonstrated against the written acceptance criteria.
Releases 30% - HandoverAt final acceptance
Code, architecture documents, deployment scripts, and credentials transferred to you.
Accepted whenFinal acceptance signed. Defects then fixed under warranty at no charge.
Releases 20%
Illustrative split. The exact percentages and dates are fixed in your statement of work.
When something goes wrong, who pays?
Every project meets surprises. What matters is who carries them. Pick one and compare how three commercial models respond.
The hours keep running while the team investigates. You pay for the surprise.
A change request is raised, usually priced at a premium and argued over.
We verified it before quoting, and the risk register held an allowance. Any overrun beyond it is ours.
It is absorbed into the hours. The date slips quietly and you learn at the invoice.
A change fee arrives, often as a lump sum with little explanation.
You get a written amendment with cost and date impact. Nothing starts until you approve it.
You pay for the difference. The estimate was only ever a guess.
The vendor reopens scope to recover margin, or cuts corners to hold it.
The price stays fixed. The overrun is ours to carry, and you see the budget position at every demo.
It is billed on the calendar anyway. The status report says "on track".
The invoice follows the date in the contract, whether or not the work is done.
Payment for that milestone is held until it passes the written criteria. You do not fund a miss.
One price, built in the open.
The proposal itemises every feature or milestone, names its assumptions, and keeps a risk register with allowances. Allowances you never use are not billed.
- Number of use cases or workflows
- Data sources and knowledge base size
- Channels and integrations
- Governance and evaluation depth
Knowledge sources and an owner for them are named in week one.
If falseDates move by the delay, written down. The price holds.
Quality is measured against the test set we agree together.
If falseA changed test set is re-priced before it is used.
Content and data-access rights are cleared by your team.
If falseAnything blocked is flagged immediately, with a costed alternative.
- Cloud hosting
- Third-party licences
- Model and API usage
Invoiced in USD for international clients, with the currency fixed in the SOW. You own it. Code, models, documents, and credentials transfer on payment.
Built on a production-grade stack.
We pick tools proven in production and maintainable over long lifecycles - not whatever is trending. These are a few we reach for here; explore the full stack behind our engineering.
Explore our technology stack →
Articles on Generative AI Development
All articles→Automating Document-Heavy Workflows Without Losing Control of Exceptions
Design document processing automation with extraction, validation, matching, human review, audit evidence and end-to-end performance measures.
Read article →How Do You Test Whether an AI System Is Actually Good Enough to Deploy?
Build an AI evaluation strategy using representative tasks, groundedness, permissions, robustness, abstention, regression tests and release thresholds.
Read article →Why an Enterprise AI Assistant Needs More Than Access to Your Documents
Understand the retrieval, permissions, freshness, evaluation and audit controls an enterprise AI assistant needs to answer reliably.
Read article →What buyers ask before they commit.
Straight answers on timelines, price, risk, and ownership, the same terms that appear in every proposal.
01What is Generative AI Development?
Generative AI development for enterprises: document generation, summarisation, search, and copilots grounded in your data and deployed on your infrastructure.
02How quickly does Generative AI Development deliver a first result?
A grounded prototype on your data in 10 days. Typical milestones are Day 3: use case, sources, and quality bar agreed; Day 10: working prototype with source citations; Day 35: evaluated, guard-railed release to a pilot group. Exact dates are written into the statement of work before you commit.
03How is Generative AI Development priced?
Fixed-scope project: one price per milestone, with a first-release date, itemised in a statement of work within five working days of scoping. Payment is released as each milestone is accepted against written criteria. Cloud hosting, licences, and model usage are passed through at cost. International clients are invoiced in USD. The main price drivers are number of use cases or workflows, data sources and knowledge base size, channels and integrations, governance and evaluation depth.
04What happens if the scope changes or the work overruns?
The price stays fixed. A change to scope is quoted in writing, with its cost and date impact, and starts only after you approve it. If our own estimate was wrong, the overrun is ours, not yours. You see the budget position against milestones at every demo.
05Who owns the code, models, and documentation?
You do. Code, models, and documentation transfer to you on successful handover. Code, architecture documents, deployment scripts, and credentials transfer on payment, with no licence back.
06How are security and compliance handled?
Content filters, access rights, and data-handling rules are enforced in the prototype, so what is demonstrated is what ships.
07Do you work with clients outside India?
Yes. We are based in Noida and work with clients around the world, delivering remotely. Calls and demos are scheduled in your time zone, proposals and contracts are in English, international clients are invoiced in USD, and every engagement follows the same fixed-scope terms regardless of where you are.
08When would you decline to fix a price?
If the scope is not yet defined, we do not guess a number. We propose a short, time-boxed discovery with its own fixed price, then quote the build.
Ship generative features you can stand behind.
Tell us the workflow you want to speed up and the content it depends on. We will tell you what is feasible, what it needs, and how we would measure it.