Custom AI Software
Built around your workflow, grounded in your data.
Generic AI tools give generic answers because they've never seen your pricing, your policies or your history. Custom means it answers from your material, inside your process, with the checks that make it safe to rely on.
Why people build custom
A confident wrong answer is worse than no answer.
Off-the-shelf AI doesn't know your business, so it guesses, and it guesses fluently. In a business context that's a liability. The fix isn't a better prompt. It's grounding the thing in your actual data, constraining what it's allowed to say, and putting a human in the loop where being wrong is expensive.
What's in it
Eight things. Half of them are constraints.
Workflow mapping first.
Where the AI sits in the process, and where it doesn't.
Grounding in your data.
Retrieval over your documents, records and policies, so answers come from your material with sources attached.
Guardrails.
What it will not discuss, will not promise, and will not do. Written down and tested.
Human-in-the-loop where it counts.
Review and approval on anything with money, legal exposure or a customer relationship attached.
Confidence thresholds.
Below the line it escalates instead of guessing. Configurable by you.
Evaluation before launch.
Tested against real cases with real expected answers. You get numbers, not assurances.
Monitoring after launch.
Quality drifts. We build the alerting that tells you before a customer does.
Model flexibility.
Not locked to one vendor. When something better or cheaper appears, we swap it.
Modules are conditional capabilities. Providers, data handling, permissions, integrations, evaluation and human review are confirmed in the written scope.
How it works
Four steps.
01 — Map the workflow.
Including where AI shouldn't touch it.
02 — Build and ground.
Connected to your approved sample data, on a staging link.
03 — Evaluate.
Real cases, measured. One feedback round.
04 — Live, monitored.
With alerting on quality.
Recent work
Work examples are being prepared.
No client logo or project image is published without a complete record and permission.
No permissioned proof record is currently published.
How this starts
Give us twenty real questions.
One clickable prototype and one feedback round are free. If you stop there, no payment is due and you keep the feedback; the prototype remains Kollabit property unless the engagement proceeds, subject to our Terms.
Book a Free ConsultationThe short version
What it costs.
- 200
- CAD per day, per AI Product Engineer.
- 5
- days to a grounded, evaluated system.
- 100%
- Custom project deliverables transfer after final payment, subject to our Terms. Pre-existing Kollabit materials and third-party tools keep their existing ownership or licences.
Model API costs are yours, billed direct, usually a few dollars a day. Simple and typical estimates are non-binding. Final scope is confirmed before billing; taxes and third-party costs are additional.
Order your days →Questions
The ones we get asked.
How much does custom AI software cost?
$200 CAD per day, per engineer. About five days for a grounded system. Model API costs are separate and usually small. Simple and typical estimates are non-binding. Final scope is confirmed before billing; taxes and third-party costs are additional. Availability depends on suitable provider access or APIs, account permission, approved scope and testing; confirm before committing.
How do you stop it making things up?
Grounding in your data with sources, guardrails on what it can say, confidence thresholds that escalate rather than guess, and evaluation before launch. Collection, provider configuration, retention, access, deletion, human review and regulated-data handling are confirmed in the written privacy/security scope.
Is my data used to train models?
No. We use configurations that exclude training on your content. Collection, provider configuration, retention, access, deletion, human review and regulated-data handling are confirmed in the written privacy/security scope.
Which AI model do you use?
Whichever fits the job. We don't lock you to a vendor and we'll swap when something better appears.
Can it work with my private documents?
Yes. That's the main use case. Confidentiality is scoped at kickoff. Collection, provider configuration, retention, access, deletion, human review and regulated-data handling are confirmed in the written privacy/security scope.
What if it gives a wrong answer to a customer?
Human review sits on anything with money, legal exposure or a relationship attached. Where it's customer-facing, it escalates rather than guesses. Collection, provider configuration, retention, access, deletion, human review and regulated-data handling are confirmed in the written privacy/security scope.
How do you measure whether it works?
Against your real cases with your expected answers. You get numbers before launch.
What happens when quality drifts?
Monitoring and alerting are built in, so you hear it from us and not a customer.
Can we run it on our own infrastructure?
Usually, depending on the model. Tell us the requirement at kickoff.
Who owns it?
Custom project deliverables transfer after final payment, subject to our Terms. Pre-existing Kollabit materials and third-party tools keep their existing ownership or licences.
Start with representative questions.
With the right answers. We'll show you how many it gets, free.