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AI engineering for the products you already run
Copilots, search and document intelligence, wired into your stack and tested before release.
Where AI engineering helps
You want AI features inside your product
Copilots and assistants that work on your product’s own data, behind your existing logins and roles.
ClaimXPro.ai
Tidy text sits inside the web app’s assessment and attendance editors, for owners and admins.
Your search or documents need to be smarter
Retrieval-augmented generation over your content, so answers come from your own sources.
How we build it
On OpenAI and Claude models, inside your systems, tested with evaluation runs before release.
You need AI you can trust in front of users
Evals and guardrails test AI output before release and after every change.
ClaimXPro.ai
Ten automatic checks keep numbers, dates, names and negations unchanged in every suggestion.
What does AI engineering cover?
Six building blocks we add to products you already run, without a rebuild.
How do we ship AI without breaking things?
Every change goes through Git, code review, automated tests and staging. AI drafts code; an engineer reviews every change before release.
Book a discovery callStep 01
Discover
Map the workflow, data and systems before writing any code.
Claude
Step 02
Plan
Scope, fixed estimate and success measures agreed with you.
Step 03
Build
Small, reviewed changes. AI-assisted, engineer reviewed.
Git
Docker
Step 04
Test
Automated tests, plus evaluation runs on AI output.
- Playwright
PHPUnit
Step 05
Ship
Planned releases with a tested rollback.
GitHub Actions
Step 06
Monitor
Errors, latency, cost and AI answer quality watched after release.
- CloudWatch
An AI feature we shipped
ClaimXPro, one of 100+ projects delivered, added an AI writing assistant to a live product.
See all projects
Case 01Custom build
ClaimXPro.ai
Claims and restoration platform on web and iOS, with Amazon Bedrock in the technician workflow
- Property restoration
- Next.js
- Australia
Tidy text in ClaimXPro
- Amazon Bedrock
- Claude Haiku 4.5
- NestJS
- Next.js
- A button in the editors technicians already use, no new tool to learn.
- Fixes spelling, grammar and punctuation without changing any facts.
- Ten automatic checks run before a suggestion is shown.
- The user accepts every suggestion; nothing is stored or logged.
The stack we work in
Models
- Claude
- OpenAI
AI platforms
- Amazon Bedrock
- Microsoft Foundry
Build
- Python
- Node / NestJS
- React / Next.js
Test and ship
- Git
- Playwright
- GitHub Actions
Ways to work with us
A free call, a scoped build or a dedicated engineer. Start small, switch later.
AI engineering questions
What is AI engineering?
AI engineering is building language-model features into real software: copilots, search and document intelligence, with tests, guardrails and monitoring, so they work for users every day.
Do we need to rebuild our product?
No. We add AI to products you already run, wired into your existing stack, logins and data. In ClaimXPro, the AI feature is a button inside editors users already know.
What is RAG?
RAG, retrieval-augmented generation, lets a model answer from your own documents and data instead of only what it learned in training, so answers can point to your sources.
How do you test AI features?
Automated tests, plus evaluation runs on AI output, at every stage. Every change is reviewed by an engineer, tested and committed to Git before release.
Who owns the code and the data?
You do. We sign an NDA on request, you own all code and IP, and we hand over the complete Git history at any point.
What happens next
A straight answer on what to build first.
- Your workflow, systems and goals.
- We reply with times for the call.
- A fixed-price next step, or a referral if we are not the right fit.
First reply within 1 business day.
Free call. NDA on request. First call in your time zone.
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