Custom Software Development
Systems that fit how your business actually runs, built from the ground up.
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AI Development & Integration
AI development and integration for business
AI put to work in the parts of your workflow where it genuinely saves time, wired into the systems you already run.
Overview
What this is
Most businesses do not need an AI research project. They need a specific task done faster: sorting incoming email, drafting a first version of a document, pulling an answer out of years of PDFs, or checking a form for errors before a person sees it.
We find the task where AI earns its place and build it into your existing software, with guardrails so the output can be trusted. Where a plain rule or a smaller model does the job, we use that instead.
Included
What’s included
Use-case assessment
We look at where your team spends repetitive effort, then work out which tasks AI can take on reliably and what they would cost to run.
Integration with your systems
The AI feature built into the tools you already use, so it shows up in the workflow rather than as another tab to check.
Retrieval over your own content
Question-and-answer and search across your own documents and records, with answers that cite where they came from.
Guardrails and review
Checks on the output and a way for staff to correct it, with logging so you can see what the system did and why.
Cost and model management
We keep an eye on usage cost and match the model to the job, swapping it as better or cheaper options appear.
Approach
How we approach it
Understand
We start with the work, not the technology. We watch where time goes and pick a task where the input is clear and the output can be checked, and where being slow today carries a real cost.
Simplify
We try the plainest thing that could work first. Often a small, well-scoped feature beats an ambitious one, and sometimes the answer is not AI at all.
Build
Senior developers build the feature into your existing system in short cycles, with a person kept in the loop on anything that carries risk.
Improve
After launch we watch how often staff override the output and what the feature costs to run, then tune the prompts and the data behind them and change the model if a better fit appears.
Stack
Tech we use
An honest starting point, not a fixed menu. We pick per project and tell you why.
- OpenAI and Anthropic APIs
- Open-weight models where they fit
- Python
- TypeScript
- pgvector
- Your existing database and stack
- AWS
FAQ
Common questions
- Is our data used to train an outside model?
- Not on the setups we build. We use business API tiers and configurations where your content is not retained for training, and for sensitive material we can run smaller models on infrastructure you control.
- What if the AI gets it wrong?
- We assume it sometimes will. That is why we scope tasks where the output is checked, by a person or by a rule, before it does anything that matters. We also log every call so mistakes can be traced.
- Do we need a large budget to start?
- No. A first, narrow feature is a small build, and the running cost for one task is usually minor. Starting small is also the right way to find out whether AI helps before committing further.
Bespoke SaaS
Your own platform, built to your process — not another off-the-shelf tool you have to bend around.
Learn more →Existing Software
Inherited something half-built or stalled? We take it over, tidy it up, and move it forward.
Learn more →If this sounds like your project, Discovery is the next step.Start with a fixed-price Discovery — you get the scope, the plan and the number before you commit.
See how Discovery works →