AI development & integration

AI Development & Integration Services

AI applied to a specific, expensive problem - reading documents, classifying requests, answering questions from your own data - rather than added because it is expected.

The problem

What usually brings people here

People are reading documents for a living

Invoices, purchase orders, delivery notes and forms arrive as PDFs and images, and somebody types the contents into a system. It is slow, and accuracy drops through the afternoon.

The same questions arrive every day

Support and internal teams answer variations of the same forty questions. The answers exist, scattered across documents nobody can find quickly.

Triage is a bottleneck

Requests, tickets and applications queue while a person sorts them into categories and routes them onward.

Capabilities

What we build

Document processing

Extracting structured data from invoices, forms, contracts and scanned paperwork, with confidence scoring and human review where it matters.

Retrieval-based assistants

Question answering grounded in your own documents and data, with citations, so answers can be checked rather than trusted blindly.

Classification and routing

Sorting incoming email, tickets and requests by type, urgency and owner.

Forecasting and anomaly detection

Demand, stock and utilisation forecasting, and flagging transactions that do not look like the others.

AI features inside existing software

Adding drafting, summarising or search to a system your team already uses, rather than sending them somewhere new.

How we work

Our approach

01

Start with the cost, not the technology

We look for a task with real volume and measurable handling time. If there isn't one, AI is not the answer yet and we will say so.

02

Prove it on your data

A narrow evaluation on your real documents before committing to a build, because published benchmarks say nothing about your paperwork.

03

Design for the wrong answer

Confidence thresholds, human review queues and audit trails. Systems that assume the model is always right fail badly and quietly.

04

Measure against the manual baseline

Accuracy and handling time compared with how the work is done today, so the benefit is a fact rather than an impression.

Technology

What we build with

Chosen for fit and for how easily another team could pick the work up, not for novelty.

Python FastAPI Anthropic Claude OpenAI Vector databases PostgreSQL pgvector Redis Docker AWS Azure
Outcomes

What changes afterwards

Reading time collapses

Documents are extracted and queued for review rather than typed from scratch.

Answers become findable

Staff and customers get grounded answers with citations instead of hunting through folders.

Judgement stays with people

Automation handles volume; anything uncertain goes to a person with the context attached.

Industries

Where this work lands

Questions

Frequently asked

Often you do not, and we will tell you. AI earns its place where there is a high-volume task involving language or images that currently consumes staff hours - reading documents, sorting requests, answering repeated questions. If your problem is a broken process, fixing the process is cheaper and more reliable.

It will, so systems are designed around that. Extractions carry a confidence score, anything below a threshold routes to a person, and every decision is logged. The goal is to reduce the volume a human handles, not to remove the human.

That is a decision we make with you before building. Options range from commercial APIs with data-retention controls, through cloud-hosted models in a region you choose, to models running entirely on your own infrastructure. Regulated data usually points to the latter two.

Frequently yes, if it has an API or a database we can reach. Adding a capability to a system your team already knows beats introducing another tool.

Against the manual baseline: how long the task takes today, how accurate it is today, and what those become afterwards. We establish that baseline before building.

Discuss your ai development & integration project

Describe the challenge in your own words. You will get a candid assessment of whether software is the right solution, what the work would involve, and a realistic cost range.