How much does an AI feature cost to build?

A focused first feature — say, document extraction or a grounded assistant over your knowledge base — is typically £10k to £40k including evaluation and production hardening. Ongoing model costs are usually modest and we design to keep them that way.

How do you stop the AI making things up?

Retrieval grounding (answers must come from your documents), structured outputs, confidence thresholds, human-in-the-loop approval for consequential actions, and automated evaluation against a test set that we build with you.

Which AI models do you use?

We choose per task from the leading commercial models and open-weight models that can run privately. The integration is written so switching models later is a configuration change, not a rebuild.

Can you add AI to our existing software?

Yes. Most of our AI work is adding features to products that already exist — ours or someone else’s. We start with a review of your codebase and data, then prototype against real records.

AI & Automation

AI features that earn their place

Copilots, agents, document understanding and automation built into your product — designed around a real workflow, measured against a real outcome.

Overview

AI & Automation Development

Most “AI features” fail for a simple reason: they are added because AI is fashionable, not because a specific job in the product got easier. We build AI the other way round. We start with a workflow that costs your team or your customers time — triaging enquiries, extracting data from documents, answering questions from a knowledge base, drafting the same report every week — and design the smallest AI feature that removes that work reliably.

Technically that means large language model integration done properly: retrieval over your own data (RAG) so answers are grounded in your documents rather than invented, structured outputs that your system can act on, guardrails and evaluation so quality is measured rather than assumed, and cost and latency controls so the feature is affordable at scale.

We build with the current generation of models and tooling, keep you independent of any single provider, and are honest about where AI is not the right answer. Sometimes the best result is a well-designed automation with no model in it at all.

What you get

Delivered as one complete product

Everything a production-grade product needs, built by the same senior team from start to finish.

LLM-powered product features

Assistants, summarisation, classification, drafting and search built into your existing product with a proper user experience around them.

Retrieval over your data (RAG)

Pipelines that index your documents, tickets, policies or product data so answers are accurate, cited and up to date.

AI agents & copilots

Multi-step agents that can look things up, call your APIs and complete tasks, with human approval where the stakes require it.

Document & process automation

Extracting structured data from invoices, forms, emails and PDFs and pushing it into your systems without manual re-keying.

Evaluation & guardrails

Test sets, quality scoring and safety checks so you know how the feature performs before and after every change.

Cost, latency & observability

Caching, model routing, streaming and monitoring so the feature stays fast and affordable as usage grows.

How we work

From first call to live product

01
Find the right job
A short workshop to identify workflows where AI can remove real effort, and to rule out the ones where it would only add risk.
02
Prototype with your data
A working prototype against real documents or records within a couple of weeks, so you can judge quality on your own material.
03
Build for production
Evaluation sets, guardrails, fallbacks, logging and cost controls turn the prototype into a feature you can trust in front of customers.
04
Measure and improve
Usage and quality metrics feed a steady loop of improvements — prompts, retrieval, models — after launch.

Where this fits

Typical projects

Customer support and enquiry triage

Classify, route and draft replies to incoming enquiries, with the knowledge base answers grounded in your actual documentation.

Document processing

Turn invoices, applications, contracts and reports into structured data that flows straight into your platform or accounting system.

Internal knowledge assistants

A copilot that answers staff questions from policies, procedures and past work — with citations, so people can check the source.

Intelligent features inside your SaaS

Smart search, recommendations, auto-tagging and report generation that make your existing product more valuable to pay for.

Why InteleForge

What makes the difference

Product engineers first

We build the whole feature — UI, API, data pipeline and model integration — not a notebook demo that someone else has to productionise.

Measured, not magical

Every AI feature ships with an evaluation set and quality metrics, so “it works” is a number rather than a feeling.

Provider-independent

Model calls are abstracted so you can switch providers or move to a cheaper or self-hosted model as the landscape changes.

FAQ

AI & Automation: your questions

Straight answers on cost, timing and how we work.

We use business-tier APIs where your data is not used for training, keep sensitive data out of prompts where possible, and can deploy self-hosted models for the most sensitive workloads. Data handling is designed around UK GDPR from the start.

Related services

Have an idea worth building?

Tell us what you’re trying to build. We’ll come back within 24 hours with honest feedback and a clear first step — no obligation.

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