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 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.
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
Often built together
SaaS & Web Platforms
Dashboards, workflows, subscriptions and integrations — custom web applications that your customers pay for and your operation runs on.
Learn moreProduct Engineering
One team takes your idea through discovery, design, build and launch — and stays to scale it. This is how we built The SBK Dance, a live events marketplace.
Learn moreCloud & DevOps
Cloud architecture, automated deployments, security and monitoring — so your product is fast, resilient and affordable to run.
Learn moreTell us what you’re building.
You’ll get a reply from an engineer within one working day, with honest feedback and a clear first step. No sales script, no obligation.