Services

AI Integrations

Intelligent systems that add real value. From LLM-powered features to computer vision pipelines — we integrate AI where it actually matters.

A model call is easy. The hard part is everything around it: grounding answers in your data, handling the cases where the model is wrong, keeping latency tolerable, and controlling what it costs per user. We build the parts that make an AI feature safe to put in front of customers.

What we build

LLM-powered features

Assistants, summarisation, extraction, and classification wired into your existing product and your existing data.

Retrieval over your own data

Document ingestion, chunking, embeddings, and retrieval so answers cite your content instead of improvising.

Document processing

Parsing, extraction, and review workflows for contracts, invoices, and forms — with a human approval step where it matters.

Computer vision pipelines

Detection and classification pipelines, from capture through to the queue that processes them.

Evaluation and guardrails

Test sets, regression checks, fallbacks, and rate limits, so a model change does not quietly break your product.

Cost and latency control

Caching, model routing, and streaming, so the feature stays affordable at volume.

What you get

  • The feature running in your product, not a standalone demo
  • An evaluation set you can re-run when models change
  • Cost and latency figures measured under realistic load
  • Documented fallback behaviour for when the model fails

We build this for ourselves too

LawManager is our AI-powered legal practice platform, with document review built into the day-to-day workflow rather than sitting beside it.

Common questions

Do we need our own model?

Almost never. Most products are better served by a hosted model plus good retrieval over your data. We will tell you if your case is genuinely an exception.

How do you stop it giving wrong answers?

Grounding answers in your own content, an evaluation set that runs on every change, and a designed fallback for low-confidence cases rather than a confident guess.

What does it cost to run?

That depends on volume and model choice. We measure cost per action during the build and design caching and routing around the number.

Other services

Let's talk about your ai integrations project.

info@an2tech.com