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PlanBuildAI AI in Construction

Custom AI Development

Custom AI development, built on your data

We design and build AI features that do a specific job inside your business — answering questions from your documents, extracting data from files, classifying images — and we make them reliable enough to run every day.

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Covers: Custom AI Development · Data Analytics and AI Solutions

What our team does

Most useful AI is narrow: one well-defined task, measured against real examples, wired into the system where the work already happens. Our team scopes that task with you, tests candidate approaches on a sample of your data, and only then builds the production version — with evaluation, monitoring and a clear path to improve it.

  • LLM integration

    Adding large language model features to your products and internal tools: summarisation, drafting, classification and structured output, with guardrails and cost controls.

  • Retrieval over company documents (RAG)

    Search and question-answering over specifications, contracts, manuals and policies, returning answers with links to the source passages.

  • Document extraction

    Pulling structured fields out of invoices, delivery notes, submittals, forms and PDFs, with confidence scores and human review for uncertain cases.

  • Computer vision

    Image classification and detection for photos such as site progress, defects or safety equipment, trained and tested on your own labelled examples.

  • Data analytics and prediction

    Cleaning and joining operational data, then building dashboards, forecasts and anomaly checks that people can understand and question.

  • Evaluation and monitoring

    Test sets, accuracy reports and production logging, so you can see how the system performs and catch regressions before users do.

Problems we help solve

  • Staff spend hours searching shared drives, email and old project files for an answer someone already wrote down.
  • Information arrives as PDFs, scans and photos and has to be re-typed into another system by hand.
  • You tried a general-purpose chatbot, but it cannot see your documents and its answers cannot be checked.
  • Data exists in several systems, yet nobody can easily answer basic questions about trends or exceptions.
  • A promising AI pilot never made it into daily use because it was not reliable, secure or integrated.

What you receive

  • A written problem definition and success criteria agreed before build work starts
  • A prototype tested on a representative sample of your data, with results you can review
  • The production feature or service, deployed to your environment or ours as agreed
  • An evaluation set and a report of measured accuracy against it
  • Source code, configuration and technical documentation
  • A handover session and an agreed support period

The exact deliverables for your project are listed in your written proposal.

Technologies we use

We choose tools for your requirements, existing systems and the team that will maintain the result — not the other way round. Typical choices include:

  • Python
  • PHP
  • TypeScript
  • Claude and OpenAI APIs
  • Open-weight models where data must stay on-premises
  • PostgreSQL / pgvector
  • MySQL / MariaDB
  • OCR and PDF parsing
  • Computer-vision frameworks

How the process works

Every AI development project follows the same transparent path. You always know what happens next and nothing is built before you have agreed the scope in writing.

  1. Step 1: Request

    You describe the problem, the systems involved and any constraints in a short form. Attach documents if they help.

  2. Step 2: AI-assisted qualification

    An AI assistant organises the request and flags missing details. It does not price or approve anything.

  3. Step 3: Review by our engineers

    An engineer on our team reads the request, checks feasibility and contacts you with any questions.

  4. Step 4: Written proposal

    You receive scope, deliverables, timeline, price and assumptions in writing — nothing is implied or hidden.

  5. Step 5: Agreement

    Once you accept, we put a formal agreement in place before any build work starts.

  6. Step 6: Delivery

    We build in short, reviewable increments, test against the agreed acceptance criteria and hand over.

Frequently asked questions

Usually not. Many document and language tasks work with existing models plus a few dozen good examples for testing. Computer-vision and prediction tasks need more labelled data; we will tell you how much after looking at a sample.

We choose per task, based on accuracy on your examples, cost, latency and where your data is allowed to go. That can be a commercial API such as Claude or an open-weight model hosted in your environment.

No. We agree in writing which providers may process your data, use API terms that exclude training on customer data, and can keep processing on infrastructure you control when required.

We build a test set from your real cases, measure results against it, show sources for every generated answer and route low-confidence results to a person. No AI system is perfect, so we design for checking.

Yes. We start with a short review of the existing code, data and results, then propose either targeted fixes or a rebuild, with the reasons for each option.

Related services

Looking for something else? See all our services.

Start your AI development project

Tell us what you need in a few minutes. An engineer on our team reviews every request and replies with questions or a written proposal — scope, timeline and price included.

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Or start with: Custom AI Development Data Analytics and AI Solutions

Free and without obligation — work starts only after you accept a written proposal.