GlenndilenDigital

Intelligent AI systems Built to do real work

Custom AI applications, automation and knowledge systems designed around specific business tasks, tested on your real data and built to be relied on.

Explore an AI projectLLM development

Less hype. More useful work.

AI is most valuable when it takes on a specific, repeatable job: reading incoming documents, answering questions from your own knowledge, drafting responses for a person to approve, or moving a routine request to the next step.

We combine hands-on language-model experience with years of software, integration and infrastructure engineering. That matters, because the model is only one part of a working system. The rest is data, permissions, integration, evaluation and a clear plan for when the AI is unsure.

What we build with AI.

Each one starts with a clearly defined task and a way to measure success.

  • Custom LLM applications

    Language-model tools built around a task your business can define and test.

  • Document processing

    Invoices, orders, forms and emails turned into structured, validated data.

  • Knowledge assistants

    Answers from your own documents, with sources and access controls.

  • Workflow automation

    Routine requests classified, prepared and routed, with human approval where it matters.

  • Private deployment

    Self-hosted models for sensitive data or predictable high-volume workloads.

  • Evaluation and monitoring

    Test sets, accuracy tracking and cost monitoring for systems in production.

A task you can judge.

Good AI projects have an identifiable input, a repeatable decision and a way to check the result. Turning supplier documents into draft product records, or incoming emails into structured orders, are typical examples.

We test on your real examples before promising anything. If a simple rule or integration solves the problem more reliably, we will tell you, and build that instead.

  • Use cases chosen for measurable value
  • Tested on representative real examples
  • Conventional code where it beats AI
Document processing
purchase-order.pdf

PURCHASE ORDER

PO number: 24817
Account: 10482
Deliver by: next Friday

24 ×Waxed jacket, olive, M
12 ×Quilted gilet, navy, L
6 ×Wool scarf, tartan
Extracted
po_number
24817✓
account
10482✓
lines
3 items · 42 units✓
deliver_by
“next Friday”Review

Relative date flagged for a person to confirm.

Grounded, controlled and accountable.

Business AI must know its limits. We ground answers in your own information, show sources, respect who is allowed to see what, and design clear behaviour for when the answer is not in the data.

Where an action has consequences, a person approves it. Every system is documented so you understand what it does, what it costs to run and how to change it.

  • Answers backed by your sources
  • Permissions respected throughout
  • Human approval for consequential actions
Knowledge assistant

Can trade customers return opened items?

Yes, within 30 days if the item is unused and in its original packaging.1 Returns need a return number from the trade portal before anything is sent back.2

  • 1Trade terms, section 7.2
  • 2Portal help: Returns

What AI can take off your plate.

Four common workflows we build. Each combines a language model with conventional rules, integrations and a person where it matters.

Order capture

Turn order emails into validated orders.

  1. Email arrivesPDF or message with an order
  2. AI reads itCustomer, items, quantities, dates
  3. Rules checkStock, prices and account verified
  4. Order createdOr flagged for a person to check

How we work together.

A clear, collaborative process with no surprises. You always know what is happening, what we need from you and what comes next.

  1. Step 1

    Find the use case

    We identify a task with a clear input, a repeatable decision and a way to check the result.

  2. Step 2

    Prove it

    A focused pilot tested on your real examples, with an honest view of accuracy, cost and limits.

  3. Step 3

    Build it properly

    Integrations, permissions, monitoring and human review where the stakes call for it.

  4. Step 4

    Operate & improve

    Evaluation, cost tracking and improvements as your data and needs change.

Questions, answered.

Anything else you would like to know? Ask us directly and we will give you a straight answer.

Do we need to train our own language model?

Usually not. Most business use cases are best served by an existing model combined with a good workflow and access to the right information. Fine-tuning or training is considered only when it addresses a measured gap.

Is our data safe?

We design data handling around your requirements, including which providers are used, what is stored and who can access it. For sensitive workloads, private deployment keeps data within infrastructure you control.

How do you stop the AI making mistakes?

No AI is perfect, so we design for that: validated outputs, limited actions, confidence checks and human review where errors would matter. We measure accuracy on real examples before and after launch.

How much does an AI project cost?

We usually start with a short discovery and a focused pilot, priced up front, so you can see real results before committing to a full build. Running costs are estimated and tracked.

Can AI work with our existing software?

Usually. We review the APIs and data access available and connect the AI into the tools your team already uses rather than adding another app.

Related services.

LLM development

Language-model applications built around a defined task, evaluated on real examples and engineered for dependable production use.

Explore

Business automation

Automate the repetitive steps between receiving a document or request and completing the work, with your team kept in control.

Explore

Knowledge systems

Knowledge assistants that find and explain the information your organisation already holds, with sources shown and permissions respected.

Explore

Private AI

Run language models on infrastructure you control when data sensitivity, compliance or volume make a shared API the wrong fit.

Explore

Let’s build something exceptional.

Tell us about the website, platform or problem you have in mind. We’ll reply within one working day with honest advice on the best next step.

Start a projectSee our work

Or email hello@glenndilen.co.uk