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AI & AutomationLLM features, automation, and custom models  shipped.

What this looks like in practice

We build AI-powered systems that help businesses automate operations, improve decision-making, and create intelligent digital experiences. Our AI solutions combine machine learning, automation, large language models, and intelligent workflows to solve real-world business challenges. We utilize agentic AI systems capable of handling multi-step operations, process automation, reasoning-based workflows, intelligent task execution, and adaptive business logic — enabling smarter and more efficient products.

What we build

AI Capabilities

Who it's for

Teams shipping AI features to real users — not demos. We build evaluation pipelines, guardrails, and cost monitoring from day one.

04How we work

A clear path from idea to live.

Five stages. Tight feedback loops at every handoff. You see real progress on a staging URL from week one.

  1. 01 · The Spark

    Discovery

    We listen and define success.

  2. 02 · The Sketch

    Design

    Wireframes, brand, motion.

  3. 03 · The Build

    Build

    Production code, weekly.

  4. 04 · The Polish

    Test & Refine

    QA, accessibility, real users.

  5. 05 · The Light

    Launch & Evolve

    Go-live, docs, growth.

Working together

What an engagement looks like.

Typical timeline
2–4 weeks to a working POC
Engagement model
POC first, then fixed scope or retainer
How it starts
POC first — validate before production code.
Before you ask

Common questions.

We think AI could help our business — where do we start?

With a short discovery call and a 2–4 week proof of concept on your real data and workflow. You see it working before committing to a production build — that's how every AI engagement here starts.

Do you build with our data safely?

Yes. Your data stays in your accounts and infrastructure wherever possible, we work under NDA, and we're upfront about what any third-party model provider sees.

Which AI models and tools do you use?

Whatever fits the job — commercial LLMs (Claude, OpenAI), open-source models, or classic ML. We optimise for reliability and running cost, not for using the trendiest model.

What does AI automation actually cost to run?

We design for predictable unit economics and show you projected per-month running costs in the POC report, so the production decision is made with real numbers.

What if the POC shows it doesn't work?

Then you've spent a few weeks learning that cheaply — with a written report on what blocked it and what would need to change. That honesty is the point of POC-first.

Reach us directly — no forms, no wait

Let'stalk.

Drop us a message or call us directly. We reply to every enquiry — usually the same day.