AI & Automation

Systems that work while you sleep

Chatbots, voice agents, automations and predictive models built on your own data — evaluated against real cases, deployed where your policy allows, and owned by you.

  • Chatbots
  • Voice agents
  • Workflow automation
  • Document processing
  • Predictive analytics
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AI solutions
10AI solutions
To first release
2–4 wksTo first release
Code & models
YoursCode & models
The catalogue

Where AI actually pays for itself

Each solution has its own page covering scope, delivery process, tooling and the questions clients ask before committing.

If your workflow does not match anything above, we scope custom AI properly — starting with an honest assessment of whether AI is even the right tool.

Custom AI solutions
How we build

Five stages, and an honest first one

Discovery is paid and its most valuable outcome is sometimes the conclusion that you should not build this.

  1. 01

    Assess

    We look at the problem and the data and tell you honestly whether AI is the right tool for it.

  2. 02

    Prototype

    The smallest version that proves the approach, tested against real examples from your business.

  3. 03

    Build

    Developed in stages, with quality measured against an evaluation set rather than asserted.

  4. 04

    Integrate

    Connected to the systems your team already uses, with error handling and alerting built in.

  5. 05

    Operate

    Monitored, tuned against live results, and documented so your team can run it without us.

How we work with AI

The commitments behind the buzzword

AI is easy to promise and hard to deploy responsibly. These are the specifics we hold ourselves to.

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  1. 01

    Accuracy is measured

    Every system is evaluated against a set of your real cases, and we report the number rather than describing it as "highly accurate".

  2. 02

    Your data stays yours

    Enterprise API tiers where inputs are never used for training, and deployment inside your own cloud where policy demands it.

  3. 03

    A human on the edge cases

    Low-confidence outputs go to a review queue instead of being pushed through silently and discovered three months later.

  4. 04

    We will say no

    Discovery frequently concludes that a rule, a process change or better tracking would beat a model — at a fraction of the cost.

  5. 05

    Documented and handed over

    Code, prompts, models and runbooks transfer to you. Nothing we build should be maintainable only by us.

  6. 06

    Built to fail loudly

    Monitoring, retries and alerting on every automation, so a silent failure never becomes a month of missing data.

FAQ

AI questions, answered

See all questions

Specific things: chatbots and voice agents that answer from your own documentation, automations that remove manual data entry, models that forecast demand or score leads, and AI-assisted content drafting with a human editor. Where a plain rule works better than a model, we use the rule and say so.

AI discovery call

Not sure what AI could do for you?

Describe the process that costs you the most time. We will tell you whether AI is the answer, what it would take to build, and what it would realistically save.

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