AI & automation
AI that does the work, not the demo.
Most AI projects stall between a promising prototype and a system people rely on. We build the part in between: automation that runs in production, with the guardrails to keep it there.
Book a free AI assessmentWhere AI pays off
Six places the manual work is hiding
The best automation targets are repetitive, high-volume, and already documented. These are where we see the fastest return.
Document processing
- Replaces
- Reading invoices, contracts, claims, and forms by hand.
- Outcome
- Structured data extracted in seconds, with low-confidence fields flagged for a person to check.
Customer support triage
- Replaces
- Agents reading every ticket to work out what it is and who should take it.
- Outcome
- Requests classified, prioritised, and routed on arrival. Routine answers drafted for review.
Sales and revenue operations
- Replaces
- Manual lead research, CRM data entry, and follow-up scheduling.
- Outcome
- Leads enriched and scored automatically. Reps spend their time in conversations, not spreadsheets.
Finance and back office
- Replaces
- Reconciliation, expense review, and month-end reporting done line by line.
- Outcome
- Transactions matched and exceptions surfaced, so close takes days instead of weeks.
Engineering and internal tools
- Replaces
- Answering the same internal questions, writing boilerplate, and chasing status.
- Outcome
- Assistants that know your codebase and runbooks, with every answer grounded in your own sources.
Analytics and decisions
- Replaces
- Waiting on an analyst for every question about the numbers.
- Outcome
- Plain-language questions answered from your data, with the query and sources shown.
How an automation is built
From a mapped workflow to a system you can trust
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Map the workflow
We document every step, decision point, and exception in the process as it runs today. This shows where automation pays and where human judgment has to stay.
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Design the agent
Structured inputs and outputs, explicit confidence thresholds, and named checkpoints where a person reviews or approves before anything irreversible happens.
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Ship in shadow mode
The automation runs alongside the existing process on real traffic, without acting. We compare its decisions to yours until the numbers earn trust.
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Monitor and improve
Every run is logged with its inputs, outputs, cost, and outcome. Accuracy, throughput, and savings are on a dashboard, and the model improves on what it sees.
Two ways to bring AI in
Pick the engagement that fits the problem
AI integration
You have a product, and you want intelligence inside it.
Language models, vision, and prediction embedded in your own software: model selection, fine-tuning, evaluation, and production deployment.
See the serviceAI automation
You have a workflow, and you want it to run itself.
Agents that take over document processing, routing, and multi-step back-office work, with human checkpoints and full observability.
See the serviceWhat we hold ourselves to
Four rules every AI system we ship follows
They are not advanced techniques. They are the difference between a feature that gets quietly switched off and one that stays on.
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Structured output, always
Every model call returns a defined schema, never free text. Outputs are validated before they touch a downstream system.
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A person in the loop where it matters
Low-stakes, high-confidence decisions run on their own. Anything costly to get wrong routes to a reviewer with the context already assembled.
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Grounded in your sources
Answers are retrieved from your documents and data at the moment of the question, and cite where they came from. Guessing is not a feature.
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Observable from day one
Prompts, responses, latency, cost, and what the user did next are recorded for every call. You can see exactly what the system is doing and why.
In production
What this looks like when it ships
Real-time AI risk scoring
A two-stage model replaced 400 hand-written rules, scoring 10,000 transactions a second in under 50ms.
AI-powered order operations
Routing, fraud review, and customs handling automated, scaling from 500 to 50,000 orders a day.
Not sure where AI fits yet?
A free 30-minute readiness assessment: we look at your workflows and data and tell you honestly what is worth automating first, what it would take, and what it would return.