AI that removes work, not headcount theatre.
The useful AI projects are unglamorous. A quoting process that took two days now takes ten minutes. A support inbox that triages itself. We build the specific, boring automations that give people their week back, and we are direct about the ones that are not worth building.
What is AI automation for business?
Turn repetitive knowledge work into reliable, measurable workflows powered by AI.
AI automation for business is the use of large language models and related tooling to complete repetitive knowledge work that previously required a person, such as classifying enquiries, extracting data from documents, drafting responses or summarising records. Unlike general-purpose chatbots, business AI automation is scoped to a defined task, connected to the organisation's own data, and measured against the time or error rate it removes.
Define the task
Start with repetitive work that has a clear input and a useful output.
Connect your data
Ground the automation in the documents, systems and information your business uses.
Automate the work
Use AI models and workflow tooling to handle the repetitive steps.
Measure the gain
Track time saved, errors removed or capacity created by the automation.
The goal isn't to add AI for the sake of it. It's to remove measurable work from a process while keeping the outcome useful, reliable and connected to the business.
What the engagement covers.
Custom agents, integrations and automation built on your own data.
Retrieval assistants
Assistants grounded in your own documentation, pricing and policies, so answers come from your material rather than from a model's general knowledge.
Workflow automation
Connecting the systems you already run so work moves between them without a person copying fields: CRM, inbox, forms, spreadsheets, accounting.
Document processing
Extracting structured data from quotes, invoices, contracts and forms, with confidence scoring and human review where the stakes justify it.
Support triage
Classification, routing and drafted first responses, with clear rules about what is never answered automatically.
Content operations
Production pipelines that keep a human editor in the loop, built for consistency and brand voice rather than volume for its own sake.
Evaluation and guardrails
Test sets, accuracy measurement, fallback behaviour and logging, so you know when the system is wrong and what it did.
Four stages, in order.
Find the real cost
We look for tasks with high volume, clear rules and a measurable time cost. If your best candidate does not clear that bar, we will tell you rather than sell you a build.
Prototype narrow
One workflow, real data, two to three weeks, with an accuracy target agreed before we start.
Harden
Evaluation set, error handling, human review points, access control and logging before anything touches production.
Deploy and monitor
Rollout with measurement against the original baseline, and a documented path for your team to run it without us.
AI development, answered plainly.
Will our data be used to train someone's model?
Not in anything we build. We use enterprise API tiers with training explicitly disabled, and where the data is sensitive we can architect around self-hosted or regionally-hosted models. The data handling is specified in writing before the build starts.
What does an AI automation project cost?
A scoped single-workflow automation typically runs from $8,000 to $30,000 depending on the systems involved and the accuracy required. We prefer to start with one narrow workflow so the return is proven before the spend grows.
Can AI replace our team?
That is usually the wrong goal and the wrong result. The projects that pay off remove the repetitive fraction of a role so the person can do the part that needed a person. We are sceptical of headcount-reduction business cases and will say so.
What if the AI gets something wrong?
It will, which is why we design for it. Every build has an accuracy target measured against a test set, defined fallback behaviour, human review on high-stakes outputs, and logging so an error can be traced and corrected.
Often runs alongside.
Websites that load fast and sell hard.
Design, build and maintenance for sites that carry commercial weight.
Read moreGet cited by the models people now ask.
Generative engine optimisation for ChatGPT, Gemini, Copilot and Perplexity.
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Technical, content and authority work aimed at commercial search terms.
Read moreLet's talk about your growth.
A 30 minute call with the people who would actually run your account. No deck, no pitch team.