Business automation & AI
Automate the manual work your team shouldn't be doing
Most companies know exactly which tasks are wasting their time. Someone re-types invoice data every morning. Someone copies figures between two systems. Someone chases the same approval every week.
We automate that work — and we are deliberate about where AI belongs and where it doesn't. Deterministic steps should be deterministic. AI is worth using where the input is genuinely unstructured, and even then it belongs behind a review step a person controls.
The problem
What this usually looks like before we start
- Hours a day go into manual data entry
- It is slow, it is expensive, and it is where errors enter the business. This is usually the first and most valuable thing to automate.
- Steps get missed when someone is away
- A workflow that depends on memory is a workflow that fails intermittently. Automated triggers make the next step happen on its own.
- Two systems hold the same data and drift apart
- Synchronising them by hand guarantees they will disagree eventually. Automation keeps them consistent without anyone thinking about it.
- AI pilots that never reached production
- Usually because there was no review step, no error handling and no owner. Automation only counts once it runs reliably without supervision.
Who it's for
This is built for
- Teams re-keying data between systems that were never designed to talk to each other
- Businesses processing a steady volume of invoices, forms or documents by hand
- Operations leads whose process depends on someone remembering to trigger the next step
- Companies curious about AI but unwilling to put an unreviewed model in front of customers
What you get
What a build includes
- A map of what is worth automating
- We start by identifying which tasks actually justify automation — volume, repetition and error cost — rather than automating whatever is easiest to reach.
- Reliable workflow automation
- Scheduled and event-driven jobs with retries, logging and alerting, so a failure is visible immediately instead of discovered weeks later.
- Document processing with human review
- Where documents are genuinely unstructured, we use language models to extract fields and route the result into a review queue before anything is committed.
- Human-in-the-loop by default
- A person stays in control of anything consequential. Automation drafts and proposes; people approve.
- Monitoring you can actually read
- Clear visibility into what ran, what succeeded and what needs attention — because unattended automation is only safe when it is observable.
Technology
What we build it with
We choose tools for reliability and longevity rather than novelty. For this work that usually means:
- Next.js
- TypeScript
- Node.js
- PostgreSQL
- n8n
- AI SDK
- Anthropic
- Webhooks
How we work
From first conversation to production
Audit the manual work
We measure where the hours actually go, then rank tasks by how much time and error cost automating them would remove.
Automate the highest-value path first
One workflow, done properly and running in production, before expanding. Early value beats a large plan that never ships.
Add review and observability
Approval steps where judgement is required, plus logging and alerting so failures surface immediately.
Extend as trust builds
Once the first workflow has proven itself, we widen the scope from evidence rather than optimism.
Questions
Answered honestly
- Where does AI genuinely help, and where does it not?
- AI earns its place where input is unstructured — reading invoices, PDFs and free-text forms. It is the wrong tool for steps that have clear rules, which should stay deterministic and testable. We are explicit about which is which before building.
- What happens when the automation gets something wrong?
- Anything consequential passes through a review queue, so a person approves before data is committed. Failures are logged and alerted rather than silent, and steps are designed to be safely retried.
- Can you automate between systems we already pay for?
- Usually yes, provided they expose an API or webhooks. Connecting existing systems is often cheaper and faster than replacing them, and we will say so when that is the better option.
- Does our data get sent to a third-party model?
- Only if you choose an approach that requires it, and only after we have told you plainly what would be sent and why. Where sensitive data is involved we design the pipeline to minimise or avoid that entirely.
Related services
APIs & System Integration
APIs and integrations that let your existing systems share data reliably.
Custom Business Software
Systems shaped to your operation when spreadsheets and off-the-shelf tools stop fitting.
Tell us how your business runs today.
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