Let AI sort, summarise and tag.
AI automation
In simple words: We add AI steps to your existing work so emails, forms and records get sorted, summarised and sent to the right person automatically.
Add AI steps to the workflows you already run: classify, summarise, extract and enrich data at scale with OpenAI, Claude, Gemini or open models.
For example: A team received hundreds of emails a day across sales, billing and support. Every email lands with the right owner, already summarised. See how we did it ↓
The problem
Why teams come to us
Your workflows move data, but a person still has to read, sort or summarise it before anything happens.
What you get
- AI steps inside n8n, Make or Python workflows
- Classification, summarisation and extraction
- Prompt design and output validation
- Batch processing at scale
- Cost and quality monitoring
- Documentation for your team
Benefits
What changes for your team
Removes the manual reading step
Consistent output at scale
Plugs into existing tools
Controlled costs
How it works
From first call to working result
- 1
Discovery call
A free 30-minute call to map your goal, sources, volume and where the result should land. NDA on request.
- 2
Sample first
We build a small working sample so you can check fields, format and quality before the full build.
- 3
Build & test
We build the full solution, test it on real data and edge cases, and share progress as we go.
- 4
Deliver & support
You get the result, the source code and short handover notes, plus fixes during the support window.
Example project
An inbox that sorts itself
- The challenge
- A team received hundreds of emails a day across sales, billing and support.
- What we built
- We added an AI classification step that tags each email, extracts key details and routes it to the right person with a summary.
- The outcome
- Every email lands with the right owner, already summarised.
An illustrative example of a typical AI automation engagement.
Use cases
Where this helps
Tech stack
Tools we use
FAQ
Questions about AI automation
Is AI output reliable enough?
For classification and extraction, yes, with validation rules and spot checks built in.
What does it cost to run?
Usually a few dollars per thousand items with your own API key; we estimate costs up front.
Can it use open-source models?
Yes, if privacy or cost makes that a better fit.
Related services
Often combined with
Ready to talk about AI automation?
Send a short brief or book a call. A senior engineer replies within a few hours.