AI Automation.
Workflow automation that uses AI where judgement is genuinely needed, and simple rules everywhere else.
What this covers.
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Process mapping to find where automation actually saves time
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AI-assisted steps for tasks needing judgement - classification, summarisation, drafting
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Straightforward rule-based automation for the rest, since it is more reliable and cheaper to run
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Integration with the tools your team already uses daily
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Monitoring so failures are caught, not discovered a week later
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Iteration as your processes change
A clear process from idea to launch.
Four stages, each ending in something you can see, click or sign off.
- 01/
Discovery & data prep
We review your ticket history or workflow and identify which parts are genuinely safe to automate.
DELIVERABLEWritten scope, timeline and fixed price
- 02/
Agent design
Response logic, escalation rules and a strict "say I don't know" policy, reviewed with your team before any live testing.
DELIVERABLEAgent design document
- 03/
Build & shadow mode
The agent runs alongside your team for two weeks, visible only to you, before it touches a live customer.
DELIVERABLEWorking agent in shadow mode
- 04/
Live rollout & tuning
Gradual rollout starting with the lowest-risk categories, with weekly review of every escalation.
DELIVERABLELive agent, monthly report and backlog
The right stack for your automation.
We choose what your team can maintain. If a simpler tool does the job, we will say so.
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AI & AGENTS
- OpenAI API
- Anthropic API
- LangChain
- Vector databases
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AUTOMATION
- n8n
- Zapier
- Make
- BullMQ
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INTEGRATIONS
- Zendesk
- HubSpot
- Salesforce
- Slack
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INFRASTRUCTURE
- AWS
- Node.js
- PostgreSQL
- Sentry
Questions about AI Automation.
Answers to what clients ask us most before a project starts. Don't see yours here - just ask.
Contact Us01/ Does everything need AI, or just some of it?
No - we use AI only where genuine judgement is needed and plain automation for everything else, since it is more reliable and predictable.
02/ How do you measure whether automation is actually working?
Baseline metrics agreed before launch, then measured against real usage after - time saved, error rate, or volume handled.
03/ What happens when our process changes?
Automations are built to be modified, not thrown away - we typically retain a support relationship to adjust them as needed.