AI automation that gets your time back.

Most UK SMBs are still doing 5–20 hours of weekly admin that a 2026 automation stack can handle in seconds — copying leads between tools, drafting first-touch emails, categorising support tickets, extracting line items from PDFs, posting to socials, reconciling Stripe payouts. None of it is interesting work and none of it should be human work any more. The trick is building automations that are reliable, observable and easy to change — not brittle Zaps that break every time someone updates a field.

What modern AI automation actually does

The boring automation we've had for a decade — "when X happens, do Y" — is still useful. What changed in 2024 was the addition of an LLM into the middle of the workflow, which means automations can now: read free-text and decide what to do, generate first-draft responses in your tone of voice, extract structured data from unstructured inputs (emails, PDFs, voice notes), categorise and route based on intent, summarise long content, and even reason about edge cases. That unlocks workflows that were impossible with Zapier alone.

Workflows we build most often

Lead routing and enrichment: inbound form fill → enrichment via Clearbit or Apollo → scored by GPT against your ICP → routed to the right rep with a personalised first-email draft. Response time drops from hours to seconds. Email triage: shared inbox → GPT categorises (sales, support, billing, junk) → routes to the right channel → drafts a response in your brand voice for human review. Invoice processing: incoming PDF invoice → GPT extracts line items, totals, supplier → posts to Xero or QuickBooks → flags exceptions for human review. Meeting follow-ups: Fathom or Otter transcript → GPT generates summary, action items and follow-up email → posted to CRM and Slack. Content repurposing: blog post → GPT generates LinkedIn post, X thread, newsletter version → scheduled across channels.

Our stack

We build on Make (best value for power), n8n (self-hosted for privacy-sensitive work), or Zapier (when teams already use it). LLM layer is OpenAI, Anthropic or Google depending on the task — GPT-4o-mini for high-volume cheap work, Claude Sonnet for careful reasoning, GPT-4o for vision. Vector storage in Supabase pgvector or Pinecone where retrieval is needed. Custom code in TypeScript or Python when the off-the-shelf nodes don't cut it.

Realistic outcomes

Across recent SMB engagements: 8–15 hours per week of admin recovered, lead response time reduced from 4+ hours to under 2 minutes, support ticket volume down 30–50% through AI-handled first response, invoicing time cut by 70%, and meeting follow-up time reduced from 20 minutes to under 2. Most clients see full payback inside 6 months on time savings alone.

How we engage

Automation audit (£500–£1,200): half-day diagnostic of your operations, prioritised list of 5–10 automation candidates with ROI estimates. Single workflow build (£600–£2,500): scope, build, test, document. Automation programme (£3,500–£15,000): 5–10 workflows built over 6–12 weeks with handover and training. Ongoing retainer (£300–£1,500/month): we maintain, improve and expand your automation stack as your business grows.