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Pillar 03 · AI & Automations

Practical AI.
Properly applied.
Hours saved.

We've shipped real AI automations that save real hours — not slide decks and "AI strategy workshops". Custom GPT/Claude assistants, document processing, internal chatbots, RAG on your own data, and quiet workflow automations that run while you sleep.

MODELS & TOOLS:
Anthropic ClaudeOpenAIMicrosoft CopilotLlama · Mistraln8nPower AutomateZapier · Makepgvector
§ 01 — What we ship

Six shapes of AI work,
most of the time.

Almost every engagement is one of these six patterns. We'll tell you which one fits your problem on the first call, and which models we'd reach for.
/01 — ASSISTANTS

Custom Claude / GPT assistants on your own knowledge.

An internal chat your team can ask "what's our holiday policy?", "what did Acme buy in 2023?", "draft a follow-up email like Mo wrote last time" — answered from your handbook, your CRM, your past correspondence. Citations included.

/02 — AUTOMATIONS

Workflows that quietly run while you sleep.

"When this email arrives, extract the data, file it in Notion, ping Slack, and update Xero." Boring repetitive work, automated end-to-end. We use Power Automate, Make, n8n, Zapier — whichever your team can pick up if we step away.

/03 — DOCUMENTS

Extract structured data from PDFs & emails.

Invoices, claim forms, contracts — read, parsed, filed, and routed without a human keystroke.

/04 — SEARCH

Semantic search over your internal docs & tickets.

Find the right policy, ticket, or precedent by description — not by remembering the exact filename.

/05 — CHATBOTS

Customer-facing chat. Knows what to escalate.

On your site, in your product, or inside Intercom — with sane guardrails and a human in the loop.

/06 — AGENTS

Light-touch agents that take actions across your stack — with a human approving every change that matters.

Off-switch included. Every action is logged, reversible, and gated behind explicit human approval where it matters.

§ 02 — Before & after

Manual workflow → automated, end to end.

A composite of what a typical claims-triage workflow looks like before we touch it, and the same workflow running with Claude in the loop a fortnight later.
Before · manual triage
  • PDF claim arrives in shared mailbox at 8 a.m.
  • Two operators read every form, full pass takes 45 min
  • Manually copy policy number into the underwriter's system
  • Cross-reference paid status in a separate spreadsheet
  • Triage summary typed into a Notion page
  • Slack the duty manager when something urgent appears
After · Claude in the loop
  • Claude reads the PDF and extracts the structured fields
  • Policy number cross-referenced against the system in one call
  • Triage summary drafted, with citations to the source PDF
  • Reviewer reads the summary in 7 min and approves payout
  • Urgent claims auto-routed to the duty manager's Slack DM
  • All decisions logged · every step reversible · off-switch in place
USE CASE · B2B SaaS · 60 seats

Sales-call follow-up, written like the rep would

After every Zoom call, an n8n flow pulls the transcript, drafts a follow-up email in the rep's writing style (trained on their last 200 emails), updates HubSpot with next-step fields, and queues the email in their drafts. Rep edits and sends. Pipeline velocity up 22%.

2.8 hrs
Saved per rep / day
§ 04 — Also see

Pick a related thread.

AI builds usually need a place to live, an app to live inside, and someone keeping an eye on the whole thing.
PILLAR 01

Managed IT & Cloud

We'll run the cloud your AI lives on.

Read more
PILLAR 02

Web & App Development

The product around the AI — UI, auth, billing.

Read more
PILLAR 04

Technology Consulting

AI readiness audits, vendor selection, second opinions.

Read more
Ready when you are

Got a repetitive task?
Let's see if AI can take it.

Send us a process you're tired of doing by hand. We'll spend 30 minutes on a video call mapping it, and tell you honestly whether AI would help — or whether you just need a better spreadsheet.

A director will reply within 4 business hours · Mon – Fri, 9 – 6 UK