AI Workflow Integration | Smart Automation Across Your Stack

At a glance

What is AI Workflow Integration?

AI Workflow Integration adds an AI decision layer to the tools your team already uses. Instead of replacing your stack, I connect it: automated triggers, Claude-powered decision logic, and handoffs between systems like Notion, Airtable, Slack, Make.com, Zapier, Google Workspace, and your CRM. The result is a smarter pipeline running on infrastructure you already pay for.

What's included

Every engagement ships with.

Stack audit + workflow map
I map every tool you use, where data lives, and where the handoffs between them break down. You get a visual diagram of the current workflow and the target workflow.
AI decision layer
A Claude-powered middle layer that reads inputs from one tool, reasons about them, and writes outputs to another. Routing, categorisation, summarisation, classification.
Integration with existing tools
Native connections to Notion, Airtable, Slack, Make.com, Zapier, Google Workspace, and most REST APIs. No rip-and-replace.
Trigger + schedule setup
Event-driven triggers (new row, new message, webhook) or scheduled runs (daily, weekly). Whatever matches the workflow.
Error handling + logs
Every run is logged. Failures trigger alerts, not silent drops. You always know what the system did and when.
Handoff documentation
A clear writeup of every connection, every API key, every credential, and how to swap any of them when something changes.

Fit Check

Is this service right for you?

Both columns matter. Read them before booking.

This fits if…

Your team already uses several tools and moving data between them eats real hours.
You want the AI layer inside your existing stack, not a separate app to learn.
You have repetitive manual classification, routing, or summarisation tasks.
You are willing to provide API access to the tools I need to connect.

This is not for you if…

Your workflow depends on legacy desktop software with no API access.
You want a visual drag-and-drop builder you can edit yourself (use Make.com or Zapier directly for that).
You are not sure what tools you want to keep and would rather start fresh.
Compliance rules prevent cloud-based AI processing of your data.

Process

How it actually runs.

01

Audit

A free 30-minute call plus a short stack audit. I review every tool in play and where the time loss actually happens.

02

Design

I produce a one-page workflow diagram showing the current state, the target state, and every integration point in between.

03

Build

Integration layer built and wired up, typically one to two weeks depending on how many tools and APIs are involved.

04

Shadow run

The new workflow runs alongside the old one for a few days so you can compare outputs and catch edge cases before cutover.

05

Go live

Cutover to the new workflow with your team on the call. Documentation handed over. Two-week bug-fix warranty starts.

Stack

Built with.

Claude API Python Make.com Zapier Notion API Airtable Slack API Google Workspace Webhooks REST APIs

Live Example

See this in production.

A real system running right now, built on this exact service.

Case Study · Live

Automated Sector Research Briefing

A scheduled Monday briefing built for a Paris architecture firm. Pulls from multiple news sources, reasons with Claude, and delivers a structured report to the team inbox every week without human involvement.

Read Case Study

FAQ

Before you book.

Do you integrate with Zapier and Make.com?

Yes, both. I use Zapier and Make.com as connectors when the right fit. The AI reasoning layer runs on the Claude API, and Zapier/Make handle the event triggers and simple data moves. You get the best of both: code-level intelligence where it matters, no-code glue where it is cheaper.

Can you integrate with our existing CRM or database?

If it has an API, yes. I have integrated with HubSpot, Airtable, Notion, Google Sheets, Supabase, PostgreSQL and several custom internal databases. For legacy systems without an API I can often use a CSV export / import loop as a fallback.

How do API keys and credentials stay secure?

Credentials live in environment variables or a secrets manager (never in code). You own every key. I do not store, copy or retain any credential after delivery. On handover you rotate keys and the system keeps running with the new ones.

What happens when one of the connected tools changes its API?

Major tools (Notion, Slack, HubSpot, etc.) maintain stable APIs and rarely break backward compatibility. For the ones that do, I document every integration point so you or any developer can patch it quickly. Maintenance retainers are available for ongoing coverage.

Is this the same as building a custom AI automation from scratch?

No. AI Automation Systems build a new pipeline end to end (usually in Python). Workflow Integration adds an intelligence layer to the tools you already have. Most clients start with Integration because it is faster and reuses existing infrastructure, then move to full Automation for the workflows where a custom pipeline is genuinely worth it.

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