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Your competitors are already automating. The question is whether you're ahead or behind.

AI isn't coming — it's already running in your competitors' operations. The gap compounds. Getting it right the first time matters more than getting it fast.

Automation that works is invisible — processes run without manual input, errors don't compound and your team focuses on work that requires judgment rather than repetition. Getting there requires understanding the process before automating it: a well-designed workflow is transformative; a broken process automated at scale is just broken faster.


What's included

  • AI chatbots & assistants

    Website, WhatsApp and customer support — trained on your business, not a generic FAQ bot.

  • Workflow automation

    Make, n8n, Zapier and custom integrations — connecting your tools so manual steps disappear.

  • Lead qualification automation

    Scoring, routing and responding to leads without a human in the loop for the repetitive parts.

  • CRM & sales automation

    Follow-ups, pipeline management and notifications — so nothing falls through the gap between conversations.

  • AI-assisted content pipelines

    Generation, review workflows and publishing — structured so AI accelerates your team rather than replacing judgment.

  • Custom AI integrations

    OpenAI, Anthropic Claude, Google Gemini and others via API — connected into your existing tools and workflows.

  • Process audit

    Map manual workflows, estimate time spent and identify what's actually worth automating before writing a line of code.


Technologies & platforms

OpenAIAnthropic ClaudeGoogle GeminiMaken8nOpenClawZapierLangChainPythonNode.jsAPIs ...and others

How we approach it

  1. Process audit

    Map the workflows you want to automate, measure time spent and identify which are genuinely worth the investment before writing any code.

  2. Tool & architecture selection

    Choose the right automation stack based on your tech environment, data sensitivity and budget.

  3. Build & integration

    Automations built, connected to your existing tools and tested in a staging environment before going live.

  4. Testing & edge case handling

    Real-world testing across normal and edge cases — failure states handled gracefully, not silently.

  5. Handover & documentation

    Automations documented, your team trained and monitoring configured so you know when something needs attention.


The uWeb angle

What we do differently.

We've seen AI implementations that created more work than they saved — usually by automating a broken process, which makes it broken faster at scale. We clean up the process first. Knowing when not to automate is as valuable as knowing how. This is one of the areas where senior experience matters most.

GDPR & AI data processing.

When AI systems process personal data — customer queries, lead details, user behaviour — GDPR applies fully. We build automations with data minimisation and purpose limitation built in from the start, not added as an afterthought.


Common questions

We're not a tech company — can we still benefit from AI?
Yes. The businesses seeing most value from automation are often non-technical ones with manual, repetitive processes — quoting, follow-ups, scheduling, data entry. We handle the technical side.
How do we know what's worth automating?
That's exactly what the process audit answers. We map your workflows, estimate time spent and identify where automation has the highest ROI — before writing a line of code.
What does an AI project cost?
Anywhere from a few hundred euros for a simple automation to ongoing retainers for complex integrations. The process audit scopes it properly before any commitment.

Ready to talk about ai & automation?

No commitment required. We'll tell you honestly if we're the right fit.

Let's talk about AI & Automation →

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