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AI Enablement

Your team is busy. Most of it shouldn't be.

We put AI to work across your funnel and back office — automating the repetitive, deploying agents where they pay back, measured in hours saved and revenue moved.

Book an AI readiness callSee what we automate
Agent activity
3 agents running
Weekly performance report
Claude · Notion
4 min
Support ticket routing
Claude · Zendesk
<2 min
Content tagging & QA
Claude · Notion
Auto
Hours returned this week
−23 hrs

Trusted by Startups, Scale ups, and Brands

The real problem

Most AI pilots never leave the slide deck.

Teams buy tools, run a demo, and stall. The model isn't the hard part — adoption, data, and measurement are.

AI Enablement is for leaders who want AI in production, not in theory. We find the workflows where AI pays back fastest, ship them into daily operations, and prove the result with numbers your CFO will accept.

  • 01

    Licences nobody uses

    Adoption is flat and the ROI case never quite closed.

  • 02

    No baseline, no measurement

    "It's working" is a feeling — not a number your CFO will accept.

  • 03

    Ungoverned data

    Knowledge is scattered — agents can't be trusted to act on a mess.

What we deliver

AI that ships into the work — not onto a shelf.

Six pillars that move AI from experiment to dependable, governed operation.

How we work together

One sprint, shipped and adopted.

AI Enablement Sprint

Audit · build · adopt
Book a readiness call
Best for

Teams drowning in manual ops, brands with AI tools nobody uses, or leaders who want agents in production with proper governance.

You'll get
  • Ranked AI opportunity map
  • Two to three shipped automations
  • Adoption playbook & guardrails
  • Measured before/after baseline
Timeline
6–8 weeks
Outcome
Shipped & adopted
Measured, not promised

AI that shows up in the numbers.

High-volume DTC retailer

“Convx didn't sell us a model — they rebuilt how our merchandising and support teams work. The reporting agent alone gave us back two days a week, and the experiment pipeline finally keeps up with the calendar.”

Head of Digital & Operations
AI Enablement Sprint client
−60%
Manual hours on reporting
3.2×
Experiment velocity
Is this for you?

AI Enablement is built for teams that…

  • Lose hours to manual busywork

    Reporting, tagging, QA, and content ops eat time your team should spend on growth.

  • Bought AI tools nobody uses

    Licences are live, adoption is flat, and the ROI case never quite closed.

  • Want agents, safely

    You're ready for automation but need a human in the loop and clear guardrails.

  • Sit on messy data

    Knowledge is scattered across tools, so AI can't yet act on your truth.

  • Need proof, not promises

    You want a measured before-and-after, not a vendor's optimistic deck.

Before & after

What changes when AI is in production.

Function
Before
After
Weekly performance reporting
8 hrs manual — Analyst
30 min — Agent drafted
Content tagging & QA
12 hrs/week — 2 people
<1 hr — Automated
Support triage & routing
First response: 4–6 hrs
<5 min — Agent routed
A/B test variant generation
2–3 variants/week
12–15 variants/week
Good to know

Common questions.

Do we need a data team or platform in place first?
Do we need a data team or platform in place first?
How do you keep this safe and compliant?
How do you prove it actually worked?
What happens after the sprint?

Find the AI that pays for itself.

We'll review your workflows and data, then show you the two or three automations worth shipping first. No hype, just the payback.