AI adoption consulting

Use AI where it pays off, with tools that fit how you already work.

I help smaller companies find where AI is worth using, pick the right tools, and connect them to the systems they already run. Then I measure whether it helped.

The call is 30 minutes, free, and needs no preparation.

Book a callSee how it works
  • Less repetitive work
  • Faster turnaround for clients
  • More from the tools you already pay for
Portrait of Guy Pavlov

Guy Pavlov

Founder, Rel-AI-able. MBA. Based in Toronto, working with clients worldwide.

Most firms have tried AI. Few have it working day to day.

Large companies can hire in-house engineers, and they have the budget to match. Smaller firms usually cannot. I fill that gap.

I am a principal engineer who has done this work at Intel, Qualcomm, and Dapper Labs, and I do the implementation myself, for a fraction of an enterprise engagement.

65% of SMEs using generative AI report better employee performance, but only 26% report higher revenue.

OECD, Generative AI and the SME Workforce (opens in a new tab), November 2025.

Who I work with

I work with small and mid-sized businesses in any sector, usually with 10 to 50 people. That size is a typical fit, not a rule.

Credentials

  • No 90-page decks.
  • No 12-month roadmaps.
  • No long discovery phase.
  • No vendor kickbacks.
  • No resold platforms.

Results

A marketing agency's SEO audit

The audit meant nine separate manual tools before anyone could build the deck.

I set up an AI-assisted draft the team could review.

4 to 7 hours per audit became under an hour of review.

Read the write-up

Weekly client reporting

Raw website data still needed a person to turn it into a recommendation.

I connected the reporting workflow so the draft arrives ready for review.

70% less manual analytics work.

Read the write-up

Lead qualification

Qualifying leads took a long stretch of repetitive calls.

I set up a calling workflow that handles the first pass and hands exceptions to a person.

90% less lead qualification time.

Read the write-up

What clients say

  • “The multilingual capabilities of the chatbot have increased our user engagement and satisfaction. Moreover, it helped improve our productivity.”

    Ivano Perrone, CEO, IPT SolutionsChatbot write-up

  • “He was responsive, resourceful, and communicated well with both our team and clients.”

    Amanda Lambert, Trustcore TechnologiesAnomaly detection write-up

  • “I am happy, the generated insights are helpful and the code looks well organized.”

    Daniel PisterziAnalytics reporting write-up

What the work looks like

Screens from projects I built. Each one links to its write-up.

An answer from a chat assistant: a table of dealers with lead counts, then notes on the row count and missing values.
Ask questions of your own data

A question typed in plain English, answered from the database with notes on the data.

An Italian-language company website with a chat assistant open in the corner, greeting the visitor in Italian.
Multilingual chat assistant on a company website

Visitors ask about the company's services and get an answer in their own language.

A completed workflow run that picks up pending sites, starts an audit for each one, waits, and marks it processed.
SEO audit automation

The queue that works through a list of sites. Each audit took 4 to 7 hours by hand.

What I do

  1. 01

    Find where AI is worth using.

    I look at how the work actually gets done and find the tasks where AI saves real time.

  2. 02

    Pick the right tools.

    Off the shelf, built, ordinary automation, or no AI at all. I start from the problem, not a product.

  3. 03

    Connect and set it up.

    I connect the tools to your email, documents and client systems, and train the team to use them.

  4. 04

    Measure whether it helped.

    We agree the success measure before starting and check the result against the baseline.

How to start

Start with an AI Adoption Review. Setup follows from that review. A working session on one real task lives in the Ongoing AI Advisor.

About 1 to 2 weeks

AI Adoption Review

This is the start. Fixed fee. If the review finds no workflow where AI pays off, you don't pay.

After the review

Setup & Integration

Fixed scope. It starts with a measured pilot on one workflow, then checks the result after 2 to 4 weeks of use.

Monthly

Ongoing AI Advisor

A working session on one real task, each month, plus a note on hours, cost, and what changed.

What does the repetitive work cost?

The figures below are an example: 4 people, 6 hours a week, 75 USD an hour, hoping to recover 30%. Replace any figure. This does not assume a result from my projects.

Hours each month
104
Monthly cost of that time
$7,800
If that percent comes back
31.2 hours, about $2,340 a month
Book a call

Not sure where AI fits yet?

That's the normal starting point. Bring one task that takes your team too much time, and we'll work out whether AI can help. 30 minutes, free, no preparation needed. I'll tell you on the call if there's no opportunity.

Book a call

Guy Pavlov The call is with me.

Engineering teams have their own page.