Alytic AI implementation · SMBs & startups · Vancouver
We find the signal in your messy process.
Most companies don't have an AI problem. They have a process problem. Alytic diagnoses the workflow first, then builds the automation that actually gets used, or tells you that you don't need it yet.
01 How we work
We turn a tangle of manual work into a clean automated flow.
State: Manual process · 8 disconnected tasks, nothing talks to anything.
Before: eight manual tasks (email inbox, copy to sheet, manual review, chase sign-off, re-key data, fix errors, build report, send update) with no connection between them. After: a three-step automated flow. A trigger fires, AI does the work, and the result is delivered. On a workflow of this size, that returns roughly 12 hours per person per week.
The problem on the surface is rarely the actual problem.
02 What we build
Four ways we put AI to work.
Strategy through implementation. Each engagement is scoped to a measurable outcome, not a pile of tools.
AI Opportunity Diagnostic
A 5-day audit of your workflows to find where AI pays off, and where it doesn't. You leave with a ranked, costed roadmap, even if you never build with us.
/services/ai-diagnostic → 02Workflow Automation
Automate the repetitive work draining your team: intake, support triage, data entry, reporting, wired into the tools you already use.
/services/workflow-automation → 03Custom AI Tools & Assistants
Internal knowledge assistants and purpose-built tools trained on your data and grounded in your actual process, not a generic chatbot bolted on.
/services/custom-ai-tools → 04AI Enablement & Training
Get your team using AI well, with guardrails, prompts, and workflows built for their day-to-day, plus the change management that makes adoption stick.
/services/ai-enablement →03 The engagement
What you can expect.
Fixed scope, a costed roadmap you keep, and every build measured against a baseline. No slideware.
04 Industries
Where we go deep.
The process changes by industry. So does where AI actually helps. Dedicated playbooks for each.
05 Resources
Straight answers, no hype.
Original guides written to be genuinely useful, and clear enough for an AI assistant to cite correctly.
How to tell if a task is actually worth automating
A simple test using frequency, time, and error cost for deciding what to hand to AI and what to leave alone.
4 minThe AI readiness checklist for a 20-person company
What needs to be true about your data, process, and team before AI is worth the spend.
7 minBuild vs. buy for internal AI tools
When an off-the-shelf tool is enough, when you need something custom, and how to tell the difference early.
06 About
An engineer who builds, not just advises.
"The AI is the easy part. Figuring out what problem you're actually solving is where I come in."
I'm a software engineer turned AI founder. I started in engineering, building products at scale, then moved into consulting and led complex implementations across enough industries to know that the problem on the surface is rarely the real one.
I started Alytic because I kept seeing companies that wanted to adopt AI but didn't know where to start, or that bought the tools and never worked out how to really use them. The hard part is rarely the technology. It's knowing what to point it at, and getting a team to use it day to day. Sometimes the answer is a well-scoped automation. Sometimes it's "you don't need this yet." Both are useful, and honest.
07 Questions
What people ask before we start.
What size company do you work with?
Mostly SMBs and startups, roughly 5 to 200 people. Small enough that a single well-scoped automation moves the needle, large enough that repetitive work is genuinely costing you.
Do you build, or just advise?
Both. We start with a diagnostic and roadmap, then build the automations and tools ourselves. You're not handed a strategy deck and left to find developers.
How fast can we see results?
The diagnostic takes about a week. A first automation is typically live in production within 4 to 8 weeks, depending on scope and the state of your data.
What if we don't actually need AI yet?
Then we'll tell you. Part of the diagnostic is ruling things out. "You don't need this yet" is a real, money-saving answer we give regularly.
Where are you based, and do you work remotely?
We're based in Vancouver and work with clients across North America, remotely and on-site. We also work in English and Mandarin.
Let's find where AI actually pays off.
Book a 30-minute diagnostic call. We'll tell you where the opportunity is, and where it isn't.