EvolTech.

01—Toronto—MMXXV—Est. 2021

AI
that
ships.

We design, build, and operate AI agents and custom software for teams that measure what ships: cycle time, conversion, cost per transaction.

Book a 30-min discovery callSee services

Fig. 01 / Evoltech Agent

Running

№TimeEvent
0114:02Classified 24 inbound tickets — 18 billing, 6 account
0214:03Drafted 21 replies — awaiting reviewer
0314:04Escalated 3 edge cases — policy ambiguity
0414:06Reconciled 142 invoices — 0 exceptions
0514:07Updated 12 shipment statuses — tracking sync

Handle time1.8s↓ 68%

Illustrative

Reference workflow — inbound triage, reply drafting, escalation, reconciliation

—Selected clients—

Canada Goose
Roots Canada
DBS
Geodis
SDR

Wordmarks shown. Official trademark logos rendered only where per-brand usage permission is on file.

02—Services

Four practice areas.
Each earns the next.

  1. 01
    AI Solutions
    →
  2. 02
    Custom Software
    →
  3. 03
    Mobile Apps
    →
  4. 04
    Web Platforms
    →

03—Industries

Markets we
know well.

01 / Retail & eCommerce

Challenge
Inventory signals, personalization, and checkout-path conversion.
What we do
Demand forecasting, merchandising agents, and experiment loops.

02 / Logistics

Challenge
Route complexity, tracking reliability, and margin pressure.
What we do
Route optimization, real-time telemetry, and exception workflows.

03 / Healthcare

Challenge
Data sensitivity, fragmented workflows, and patient engagement.
What we do
Compliant portals, document agents, and integration plumbing.

04 / Finance

Challenge
Risk, auditability, and decision latency across customer journeys.
What we do
Decisioning agents, fraud signals, and trustworthy data pipelines.

05 / Startups

Challenge
Running fast without painting into an architectural corner.
What we do
MVPs you can grow into — modular scaffolds and honest cuts.

06 / Internal tools

Challenge
Brittle spreadsheets and tribal-knowledge workflows that slow teams.
What we do
Replace them with observable systems that your team uses.

04—Engagement patterns

Three common
shapes of work.

P01Logistics · 3PL

Inbound exception triage

Problem
Thousands of daily tracking exceptions flowing into shared inboxes, eating ops-team hours.
What we build
LLM-classified exceptions with auto-resolution for known patterns; structured routing for the rest.
8 weeks + retainer1 PM · 2 Eng
P02Retail · Apparel

Catalog ops acceleration

Problem
Seasonal catalog updates spread across marketing, merch, and web — measured in weeks.
What we build
Agent-driven catalog staging with automated copy & image QA and a reviewer dashboard.
12 weeks · Build-operate1 PM · 2 Eng · Design
P03Healthcare data

Document ingestion pipeline

Problem
Fragmented document ingestion across 8 partner systems with inconsistent schemas.
What we build
Document-understanding agent with compliant audit trail and human override for low-confidence cases.
10 weeks + 6mo operate1 PM · 2 Eng

05—How we work

Four phases.
No mystery.

  1. 01

    Discovery.

    We map your workflow, KPIs, constraints, and what "better" would actually look like. You leave the first week knowing what the engagement is for.

    1–2 weeks
  2. 02

    Architecture.

    Scope, data model, integration surface, and the smallest first slice worth shipping. Documented in writing; everyone signs off on the shape of the work.

    1–3 weeks
  3. 03

    Engineering.

    Weekly demos, reviews, CI, and a clear definition of done. If a scope cut becomes the right call, we raise it early — never in the final sprint.

    4–20 weeks
  4. 04

    Deployment.

    Production rollout with monitoring, runbooks, and an honest handover. Optional ongoing operation where it makes sense.

    Rolling

06—Stack

The stack we
reach for.

01 / Frontend

Interfaces that stay fast as features grow.

  • ›React
  • ›Vue / Nuxt
  • ›TypeScript
  • ›Tailwind

02 / Backend

Services and data layers that are easy to operate.

  • ›Node.js
  • ›Python
  • ›PostgreSQL
  • ›Supabase

03 / Cloud

Infra that scales with the business, not against it.

  • ›AWS
  • ›Azure
  • ›Docker
  • ›Vercel

04 / AI / ML

LLM-first, classical ML when it earns its place.

  • ›OpenAI / Anthropic
  • ›RAG pipelines
  • ›TensorFlow
  • ›PyTorch

07—Metrics

What moves.
Nothing else.

01/Cycle time
From request to working software in user hands. Shorter loops compound.
02/Cost per transaction
Unit economics the CFO sees. Unambiguous and measurable.
03/Conversion
The user action your business depends on. Instrumented, not guessed.
04/Operator hours
Where humans belong in the loop. And where they don't.
Let's pick the number we'd move first →

08—What clients say

Straight talk.
From people we worked with.

Published anonymously by role and industry at our clients' request. Named references available for serious conversations.

№ 01

"They rebuilt our inbound classification in six weeks. We'd spent a year trying to do it internally."
VP Engineering
Canadian apparel retailer · ~200 employees

№ 02

"The exception-routing workflow paid for itself in the first quarter. Our ops team got their afternoons back."
Head of Operations
North American 3PL

№ 03

"They told us what not to build, not just what to build. That judgment is worth the engagement on its own."
CTO
Canadian healthcare data platform

09—Let's talk

Start with a
conversation.

A 30-minute discovery call, no obligation. We'll share what we'd build, how long it would take, and what it would cost.

We reply within one business day.