Case studies

Real agents.
Real SMEs.
Real numbers.

Five production deployments across retail, finance, logistics, e-commerce, and manufacturing. Each with a baseline measured before we started, and the same metric measured ninety days later.

Retail · Canada2025
+38%
conversion in 90 days

Challenge

A 180-person retail group was drowning in inbound leads — 1,200+ a month — with response times averaging 28 hours. Reps were copy-pasting into a CRM that nobody trusted.

Solution

We shipped a sales-automation agent that ingests leads from web, email, and phone, scores them against ICP rules and historical wins, drafts personalized outreach, and hands the top 25% directly to AEs in Slack with full context. Predictive analytics flag deals at risk.

Results

28h → 41m
First response
+38%
Conversion
$1.4M
Pipeline added

The agent does in 41 minutes what took our team a full day. The wins started in week three.

VP Sales · 180-person retail group
Financial services · Toronto2025
0
bytes of data egress

Challenge

A regulated Toronto financial-services SME needed AI-powered analysis of confidential client data, but compliance prohibited any data leaving the premises. Off-the-shelf cloud LLMs were a non-starter.

Solution

We deployed an open-source LLM (Llama 3 70B) fine-tuned on their corpus, running on-premise on their existing GPU rack. The agent extracts patterns from financial documents and predicts compliance trends — all data stays inside the building, air-gapped from the internet.

Results

100%
Data sovereignty
9× faster
Doc analysis
PASS
External audit

We finally got to use modern AI without rewriting our data-handling policy. The auditors approved on the first review.

Chief Compliance Officer · Financial services firm
Logistics · Ontario2026
214h
recovered per week

Challenge

A regional freight carrier (40 trucks, 60 staff) was losing 5+ hours per shift on dispatch coordination — phone calls, weather checks, route reshuffles. Mistakes propagated into late deliveries and SLA penalties.

Solution

An agent that perceives load board, weather, traffic, and driver hours-of-service; reasons over delivery windows and contract priorities; acts by drafting dispatch decisions for the human dispatcher to approve in one click. Reflects on outcomes nightly to improve next-day plans.

Results

214h
Saved / week
−62%
Late deliveries
5.3 FTE
Equivalent recovered

The dispatcher used to leave at 9pm. Now she's home for dinner and we deliver more loads.

Operations Manager · Regional carrier
E-commerce · DTC apparel2026
68%
tickets auto-resolved

Challenge

A 70-person DTC apparel brand had a six-person support team buried under 4,000 tickets a month — order status, sizing, returns. Hiring more agents wasn't keeping up.

Solution

A support agent connected to Shopify, the warehouse WMS, and the returns portal. It can answer where-is-my-order, process exchanges, and write returns labels — escalating only true edge cases to humans. Tone-matched to the brand voice with eval gates on every prompt change.

Results

68%
Auto-resolved
CSAT 4.6
Up from 4.1
$220k
Annual savings

The team finally has time to do customer-driven product work. Support is no longer the bottleneck.

Head of CX · DTC apparel
Manufacturing · Hamilton2026
−47%
defect escape rate

Challenge

A specialty parts manufacturer (220 employees) had a quality problem — defects slipping past final inspection and reaching customers. Manual review of inspection notes was inconsistent across shifts.

Solution

An agent that reads inspection notes and shop-floor logs, cross-references against historical defect patterns, flags high-risk batches for re-inspection, and writes a daily quality digest for the plant manager. Runs on-prem due to IP-sensitive process data.

Results

−47%
Defect escape
$185k
Warranty saved
−23%
Re-work hours

Same team, same equipment — but the agent catches what tired humans miss at 4am.

Plant Manager · Specialty parts mfg.
Could be your story next

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