Case Studies

We Listen

A logistics company with 16 field managers across the country. The accounting person spent 12 hours/week manually processing expense reports—creating folders, downloading receipt images, transcribing data, and filing everything. The owner couldn't get managers to use expense software, so email with photo attachments was the only workflow that worked.

We Audit

We observed the accounting workflow for a morning. The email-with-photos method was actually smart—low friction for busy field managers. The problem was everything after the email arrived: manual data entry, folder creation, filing. Work that had to happen but was wasting expensive talent on tasks far below their skill level.

We Design

Design a system that keeps the manager workflow exactly the same (email photos) but automates everything on the back end. Two micro-automations working together: one to extract data from receipt images using AI vision, another to automatically organize files and folders without human touch.

We Implement

Result: Improved Business

The accounting person stopped being a data entry clerk and became the financial strategist the company actually needed—finally doing cash flow forecasting, vendor analysis, and profitability reports.

We Listen

A 10-person home generator company in Quebec. Two salespeople (including the owner) drowning in call volume. 40% of every callback was spent explaining pricing to tire-kickers—3 minutes explaining costs, 2 minutes qualifying interest, 5 minutes booking. Qualified leads waited hours while salespeople educated window shoppers.

We Audit

We tracked the callback workflow. The owner wanted to automate pricing explanations so he could skip to booking. But the real bottleneck was the entire callback cycle—voicemail delays, repetitive explanations, back-and-forth scheduling. Two salespeople at capacity, but not enough volume to hire a third.

We Design

Design a system that answers calls immediately—no more voicemail purgatory. AI handles the entire first touch: pricing explanation, qualification, and booking. Salespeople only talk to pre-qualified buyers with confirmed appointments. Two micro-automations: AI voice for instant response and natural conversation, auto-scheduling to remove booking friction.

We Implement

Result: Improved Business

The sales team stopped being pricing lecturers and became actual salespeople—closing deals instead of explaining kilowatts. No third salesperson needed.

We Listen

A mailroom operations manager in New York City with 4 positions and rotating new hires. They had SOPs and know-how documents, but everything was scattered—buried in physical file piles, lost on servers, or trapped in veteran employees' heads. New hires spent 10-15 minutes searching for answers to basic questions, often giving up and interrupting busy colleagues.

We Audit

We reviewed their training process and gathered all relevant documents. The problem wasn't missing information—it was unfindable information. Documents existed but were functionally useless because employees couldn't access them quickly. When people left, their knowledge walked out the door. The manager needed a way to compile everything in one place where it wouldn't get lost again.

We Design

Design a private RAG (Retrieval-Augmented Generation) system that employees can access anytime. Two micro-automations: one to continuously ingest new documents and prevent them from getting lost again, another to enable instant knowledge retrieval through natural language chat so employees get answers in 30 seconds instead of 15 minutes.

We Implement

Result: Improved Business

Scattered piles became a living knowledge system. New hires train themselves. Veterans' tacit knowledge is captured before they leave. Documents finally serve their purpose.

We Listen

A dog supply store owner with 4 Las Vegas locations believed deeply in fairly rewarding his team. But with 3-4 employees rotating across stores simultaneously, figuring out who drove sales was a nightmare. The only hard data came when an employee logged into the POS register—ignoring the floor staff who actually helped the customer decide. He spent 8-12 hours weekly cross-referencing scheduling data with sales spikes to guess who was performing, but the results were opaque and delayed by weeks.

We Audit

We mapped the data silos: Homebase (scheduling) and Square (POS). The owner was making educated guesses, meaning high performers were being overlooked simply because they weren't the ones ringing up the transaction. The transparency he valued was impossible without finding hidden correlations between foot traffic, shift overlaps, and category-specific sales spikes—a puzzle no human could solve manually in a reasonable timeframe.

We Design

Design a system that continuously ingests data from both platforms and uses statistical modeling to attribute sales influence even when staff aren't logged at the register. Two micro-automations: an ETL pipeline that unifies scheduling and transaction data, and an AI analysis engine that weights store busyness, shift compositions, and product categories to score true performance fairly.

We Implement

Result: Improved Business

The owner now relies on fair, defensible performance insights that account for the complexity of rotating staff. Employees trust the system because it acknowledges floor work, not just register log-ins. Best of all, rewards are given in real-time, keeping morale consistently high across all four stores.