Case studies
What we've built.
Every engagement delivered under a signed statement of work. Case studies below reflect real client problems, systems built, and outcomes measured.
Aug – Nov 2025
Conversational Voice Ordering System
Independent Restaurant Client
Problem
A busy small-business restaurant was losing 15-20% of call-in orders during peak lunch hours. Calls went unanswered, wait times stretched while staff juggled the phone, and employees who should have been preparing food were tied up taking orders. The restaurant needed a conversational phone system that could take orders in natural language, price them correctly, and route them to the kitchen, freeing staff to focus on the work they were hired to do.
Solution
An AI voice agent that answers the phone, sounds natural and conversational, takes the order, confirms each item and modifier back to the customer, calculates the total with tax and fees, provides an accurate pickup time, and logs the order for kitchen staff. Available every hour of every day. No missed calls. No held orders.
Flow
Call answered → order taken in natural conversation → items and price confirmed back to customer → pickup ETA provided → order logged and routed to kitchen.
Outcome
The system was built, tested, and validated end-to-end in staging. Voice quality, order accuracy, and operational fit all met the bar for launch. Production rollout was deferred due to an external platform integration constraint on the client's side.
Sep 2025
Multi-Location SKU Reconciliation
Multi-Location Convenience Client (3 retail locations)
0
SKUs audited
0.0%
of catalog flagged
0
price mismatches surfaced
Problem
Three retail locations ran the same point-of-sale system but maintained their product data independently. Pricing, categorization, and item descriptions had developed discrepancies over time across locations. The client had no consolidated view of the scope of the problem or where the financial impact was concentrated.
Solution
Collected raw SKU exports from each location, cleaned and normalized the data, then mapped every SKU into an organized master reconciliation sheet. Built an accompanying Excel dashboard for fast investigation: single-cell scan-code lookup, side-by-side 3-location comparison, and automated flagging across description, department, pricing, and price-group fields.
Findings
Of 11,608 unique SKUs, 4,737 flagged with at least one mismatch (40.8%). 1,890 retail price mismatches, with 96 single-SKU price spreads exceeding $5. Mean spread $1.24, median $0.40.
Outcome
The dashboard put every mismatch in front of the client in a format that was fast to investigate and easy to act on. The client used it to systematically standardize pricebooks across all three locations without needing to manually comb through 11,608 individual items.
In progress
Currently in build
A continued engagement with our multi-location retail client focused on automated operational integrity. The system catches financial leaks, reconciles daily shift data across registers, lottery terminals, and third-party reports, and creates verifiable audit trails.