Case studies
What we've built.
Every engagement delivered under a signed statement of work. Each case below gives the problem, what we built, and what came of it.
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 the people who should have been cooking were taking orders instead. The restaurant needed a phone system that could handle an order in natural conversation, price it correctly, and send it to the kitchen.
Solution
An AI voice agent that answers the phone, takes the order in natural conversation, confirms each item and modifier back to the customer, calculates the total with tax and fees, gives an accurate pickup time, and logs the order for kitchen staff. It runs every hour of every day, so no call rings out and nobody sits on hold.
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
We built the system and validated it end to end in staging. Voice quality, order accuracy, and operational fit all met the bar for launch. Rollout to production was deferred because of an integration constraint with an outside platform 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 separately. Prices, categories, and item descriptions had drifted apart over the years. Nobody had a consolidated view of how big the problem was or where the money was going.
Solution
We collected raw SKU exports from each location, cleaned and normalized the data, then mapped every SKU into a master reconciliation sheet. Alongside it we built an Excel dashboard for fast investigation: single-cell scan-code lookup, side-by-side comparison of all three locations, and automatic flagging across description, department, pricing, and price-group fields.
Findings
Of 11,608 unique SKUs, 4,737 flagged with at least one mismatch, or 40.8% of the catalog. That included 1,890 retail price mismatches, 96 of them with a single-SKU spread above $5. The mean spread was $1.24 and the median $0.40.
Outcome
The dashboard put every mismatch in front of the client in a form they could investigate quickly. They used it to standardize pricebooks across all three locations without combing through 11,608 items by hand.
Jun 2026 – In progress
Restaurant Intelligence
Internal product, deploying soon
What it is
A question-and-answer tool that lets a restaurant operator ask plain questions about their own business and get answers backed by their own numbers. It reads their sales history alongside what's happening locally, then tells them what's coming and how to staff and stock for it.
Problem
Operators have their sales data and a rough sense of the local calendar, but nothing puts the two together. No single place turns months of orders into clear patterns, lines them up against the events that change how busy a week gets, and shows where each answer came from. A generic chatbot will just make something up, which is the last thing you want behind a staffing or ordering call.
Where it stands
The core is built and working against live sales data. An operator can ask a question and get a sourced answer, pull up a sales dashboard, and see a calendar of upcoming local events with a read on how each one is likely to affect traffic. What's left is tightening the pieces that make it dependable enough to hand to a client.
How it works
The rule it runs on is that it never guesses. Every answer has to point back to a real source, and anything it can't back up it declines to answer rather than fill in the blank. That is what makes it safe to put behind a real operating decision.
Jul 2026 – In progress
Marketing Operations Platform
Deploying to two independent restaurant clients soon
What it is
One platform that runs a local business's whole marketing operation: its website, social posts, email and texts, review replies, online ordering, and the reporting that ties it all together. Each business switches on only the parts it needs.
Problem
A small operator usually pays for a handful of separate services to keep any marketing going, and still ends up with a few generic posts a month for the money. Everything lives in a different tool, the content is thin, and more often than not the business doesn't even own its own website when it's done.
Where it stands
The first business is being built out now: the content, the owner's approval step, posting to social and email, and online ordering. Catering, text marketing, and a reporting dashboard come next. Every piece is optional, so no two client setups look the same.
How it works
At the center is a content engine that drafts as many posts as each channel needs, far more than the services it replaces, and checks its own work so the posts don't all start to sound alike. Nothing publishes on its own. The owner sees the day's queue on their phone and approves, edits, or skips in a couple of minutes.