When Harvest House — a fast-growing restaurant chain with 14 locations across the Midwest — first reached out to us, their operations manager had a simple ask: "We're drowning in spreadsheets. There has to be a better way."

There was. But first, we had to understand exactly what was consuming their team's time.

The problem: time lost in spreadsheets

Over two weeks of discovery, we shadowed the operations team, interviewed location managers, and mapped every recurring task touching their back office. The team was collectively spending over 40 hours per week on tasks that followed predictable, repeatable patterns.

The biggest time sinks were inventory reconciliation across 14 locations, weekly supplier order generation, manual data entry between POS and accounting software, and compiling daily waste logs and performance reports.

What we built

We designed three interconnected AI agents. The Inventory Intelligence Agent connected to their POS and inventory tool via API, ran nightly reconciliation, and flagged discrepancies automatically. The Supplier Ordering Agent generated draft purchase orders each Thursday using historical sales data, weather forecasts, and upcoming event calendars — managers reviewed and approved in under five minutes. The Reporting Pipeline automatically compiled and distributed a clean leadership report every Monday at 7am. No human touched it.

The results

Six weeks from kickoff, all three agents were live across all 14 locations. The operations team reclaimed 38 hours per week — time reinvested in opening two new locations within the same quarter. Food waste dropped 23% as ordering became data-driven.

Interested in what this could look like for your food business?
Talk to our team

Hartwell & Partners is a 60-attorney commercial law firm specializing in M&A, real estate, and corporate transactions. When their managing partner approached us, the conversation was candid: "Our associates are burning out on contract review, and we're worried about quality when people are exhausted."

A utilization analysis showed junior associates spending 55–65% of billable hours on first-pass contract review — work that was essential but mechanical. Identifying non-standard clauses, flagging missing provisions, checking definitions against a master playbook. Necessary. Exhausting. Expensive.

The challenge: accuracy is everything

Legal AI is a domain where the stakes of error are uniquely high. A missed indemnification clause can cost clients millions. Any system we built had to be auditable, explainable, and designed to assist attorneys — not replace their judgment.

The system we designed

We built a Contract Intelligence Layer sitting between document ingestion and attorney review. When a contract is uploaded, the system maps every clause against the firm's 340-page internal playbook, flags deviations with plain-English explanations, and generates a structured review memo — color-coded by risk — in under four minutes. Every flag cites the specific playbook clause it's comparing against. Nothing is a black box.

Rollout and adoption

We piloted with four associates across two practice groups for six weeks before firm-wide rollout. Attorneys who were initially skeptical became advocates once they saw the system catch a clause they had missed in a live document review.

Associates previously handling eight matters simultaneously now manage twenty-four — without longer hours. The firm redirected time toward client-facing work and complex analysis.

Thinking about AI for your legal practice?
Let's have a conversation