AI Operations Systems · QSR & Franchise

The AI operating stack
Built for operators,
not corporate dashboards.

McPherson AI builds operator-first AI systems for QSR managers and franchise operators — covering labor, food cost, daily compliance, and shift continuity.

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1,000+
Downloads across live tools
Live suite
Operator-first
QSR-focused
Informed by broad restaurant operations experience
What McPherson AI Builds

Operational intelligence
that works like a GM.

Not dashboards. Not reports. AI systems that watch your operation daily, flag problems early, and give your managers the right information at the right time — before the week is over and the damage is done.

⏱
Labor Monitoring
Daily labor-vs-revenue tracking with mid-week alerts. Calculates exactly how many hours to cut before payroll closes — not after.
📊
Food Cost Diagnostics
Weekly COGS variance analysis across four control levers: ordering, portioning, recipes, and waste. Catches drift weekly instead of monthly.
✅
Daily Ops Compliance
Three-point daily compliance checks — opening, mid-shift, and closing. Builds a running record and flags gaps before they become audit findings.
🔁
Shift Continuity
End-of-shift reflection system that captures wins, bottlenecks, and handoff notes. The morning GM gets an alert. Nothing falls through the cracks.
🔍
Inventory Variance
Compares theoretical usage from sales against actual usage and deliveries. Surfaces unexplained loss before it compounds into a P&L problem.
🎯
Pre-Rush Strategy
15-minute pre-rush check-in. Confirms A-positions, surfaces call-outs, adjusts tactics for the volume ahead. Forces 60 seconds of strategic thought before the chaos starts.
Why This Exists

Most operators find out too late.

01
The P&L comes too late to act on.
By the time the monthly numbers hit, the hours are worked, the food is wasted, and the only option is "do better next week." The problem isn't the data — it's the timing.
02
Generic software doesn't think like an operator.
Most tools give you a dashboard. They show you what happened. A real operator tells you what it means, what's causing it, and what to do about it before the week ends.
03
Managers are stretched thin and information is scattered.
A shift lead shouldn't need to manually calculate labor drift while running a lunch rush. The system should catch it and surface it at the right moment — not buried in a report.
"Most operators find out they're over on labor when the P&L hits. By then it's too late. The hours are worked and the money is gone."
Blake McPherson · Founder, McPherson AI
Informed by restaurant operations experience
The Founder
Blake McPherson
Founder · McPherson AI
Background in restaurant operations, management, and information systems with a focus on workflow design, automation, and applied AI for small business operations.
Deep background in labor control, food cost management, shift performance, and team development.
Builder focused on designing practical AI-assisted systems for common frontline operational challenges.
Background in business and information systems with a growing focus on automation, infrastructure, and applied AI.

Built for operators,
not corporate dashboards.

McPherson AI exists because my background in restaurant operations made it clear how often operators are asked to solve the same workflow problems manually, under time pressure, with limited visibility and delayed feedback.

Restaurant teams regularly deal with labor drift, food cost variance, missed handoffs, audit pressure, and other blind spots that often get noticed too late. The tools I’m building are designed to surface those issues earlier, in a format operators can actually use.

I’m not building software for boardrooms. I’m building practical AI-assisted systems for GMs, shift leaders, and franchise operators who need faster visibility, better handoffs, and tighter control over execution.

This is product shaped by operational understanding — practical workflow logic turned into usable systems.

Technical Approach

Built on a serious foundation

McPherson AI runs on Anthropic's Claude — chosen for its handling of business data, output quality, and structured operator workflows. Each client deployment runs on its own isolated infrastructure, so store data stays scoped to the store.

The agent layer, memory architecture, skill design, and operational guardrails are McPherson AI's work. Anthropic's models provide the inference layer; the operator-specific intelligence — what the system knows about how a store actually runs — is built and maintained by us.

The system is engineered for cost discipline. Prompt caching, structured compression, and a multi-agent architecture keep per-client infrastructure costs predictable, which is what allows founder pilot pricing to stay flat instead of metered.

Anthropic states that, by default, inputs and outputs from commercial products such as the Anthropic API are not used to train its models. Anthropic also states that standard API inputs and outputs are generally deleted from its backend within 30 days, subject to listed exceptions. McPherson AI separately scopes each client deployment through isolated infrastructure, workspace, memory, secrets, and messaging bindings.

QSR Operations Suite

Live tools and upcoming releases.

McPherson AI is building a growing suite of operator-focused systems for labor, food cost, compliance, handoff, and execution. Current live tools are listed alongside upcoming releases.

Live
Daily Ops Monitor
Three-point daily compliance — opening, mid-shift, closing. Running record. Gap detection.
Live
Food Cost Diagnostic
COGS variance analysis. Four-lever diagnosis. Catches drift before the monthly P&L.
Live
Labor Leak Auditor
Daily labor tracking. Mid-week alert with hours-to-cut calculation. Clock padding detection.
Live
Ghost Inventory Hunter
Theoretical vs actual usage comparison. Surfaces unexplained loss before it compounds.
Live
Shift Reflection
Three questions at close. Captures wins, bottlenecks, and handoff notes. 5am alert to morning GM.
Live
Audit Readiness
30-day audit prep protocol. Daily compliance system designed to improve consistency and readiness.
Live
P&L Storyteller
Variance narrative with diagnostic hierarchy. Plain-language explanations for owners who don't live in the numbers.
Live
Pre-Rush Coach
15-min pre-rush check-in. A-position confirmation. Tactical adjustments for the volume ahead.
Early Signal

The market is moving.
We're already in it.

1,000+
Downloads across the first live QSR tools — early traction without paid distribution.
Niche
One of the only publishers focused specifically on QSR manager operations on the platform.
Industry demand is documented.
Nation's Restaurant News reported that 37% of restaurant operators plan to adopt automated labor management and recruitment systems. A Harri survey cited by Nation's Restaurant News found that scheduling and labor optimization was the top-ranked area where hospitality professionals believed AI could provide operational value.
Enterprise is already moving this direction.
Yum China is piloting Q-Smart, an AI-enabled assistant for restaurant managers at select KFC restaurants, with support for labor scheduling, inventory management, and food quality and safety inspection.
First-mover position in an underbuilt niche.
QSR manager operations is still an underbuilt niche, and McPherson AI is among the early focused publishers in the category.
Now opening conversations with early pilot operators.
San Diego market, Q2 2026. Small number of QSR and franchise locations — setup included.
Get Started

Let's talk about
your operation.

McPherson AI deploys tailored AI operator systems for QSR teams, configured to your workflow and delivered through simple interfaces your managers can actually use. If you're managing a high-volume location and want to catch problems before the week is over — reach out directly.

Email Blake Directly Browse the skills on ClawHub →