AI Integration for Brick & Mortar Operators

Your Operations. Made Intelligent.

Your team is already using AI. The question is whether it's structured, secure, and actually making them better at their jobs — or whether it's a collection of personal ChatGPT accounts leaking your IP into training data.

Generic rollouts fail. Most AI tools get rolled out and quietly ignored — the license gets bought, the tool gets opened once, and then the team drifts back to how they always worked.

We do it differently.

Three Problems Nobody Wants to Talk About

Someone in the org needs to own this. Not the IT department. Not the CEO who read an article. A real person who understands the workflows and has the credibility to drive adoption. Most rollouts skip this step entirely.

No Champion

Buying licenses isn't a strategy. Without individual intake — actually learning how each person works — you're guessing at what tools to deploy and how to configure them. Guessing is what produces the tool nobody opens twice.

No Process

Enterprise agreements, zero data retention, permission trees, usage policies. The security and governance layer that turns "employees using AI" into "employees using AI safely." Skip this and you have a material risk sitting in every browser tab.

No Structure

Person by Person. Workflow by Workflow.

6 weeks from kickoff to operational.

Pitch

Executive Intake: 60 min with leadership. Org structure, tools, pain points, shadow AI audit.
Champion Selection: 3-5 internal champions identified and scored.
Workforce Intake: 60-90 min per employee. Multi-category work classifications.
Engagement Prep: Risk assessment, tool recommendations, estimate, implementation proposal.

Phase 1 — Pitch

Intake

Individual Sessions: 60-90 min per person. Written intake classifies work into five categories — delegate, manual, repetitive, research, math/data.
Scenario Mapping: Natural conversation validates what the form captured and surfaces hidden workflows.
Tool Matching: Dev Pack or Office Pack assigned based on role, technical level, and intake profile.
Deliverables: Completed intake records, shadow AI risk report, tool recommendation matrix.

Phase 2 — Intake

Ops Engagement

Backend Setup: Enterprise agreements, zero data retention, permission trees, usage policies.
Unit Setup: Personalized install per employee — Dev Pack or Office Pack based on intake profile.
Training: One-on-one, hands-on, using their actual workflows.
Agent Creation: Global logic blocks → role patterns → individual workflows. All tested before handoff.

Phase 3 — Ops Engagement

Ongoing

Cost Reporting: Monthly spend reports by tool, team, user. Budget vs actual with trend lines.
Seat Optimization: Quarterly usage audits. Who's active, who's idle, reallocation recommendations.
Pattern Maintenance: Pattern library reviewed and updated on every model release. Version control, cleanup.
Adoption Review: Quarterly executive briefing. ROI analysis, expansion recommendations, new hire onboarding.

Phase 4 — Ongoing

Every Hour From Us Multiplies Your Team

Every hour of AI integration work multiplies the efficiency of each employee it touches. This isn't a cost — it's a force multiplier across your entire operation.

Compounding

Leverage on every workflow it touches

Daily

Measurable time back, every single day

6 weeks

From kickoff to operational

Meta just made AI usage a KPI requirement for every employee. This isn't the future — it's the expectation. The question is whether your team is structured for it or scrambling to catch up.

Built for Operators, Not Tech Companies

Mid-market operators (20–500 employees)

Multi-location businesses — restaurants, retail, hospitality

Franchise groups with standardized operations

Commercial real estate — property managers, developers, contractors

Any brick & mortar business where the work happens in the real world

Straightforward Pricing

Intake & Setup

Flat fee. You know the cost before we start. Covers executive intake, workforce intake, tool setup, training, and pattern library build.

Ongoing Optimization

Time and materials. Monthly cost reporting, pattern maintenance, seat optimization. Billed for actual hours worked.

No retainers for work that isn't happening. No minimums. No long-term contracts unless you want one.

What It Actually Looks Like

Week 0

Executive intake. 60 minutes. Shadow AI risk assessment.

Weeks 1–2

Champion intake, backend setup, enterprise agreements.

Weeks 3–4

Full workforce intake. Individual sessions with every employee.

Weeks 5–6

Training, pattern library handoff, governance docs. Team is operational.

Month 2+

Ongoing optimization. Monthly reports, quarterly reviews.