AI-Enabled Business Services Strategy

Source Excerpt

Concept

Offer AI-enabled business management services as a recurring revenue model, starting with small businesses as a learning lab and expanding to municipal governments and utilities. The core infrastructure — Mac Studio, Mac Mini, 3090 worker, wiki with ~2,400 pages, team of agents — is the competitive advantage.

This is not about selling AI tools. It is about solving expensive business problems with AI as the engine, delivered as managed services with recurring revenue.

Strategic Direction

Two-Track Approach

Track 1: Small Business Operations (Learning Lab)

• Target: 5–20 person businesses (local contractors, small manufacturing, HVAC companies, dental offices)
• Goal: Learn the mechanics of delivering value and getting paid
• Pricing: Lower price points while learning
• Scope: Narrower deliverables, focused on quick wins

Track 2: Municipal Government & Utilities (Higher Value)

• Target: Small towns, municipal utilities, local government departments
• Goal: Higher-value recurring contracts with sticky vendor relationships
• Advantage: Municipalities have massive operational inefficiency, tight budgets, and actively seek cost-saving solutions
• Stickiness: Once a vendor is in, municipalities tend to stay with them

Why Not Other Models

Rejected approaches:

• Fiverr/gig work: Competing with humans in Bangladesh charging $5. Terrible margin, difficult clients.
• Report writing: Commodity — anyone with a prompt can do it. No differentiation.
• Video clipping/YouTube automation: Low-value, high-competition, platform-dependent.

Selected approach: AI-enabled business management — recurring revenue solving expensive problems.

Market Assessment

Landscape

The AI services space is crowded at the surface level — everyone is selling "AI agents" — but there is a huge gap between people who can actually deliver and people who just have a landing page. Most of the $750–$5K/mo "AI COO" and "AI bookkeeping" services are either humans pretending to be AI or AI pretending to be humans, with lots of manual work in between.

What's Actually Working

1. Customer support/lead gen agents ($1.5K–$8K/mo/client) — highest demand but most competitive
2. AI bookkeeping/finance ops ($500–$3K/mo/client) — growing fast, clear ROI
3. AI COO/operations management ($1K–$5K/mo/client) — premium positioning, requires actual delivery capability
4. Industry-specific AI workflows ($2K–$10K/mo/client) — less competitive, higher margins

The Gap

Most providers cannot actually deliver on their promises. A team with real local inference infrastructure, a curated knowledge base, and agents that can actually work represents a genuine differentiation.

Discovery Framework

A structured discovery interview is critical. The difference between "interesting idea" and "sellable package" is understanding the business's actual workflow before proposing solutions.

Key Discovery Areas

1. Current tech stack: What software do they use? (ServiceTitan, Housecall Pro, Jobber, paper?)
2. Pain points: Where do they lose time/money? (missed calls, scheduling conflicts, invoice delays)
3. Team structure: How many techs, dispatchers, office staff?
4. Customer communication: How do they handle quotes, updates, follow-ups?
5. Revenue impact: What would saving 10 hours/week be worth?

Pilot Approach

Start with a warm introduction (Lowry's) to refine the model, then scale to cold outreach on trades. The pilot validates:

• Discovery framework effectiveness
• Setup time and complexity
• Measurable ROI within 30 days
• Referenceable customer for sales

Package Components (TBD)

• Hermes Agent instance configured for their workflow
• Custom skills for their industry (scheduling, quoting, customer comms)
• Integration with existing tools (email, calendar, CRM)
• Training and onboarding
• Ongoing support retainer

Economic Model

• One-time setup fee (covers discovery + configuration)
• Monthly retainer (support + optimization)
• ROI-based pricing (percentage of time/cost savings)

Status

May 2026 update: Strategy defined, two-track approach approved. Starting small to learn the mechanics of delivery and payment. Municipal government track in parallel exploration. Not yet built or sold.

Sources

• Session 20260523_164110_ff96b5f9 — AI services strategy discussion (52 messages)
• Sessions 20260421_230904_42ecfa and 20260421_090337_5538e466 — Original small business AI packages concept