Applied AI for Owner-Operated Businesses

Too complex for a freelancer.
Too small for an enterprise consultancy.

Airtolabs designs and builds production AI systems for owner-operated and mid-market businesses — led by a former AWS Principal Solutions Architect who's done the work inside a business like yours, not just advised from the outside.

Start a conversation See the approach
ENGAGEMENT SEQUENCE Discovery Assess & scope Architecture Design the system Build Ship production code Operate Monitor & extend
REV. 2026.07AIRTOLABS / PROCESS-01
01
What we build

Three engagement types, scoped to how much of the system you need built versus operated.

SVC.01

AI Readiness Assessment

Most owner-operated businesses don't need more AI hype — they need someone to say plainly what's worth building and what isn't.

  • Plain-language readiness review
  • Prioritized roadmap, not a slide deck
  • Realistic cost & timeline scoping
SVC.02

Customer & Ops AI Agents

Production RAG-based agents that actually reduce the manual load on a lean team — customer support, internal knowledge, order handling.

  • RAG customer support agents
  • Knowledge-base grounding & accuracy tuning
  • Built to run without a dev team on standby
SVC.03

Fractional AI & Tech Leadership

Embedded technology leadership for businesses navigating growth, transition, or ownership change — not just a consultant who leaves a report.

  • AI & technology strategy through transitions
  • Data-driven operational analysis
  • Hands-on, not slideware
02
Proof, not promises

Two engagements, both with businesses your size — not enterprise pilots that never shipped.

CLIENT TYPE
Multi-channel e-commerce company (BigCommerce, Amazon Vendor Central, Chewy, Faire) — fractional COO & AI strategy engagement, including through an ownership transition.
WHAT WE BUILT
A Claude-powered RAG customer support agent, grounded in the business's own product and policy knowledge base, running on a serverless backend — no dev team required to keep it running.
WHAT WE FOUND
Multi-year sales data analysis surfaced a structural growth gap the owner couldn't see from inside day-to-day operations — the kind of finding that changes what gets prioritized next.
SECOND ENGAGEMENT
Built a working proof-of-concept HR chatbot for an HR consulting firm's small-business clients — RAG over the employee handbook for real Q&A, not a demo script.
BACKGROUND
Two and a half years as an AWS Principal Solutions Architect before going hands-on with owner-operated businesses directly.
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