AI decision-support for retail small businesses

Illuminating business decision hiding in your data.

Affordable AI-powered decision support for retail small businesses — turning fragmented data into timely, actionable recommendations.

Mobile-first · Conversational · Built for stores without a data team

Point of sale Inventory E-commerce LUMORA INSIGHT Restock oat milk before Saturday — demand is up 34% versus last month.
The problem

Five screens to make one decision.

Sales, stock, and online orders each live in a different system. By the time it's pieced together, the moment to act has often passed.

Fragmented systems

Data in five places

POS, inventory, and e-commerce tools rarely talk to each other.

No analyst on staff

No time to dig

Owners are on the floor, not building spreadsheets.

Enterprise pricing

Priced out of analytics

Enterprise tools assume enterprise budgets and IT teams.

Reactive, not proactive

Decisions arrive late

Most tools wait to be asked, after the shelf is empty.

The product

Three capabilities, working together.

Lumora connects the tools a store already runs on, and turns what they know into something a person can act on immediately.

Integration

Lightweight business connectors

Low-cost connectors that pull data from the POS, inventory, and e-commerce systems small businesses already use.

Context

A unified business context

Sales, stock, location, and local signals organized into one coherent picture — not another dashboard to read.

Decisioning

An AI decision engine

Conversational analytics and proactive recommendations, explained in plain language.

Technology

How fragmented data becomes one decision.

POS Inventory CRM Shopify Business Context Builder AI Decision Engine Mobile-first Assistant Operational Decisions
Business Context Decision Engine Mobile-first Affordable AI Security
9:41 · Lumora
Ask Lumora

"How's the store doing today?" — Foot traffic is 22% above average for a Saturday, driven by the farmers market next door.

Recommendation

Feature your bestsellers near the entrance — nearby event traffic tends to convert well on impulse items.

Notification

Cold brew concentrate: 2 days of stock left at current pace.

Our approach

Built for the floor, not the back office.

  • Recommendations surface in the moment, wherever the decision is made.
  • Reusable architecture keeps deployment fast and pricing affordable.
  • Business rules and lightweight ML handle routine tasks; LLMs are used where they add real value.
  • Faster responses, stronger privacy, lower cost.
Three-year plan

From first pilot to industry impact.

A deliberately staged path — validate with real stores first, then commercialize, then scale.

Year 1

Platform development & pilot validation

Technology
  • Lightweight connectors for POS, inventory, and customer management
  • First production-ready AI decision engine
  • Mobile-first release, starting with iOS
Customer validation
  • 3–5 pilot deployments with retail small businesses
  • Real operational scenarios: inventory, store management, customer engagement
  • Feedback loop into usability and recommendation quality
Business
  • Establish the U.S. business entity
  • Build relationships with local business organizations
  • Bring on AI and ML technical advisors
Year 2

Commercialization & customer growth

Technology
  • Expanded connectors and operational workflows
  • Behavioral analytics enrich business context
  • Refined notifications and recommendations from usage data
Commercialization
  • Launch the first commercial SaaS release
  • Grow to roughly 10–20 paying small business customers
  • Standardized onboarding and support processes
Growth
  • Expand cloud and retail technology partnerships
  • Hire the first engineer or implementation specialist
  • Recurring subscription revenue established
Year 3

Scaling, partnerships & broader impact

Technology
  • Decision engine improves on accumulated usage patterns
  • Stronger scalability, security, and admin capabilities
  • Coverage for workforce coordination and store performance
Expansion
  • Explore adjacent small business sectors with similar needs
  • Grow through standardized SaaS and implementation partners
  • Continue hiring engineering and customer teams
Contribution
  • Publish best practices on AI decision-support systems
  • Present at industry conferences and webinars
  • Explore intellectual property opportunities
Insights

Writing on AI, retail, and decision intelligence.

Blog

How AI Can Help Retail Small Businesses

Coming soon
Whitepaper

Business Context vs. ChatGPT

Coming soon
Blog

Reducing AI Cost

Coming soon
Whitepaper

Decision Intelligence

Coming soon
Long-term vision

A trusted digital operating companion for customer-facing small businesses.

Retail is the start, not the ceiling — the same architecture extends to restaurants, cafés, and other local businesses built on real-time decisions.