Building GM: Our Own Model, Trained In-House

Every other case study on this page is proof we can build for someone else. This one is proof we built for ourselves first. GM is the local-first AI workspace at the core of StottifAI: a model and memory system we designed, trained, and now run on hardware we control, not rented from someone else's cloud.

The goal was never a chatbot with a new coat of paint. It was a system that keeps your models, your memory, and your working context private and portable: yours on the desk where it lives, and yours again from a phone or laptop when you're not at that desk.

• Local-first architecture, no dependency on third-party inference for core use
• Persistent memory and project context that travels with you across devices
• Secure remote access from phone, Mac, or any trusted device
• A full application shell, not a demo: real navigation, real feature set, built and running
• The foundation CryptoifAI and future StottifAI products are built on top of

Design philosophy: Build the thing we'd actually want to use, prove it on our own infrastructure, then let it carry the rest of the product line.

Outcome: GM v1 is complete, functional, and live on stottifai.com. It already powers internal workflows, is the base CryptoifAI was built on, and is now ready for client-facing engagements.

CryptoifAI: An Autonomous Trading System, Built the Same Way We Build Everything

Proof of what a private, local-first AI workspace can run: an autonomous crypto trading system pairing pattern-trained models with a disciplined, always-on risk layer. Live and trading real funds since February 2026, and free to use.

• Automated market analysis across live conditions
• Risk-managed execution on every trade
• 24/7 autonomous operation, no manual intervention
• Pattern-trained models, tuned and monitored
• Free to use, no subscription required

Outcome: Live in production, trading real funds, with 8 independent risk safeguards enforced on every trade. Built on GM, and the proof that the same architecture holds up under real financial stakes.

Streamlining Operations: The BK Operations App

We designed and built a fully functional internal operations app for an international Burger King franchise operator, replacing fragmented paper checklists, verbal handoffs, and siloed systems with a single, manager-first digital hub.

The app focuses on real-world restaurant execution: shift readiness, food safety, labor efficiency, and accountability, without adding friction to already fast-paced operations.

• Daily shift checklists and punch lists tied to operational standards
• Real-time issue tracking for maintenance, cleanliness, and equipment
• Manager notes and handoff summaries between shifts
• Labor awareness tools aligned with productivity targets
• Training progression visibility for new and developing team members
• Visual accountability using photos and timestamps
• Clean dashboard views designed for quick decision-making under pressure
• Easy translation options for multi-lingual staff
• Internal AI assistant, built into the dashboard

Design philosophy: Built for speed, clarity, and adoption. Every feature was designed around how managers actually work on the floor, not how corporate systems assume they do.

Outcome: Delivered to the client and in active use across their franchise operations. Specific deployment details are withheld under client confidentiality, but the underlying architecture extends cleanly to multi-unit operations, franchise oversight, and broader QSR brands.

AI as a Thinking Partner

AI used as a strategic co-pilot for decision support, documentation, and systems thinking, with a particular focus on adoption for older adults and less tech-fluent teams.

• Industry-specific implementation versions
• Adoption-focused rollout for less tech-fluent teams
• Reframed workflows for modern environments
• Language and interface tuned for target audiences