MiseLoop

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Inspiration

Restaurant software is great at recording operations, but it still depends on managers to make decisions. Every day, restaurants respond to changing demand, expiring inventory, supplier delays, and purchasing decisions manually.

We asked a simple question: What if restaurant software became an autonomous decision layer instead of another dashboard? That idea became MiseLoop.

What it does

MiseLoop is an autonomous restaurant supply chain and operations agent.

It continuously observes operational data, identifies business risks, executes actions such as promotions, purchase adjustments, supplier coordination, and inventory transfers, then evaluates the outcome and self-corrects until operational goals are achieved.

Our demo showcases this closed-loop process through a food waste scenario, but the same architecture can support many operational workflows.

How we built it

We designed MiseLoop around a continuous decision loop:

Observe → Plan → Act → Evaluate → Self-Correct

The backend combines a deterministic risk engine, structured restaurant data, an LLM planner, executable business tools, and a restaurant simulator that generates measurable feedback. Every tool changes the application state, allowing the next iteration to learn from real outcomes instead of static prompts.

Challenges we ran into

The biggest challenge was making an AI agent truly autonomous instead of generating one-time suggestions.

We built deterministic validation, structured tool execution, and an outcome simulator so every decision could be measured before the next iteration begins.

Accomplishments that we're proud of

Built a complete closed-loop autonomous agent instead of a chatbot. Every recommendation executes real operational tools. The agent adapts its strategy when the first attempt fails. Designed an architecture that can extend beyond food waste to broader restaurant operations.

What we learned

We learned that autonomy is not about giving an LLM more freedom—it's about building reliable feedback loops around it.

The hardest problem wasn't generating actions; it was measuring whether those actions actually improved the business outcome.

What's next for MiseLoop

We're expanding MiseLoop into a broader autonomous operations platform for restaurants, including supplier management, procurement optimization, demand forecasting, and multi-location inventory coordination.

Our long-term vision is to become the autonomous decision layer that continuously improves restaurant operations through closed-loop intelligence.

Built With

• agentic
• agents
• ai
• automation
• autonomous
• chain
• decision
• fastapi
• intelligence
• language
• large
• models
• nexla
• operations
• python
• react
• sqlite
• supply
• systems
• typescript
• workflow
• zero.xyz