Inspiration

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of*Inspiration*

We noticed that in most companies, critical operational decisions — like detecting machine failures or stockout risks — still depend on manual monitoring, scattered spreadsheets, and delayed human responses. This leads to unnecessary downtime, lost revenue, and slow action. We were inspired to build a system that could identify risks early, recommend the right actions, and even execute them automatically. The goal was simple: turn raw data into real decisions.


What We Learned

  • How to design a full AI pipeline: ingestion → prediction → reasoning → action.
  • Using AI agents to break complex tasks into modular steps.
  • Building end-to-end automation using Base44 (data tables, triggers, workflows).
  • How risk scoring models work, including basic ML heuristics and feature engineering.
  • The importance of auditability, logging, and orchestrating multi-step actions.

How We Built It

  1. Created a data ingestion module to upload CSVs and convert rows into Incidents.
  2. Built preprocessing steps to clean data and compute features like [ \text{days_of_supply} = \frac{\text{stock_level}}{\text{sales_velocity}} ]
  3. Designed a Prediction Agent that assigns Low/Medium/High risk.
  4. Added a Reasoning Agent (LLM-based) that generates three prioritized actions per incident.
  5. Implemented an Orchestrator that sends alerts, creates tickets, and logs everything.
  6. Connected all components into a single flow: Incident → Prediction → Actions → Ticket → Logs

Challenges We Faced

  • Finding a clean structure to organize multiple AI agents in the right order.
  • Ensuring predictions were meaningful even with simple CSV data.
  • Designing actions that were both accurate and safe to automate.
  • Handling edge cases like missing values, inconsistent columns, and noisy data.
  • Keeping the demo simple while showing real end-to-end automation.

What we learned

What's next for Unified AI Decision Intelligence Engine (DIE)

Built With

  • base44*
  • css
  • keras*
  • matplotlib*
  • ml
  • numpy*
  • pandas*
  • python*-*-*html
  • scikit-learn*
  • tensorflow*
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