Hi HN! I built BrainPredict because I was frustrated with cloud-only AI solutions that require sending sensitive business data to third parties.
What it does:
- 445 specialized AI models covering 16 business domains (finance, HR, sales, supply chain, etc.)
- Runs 100% on-premises - your data never leaves your infrastructure
- Intelligence Bus architecture that lets AI models share insights across platforms
- Works completely offline once installed
Tech stack:
- Python backend with FastAPI
- XGBoost, Prophet, LSTM, BERT for predictions
- No external API calls (OpenAI, etc.) - fully autonomous
- PostgreSQL + Redis
The models predict things like:
- Revenue (95% accuracy)
- Customer churn (30 days ahead)
- Employee turnover risk
- Inventory needs
- Cash flow
brainpredict•49m ago
What it does: - 445 specialized AI models covering 16 business domains (finance, HR, sales, supply chain, etc.) - Runs 100% on-premises - your data never leaves your infrastructure - Intelligence Bus architecture that lets AI models share insights across platforms - Works completely offline once installed
Tech stack: - Python backend with FastAPI - XGBoost, Prophet, LSTM, BERT for predictions - No external API calls (OpenAI, etc.) - fully autonomous - PostgreSQL + Redis
The models predict things like: - Revenue (95% accuracy) - Customer churn (30 days ahead) - Employee turnover risk - Inventory needs - Cash flow
Live demo: https://brainpredict.ai/demo/live
I'd love feedback on the approach. Is on-premises AI something enterprises actually want in 2025?