Aletheia is a technical system for retrieval quality, evaluation loops, search observability, and AI-assisted knowledge workflows.
Stack, status, evidence, and public actions are rendered from the typed project record.
Category
AI Systems
Type
Platform
Priority
Flagship
Overview
What this project is
Aletheia is a technical system for retrieval quality, evaluation loops, search observability, and AI-assisted knowledge workflows.
Problem
Why it matters
Modern search and retrieval systems need more than keyword matching. Retrieval quality, ranking behavior, evaluation feedback, and observability need to be visible in one system.
Solution
Approach
A hybrid retrieval and search observability platform direction that combines API surfaces, retrieval backends, background jobs, database state, and evaluation-oriented architecture.
Architecture
System shape and stack
Architecture
Retrieval quality as an observable system
The project is framed around retrieval, reranking, evaluation, and operational visibility rather than a single chat surface.
System Shape
Backend, index, and evaluation loops
The stack points toward API services, database state, background queues, vector search, keyword search, and evaluation workflows working together.
- Python
- FastAPI
- PostgreSQL
- Redis/RQ
- OpenSearch
- Qdrant
- SQLAlchemy
- Alembic
- Docker
- Next.js
Technical Highlights
Visible technical signal
- Hybrid retrieval system direction
- Reranking and evaluation workflow
- Search observability surface
What It Proves
Builder signal
Ability to design AI and search infrastructure beyond a simple chatbot wrapper.