Mindshine
TIVA
Full-stack Developer · AI Platform
TIVA — Mindshine’s voice and text retrieval product — reaches data regardless of source so teams can query knowledge without a siloed search screen.
01What I built
Built client and server application layers for TIVA: React on the client, Node.js services over RPC, retrieval data in PostgreSQL and MongoDB. Profiled and debugged RPC paths under load. Assisted technical direction and coding practice — did not solely own the platform architecture.
- Client and server application layers for voice and text retrieval
- RPC profiling and debugging under load
- Persistence against PostgreSQL and MongoDB
- Technical direction and coding practice alongside the team
02Engineering proof
- Client and server application layers in one engagement
- RPC paths profiled and debugged under load
- Retrieval over PostgreSQL and MongoDB
04Problem
Voice and text retrieval had to span heterogeneous sources and stay inside existing workflows, including RPC paths that had to remain stable when load increased.
05Scale & constraints
- Heterogeneous sources feeding a knowledge base
- Voice and text retrieval in one product
- RPC stability under load
- Client and server in the same engagement; platform architecture was not solely owned
06Outcome
Client and server layers for the retrieval product shipped, and RPC paths were profiled under load. Latency numbers and source-coverage figures are not published.
- Production client and server layers for the retrieval product
- RPC paths profiled under load
07Stack
- TypeScript
- React
- RxJS
- Ramda
- Node.js
- RPC
- PostgreSQL
- MongoDB
- Cube
- Ansible
No verified public metrics are published for this engagement.
Categories: AI, SaaS
Year: 2024