Mera / NuSeat — AI Job Matching Platform
Dynamic LLM-powered job matching with L-Trees algorithm
One example subsystem from this build. In most engagements we deliver the entire stack top to bottom — application code, Docker, infrastructure, deployment, and scaling — all in-house. Where a client already has platform teams in place, we work alongside them.
Project Summary
A job matching platform built at NuSeat using the novel L-Trees algorithm — a dynamically-sorted categorical tree powered by LLMs. The tree's state guides the LLM in asking the right questions to match candidates with job postings. Later evolved into CL-Trees (chronological variant for memory) and ultimately DynamicContextObjects built on pgvector.
Our role: AI Engineering
What We Did
- Novel L-Trees algorithm for dynamic LLM-guided categorization
- CL-Trees chronological variant for temporal memory
- DynamicContextObjects abstraction (pgvector-based)
- Overlap with key ideas in Microsoft's GraphRAG
Want something like this?
Describe what you'd build and get a scoped plan with a budget — drafted in minutes, confirmed by a human.
Scope Your Project — Free