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Mera / NuSeat — AI Job Matching Platform

Dynamic LLM-powered job matching with L-Trees algorithm

Mera / NuSeat — AI Job Matching Platform architecture schematic

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

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