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Chennai, Tamil Nadu, IndiaB.Tech CSE · VIT Chennai

Nithish Kannan M

I build AI systems that remember, retrieve, and know when to stop — hybrid retrieval, predictive memory orchestration, and reliability for agent loops.

01

What I work on

Memory

What a system keeps, what it forgets, and what it costs to be wrong about either. Predictive memory orchestration and contradiction-aware stores.

  • Ring Zero
  • ex_mem

Retrieval

Getting the right context in front of the model, and knowing when you haven't. Hybrid dense-plus-lexical retrieval and confidence-based routing.

  • Modular Memory Unit
  • adaptive-rag-router

Knowing when to stop

Systems that recognise their own failure to progress and halt, rather than burning tokens producing the appearance of work.

  • Plateau
02

Selected work

activeJan 2026 — Present

Modular Memory Unit

Hybrid retrieval RAG framework

A retrieval framework that fuses dense and lexical signals with Reciprocal Rank Fusion, benchmarked on legal and compliance documents across five custom metrics including faithfulness and cross-document reasoning.

  • Python
  • FastAPI
  • BGE-M3
  • FAISS
  • BM25
Retrieval signals fused
3
BGE-M3 · FAISS · BM25
Custom eval metrics
5
incl. faithfulness, cross-doc reasoning
Target venue
EMNLP/ACL
Student Research Workshop
shippedApr — May 2026

Ring Zero

Predictive memory orchestrator

A predictive memory orchestrator pairing a multi-modal next-context transformer with a PPO-trained cgroup v2 tier policy. Beat the Android App Standby Buckets baseline on both warm rate and latency at a fixed 400MB budget.

  • Python
  • PyTorch
  • PPO
  • cgroup v2
  • PSI telemetry
Warm rate
90%
86% App Standby Buckets
Latency
192ms
217ms App Standby Buckets
Memory budget
400MB
fixed constraint for both systems
activeJun — Jul 2026

ex_mem

Contradiction-aware shared memory server (MCP)

An MCP memory server that treats a changed fact as evolution with preserved history rather than an overwrite — aimed at a benchmark gap where every system evaluated scores in single digits.

  • Python
  • MCP
  • SQLite FTS5
  • sqlite-vec
  • LLM-judge
Best FactConsolidation score
≤7%
across all 22 systems evaluated
Systems evaluated
22
MemoryAgentBench
Retrieval stack
2
SQLite FTS5 + sqlite-vec
shippedJul 2026

Plateau

Semantic circuit breaker for AI agents

A detector that trips on semantic information stagnation rather than textual repetition, so autonomous agent loops can be stopped when they stop making progress — not merely when they start repeating themselves.

  • Python
  • Sentence embeddings
  • pytest
Passing tests
121
validation suite
Live demo
2machines
distributed, at the hackathon
Distribution
pip
installable package `plateau`

Mechanisms from the work above, rebuilt as things you can drag. Free, no signup — if one of them saves you an afternoon, it did its job.

04

Experience

05

Writing

Get in touch

Open to internships, research collaboration, and conversations about memory and retrieval systems.