AI Lab
AI Engineering Lab & Research.
Models
Open models built for Indic languages.
Med360 Lite
Medical AI assistant for Indian healthcare with Hinglish support. 173K+ training examples.
SLM360
On-device AI that thinks, learns, and remembers. 50MB, 39ms latency, 100% offline.
2 models
Research
Read our technical papers on Med360 and SLM360 architecture, training methodology, and benchmarks.
Technical Report • 2025
Med360: A Family of Fine-tuned Multilingual Medical AI Assistants for Indian Healthcare
We present Med360, a family of fine-tuned large language models designed specifically for Indian healthcare contexts with native Hinglish support, Indian pharmaceutical nomenclature, and AIIMS/NEET-PG level medical knowledge.
Technical Report • 2025
SLM360: Breaking the NLU Trilemma - Accuracy, Latency, and Efficiency On-Device
A lightweight NLU engine achieving 98-100% accuracy at 39ms latency in 50MB -4x faster than Rasa, 10x less memory. Hybrid classification with reasoning, memory, and prediction, all on-device.
Technical Report • 2026
AgentGuard: Deadlock Prevention for Multi-AI-Agent Systems via Extended Banker’s Algorithm
A C++17 library that extends Dijkstra’s Banker’s Algorithm for LLM agent orchestration — with progress monitoring, authority cycle detection, and adaptive demand estimation. 285 tests, LangGraph integration.
Technical Report • 2026
VAJRA: A Multi-Sensor On-Device Counter-UAS System with Custom-Trained Visual and Acoustic Deep Learning Models
A fully on-device, multi-sensor drone detection and neutralization system running on a commercial Android smartphone. Integrates visual (YOLOv8n), acoustic (FFT + CNN), and RF analysis -fused into a unified threat display with countermeasure control. 38MB APK, zero network dependency.
Technical Report • 2026
KAVACH: An On-Device Tactical Intelligence Platform with SLM360-Powered Natural Language C2, Real-Time ISR, and Automated Reporting
A tactical intelligence platform running entirely on Android with zero network dependency. Integrates Tactical C2, ISR Processing (YOLOv8n, ~19 FPS), Auto SITREP (SALUTE reports in ~8s), and Patrol Optimization -all powered by SLM360 (577K params, 848KB).
5 papers
Blog
Technical deep-dives and engineering insights.
Blog Post • February 2026
12 min readYour LangGraph Agents Are Deadlocking. Here’s the Fix.
How we applied a 60-year-old OS algorithm to prevent deadlocks in multi-AI-agent systems. A practical guide to using AgentGuard with LangGraph.
1 post
Quick Start
Get started with Med360 in just a few lines of code.
1from med360 import Model2model = Model("360labs/med360-hindi")3# Generate response4response = model.generate(5prompt="मुझे बताओ",6max_tokens=2567)