Our Work Speaks
for Itself

A modular cybersecurity platform combining Suricata IDS, multi-agent AI orchestration, and real-time visualization to enable proactive threat detection and fully automated incident response. LLMs power the threat classification engine, providing human-readable risk assessments and actionable recommendations.

• Real-time network traffic analysis via Suricata IDS integration with AI correlation engine
• Multi-agent orchestration for parallel threat investigation and automated response playbooks
• LLM-powered threat classification with contextual risk scoring and severity ranking
• Secure Linux desktop app for team collaboration, live dashboards, and incident tracking

A multi-agent AI legal assistant leveraging RAG pipelines over vast legal corpora and fine-tuned LLMs trained on jurisdiction-specific law to deliver intelligent contract analysis and real-time legal guidance — making expert legal reasoning accessible at scale.

• Smart contract analysis with clause-level risk identification and plain-language summaries
• RAG over legal databases for real-time case precedent retrieval and citation generation
• Fine-tuned LLMs on jurisdiction-specific legal language for accurate domain understanding
• Multi-agent pipeline: intake → research → analysis → drafting → review agents in sequence

A real-time sports analytics platform using state-of-the-art computer vision to deliver professional-grade coaching insights. Tracks players, ball trajectory, and game dynamics from match footage — transforming raw video into actionable performance data used by coaching teams.

• YOLOv8-based multi-object detection for simultaneous player and ball tracking at 30+ FPS
• Ball trajectory analysis with physics-informed path prediction and speed calculation
• Player positioning heatmaps, movement patterns, and court coverage analytics
• Match dynamics dashboard with serve speed, rally statistics, and performance scoring

An intelligent financial analysis platform powered by multi-agent AI that ingests real-time market data, earnings reports, and news sentiment to deliver data-driven stock recommendations. Combines quantitative models with NLP-driven sentiment analysis for a comprehensive investment intelligence layer.

• Real-time market data ingestion with automated technical indicator computation and signal generation
• NLP sentiment analysis over financial news, earnings calls, and social media feeds
• Multi-agent orchestration: data agent → analysis agent → recommendation agent → risk agent
• Interactive dashboard with portfolio tracking, risk scoring, and explainable AI insights

A production-grade conversational AI system designed to autonomously handle customer support workflows across industries. Integrates with CRM systems, knowledge bases, and ticketing platforms to resolve queries end-to-end — escalating only edge cases to human agents.

• Intent classification and entity extraction with 95%+ accuracy across multi-domain queries
• RAG-powered knowledge retrieval over product docs, FAQs, and policy databases
• CRM and ticketing integration for automated case creation, updates, and resolution logging
• Multilingual support with context-aware handoff protocol for complex human escalations

A scalable, enterprise-grade recommendation system that combines collaborative filtering, content-based signals, and LLM-augmented personalization to deliver hyper-relevant product, content, or service recommendations at millions-of-users scale.

• Hybrid recommendation architecture: collaborative filtering + content embeddings + LLM reranking
• Real-time user behavior ingestion with sub-100ms recommendation serving at scale
• A/B testing framework with automated metric tracking and model performance dashboards
• Modular design supporting cold-start handling, seasonal trends, and diversity injection