Projects
A collection of infrastructure projects, platform engineering solutions, and ML systems I've built to solve real-world problems at scale.
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Aether
A production-ready Safe GenAI Platform integrating content safety, traffic governance, ML inference, and real-time observability into a unified system.
- Unified Architecture: Orchestrates Sentinel, Atlas, Hyperion, and MonitorX into a cohesive GenAI platform.
- End-to-End Safety: Every request passes through content moderation before and after inference.
- Production Observability: Real-time metrics, alerting, and dashboards for complete visibility.
- One-Command Deploy: Docker Compose setup brings up the entire stack with health checks and dependencies.
Sentinel
A production-grade AI supervision layer that acts as a firewall for LLMs. Enforces compliance, safety, and quality standards in real-time.
- Live Supervision: Intercepts and audits LLM responses before they reach the user.
- Pluggable Policies: Define custom rules for Healthcare (HIPAA), Finance, or Brand Tone.
- SaaS Architecture: Built with a secure API Gateway pattern using RapidAPI and Google Cloud Run.
- Monetized API: Fully integrated billing and quota management system.
Atlas
A sophisticated LLM traffic and quota management gateway built with Redis, FastAPI, and Prometheus. Enables intelligent model routing, request limiting, and comprehensive observability for AI applications at scale.
Key Features:
- Real-time quota management and rate limiting
- Intelligent model routing based on load and cost
- Comprehensive metrics and monitoring
- High-performance async architecture
Guardian
A semantic firewall for Autonomous Agents. Intercepts and validates tool calls, analyzes generated code (AST), and enforces business logic policies before execution.
- Semantic Firewall: Blocks dangerous agent actions (SQL injection, RCE) before they happen.
- Policy-as-Code: Dynamic rule engine to enforce business logic (e.g., “No refunds > $100”).
- AST Analysis: Statically analyzes generated Python code to detect forbidden imports or syscalls.
- Sentinel Integration: Deep integration with Sentinel for content safety inspection.
Hyperion
High-performance ML inference platform with GPU acceleration and intelligent request batching. Achieves 10-50ms inference times with 10x+ throughput improvements through dynamic batching and Kubernetes-native autoscaling.
Key Performance Features:
- GPU acceleration: 10-50ms inference times (10x faster than CPU)
- Intelligent batching: 10x+ throughput with dynamic batch sizes
- Advanced Kubernetes scaling: HPA, VPA, and KEDA support
- Production monitoring: Prometheus metrics and real-time observability
System Metrics
Strategos
A durable agent orchestration engine. Features an event-sourced workflow kernel, tiered context memory, and Model Context Protocol (MCP) integration.
- Durable Execution: Event-sourced workflow engine that survives infrastructure failures.
- Cognitive Architecture: Pluggable reasoning loops (ReAct, Plan-and-Solve) decoupled from the runtime.
- MCP Integration: Native support for the Model Context Protocol to standardize tool connectivity.
- Context Virtualization: Automatic tiering of agent memory (Working Memory vs. Vector Storage).
MonitorX
Comprehensive ML/AI infrastructure observability platform with zero-code monitoring, intelligent alerting, and real-time drift detection. Provides complete visibility into production ML systems with enterprise-grade dashboards and automated model health monitoring.
Key Features:
- Real-time model performance monitoring and drift detection
- Intelligent multi-channel alerting with automated remediation
- Interactive dashboards with A/B testing and model comparison
- Cost optimization insights and resource utilization tracking
MonitorX Dashboard
AerialView
Interactive stock market analytics dashboard with real-time visualizations, candlestick charts, and technical indicators powered by Streamlit.
Technology Stack
Technologies and tools I use to build scalable, reliable systems