Portfolio
AI Engineering & Research Portfolio
Showcasing our contributions to the AI and machine learning ecosystem through research, engineering projects, and open-source initiatives.
Research & Publications
AI Agent Evaluation Frameworks
Comprehensive analysis of benchmarking methodologies for autonomous AI systems, focusing on production deployment metrics and reliability assessments.
Vector Database Performance Analysis
In-depth engineering study of vector database performance characteristics, covering latency, recall trade-offs, and cost optimization strategies.
Engineering Projects
AgentOps Framework
Production-ready observability and reliability framework for AI agent deployments, including monitoring, retry logic, and cost optimization tools.
Multi-Step Reasoning Evaluator
Open-source toolkit for evaluating LLM reasoning capabilities across various domains, with support for chain-of-thought and tree-of-thought methodologies.
Consulting & Advisory
We provide strategic guidance and technical expertise to organizations building AI systems at scale.
- • AI strategy development and technical roadmap planning
- • Production deployment architecture and best practices
- • Performance optimization and cost management
- • Team training and capability development