Advanced implementations of GPT-4 agents with function calling, assistants API, and custom tools integration.
Enterprise-scale Vertex AI agents with Gemini models, leveraging multimodal capabilities and grounding.
Cognitive Services agents with Azure OpenAI, orchestrated through Logic Apps and Function Apps.
Multi-agent collaboration frameworks enabling specialized agent teams for complex problem-solving.
Agents that independently analyze complex scenarios, evaluate options, and execute decisions with human-level reasoning capabilities.
Sophisticated workflow agents that break down complex tasks, delegate to specialized sub-agents, and synthesize results.
Dynamic agents that learn from interactions, adjust strategies on-the-fly, and optimize performance through continuous feedback loops.
Seamless agent deployment across cloud providers, on-premise systems, and edge devices with unified orchestration.
End-to-end agentic system design for enterprise deployments
Multi-modal inputs
Context enrichment
Intent recognition
Task decomposition
Agent selection
Resource allocation
Parallel processing
Tool invocation
State management
Short/Long-term memory
Knowledge graphs
Experience replay
Result aggregation
Quality assurance
Human feedback
Multi-tier agent system handling 100K+ daily queries with 95% resolution rate without human intervention.
Autonomous development agents that generate, test, and deploy production-ready code with built-in quality checks.
CrewAI-powered research teams conducting market analysis, competitive intelligence, and trend forecasting.
Real-time market analysis agents processing millions of data points for algorithmic trading decisions.
Medical agent assistants analyzing patient data, suggesting diagnoses, and recommending treatment paths.
Autonomous agents managing inventory, predicting demand, and optimizing logistics across global networks.
• Novel agent memory architectures enabling infinite context retention
• Cross-framework agent communication protocols
• Self-improving agent systems with automated performance optimization
• Core contributor to major agentic frameworks
• Published agent benchmarking suites adopted industry-wide
• Maintained libraries with 15K+ GitHub stars
• Architected agent systems processing $2B+ in transactions
• Reduced operational costs by 75% through agent automation
• Mentored 100+ engineers in agentic AI development