AI Agents Development

Building Custom AI Agents

Designing intelligent agents that work autonomously and collaborate efficiently across your systems. Our approach combines proven architectural patterns with cutting-edge AI capabilities.

MCP-Ready Agents

Build agents that speak the Model Context Protocol—the standard for AI-to-AI communication. Seamlessly integrate with Claude, GPT, and other LLMs. Define custom tools, manage complex prompts, and handle multi-turn conversations with full context awareness.

Multi-Agent Orchestrators

Coordinate teams of specialized agents to solve complex problems. Router agents direct tasks, specialist agents execute them, aggregator agents combine results. We architect orchestration patterns for:

• Hierarchical workflows: Supervisor agents managing task delegation
• Collaborative teams: Agents sharing knowledge and voting on decisions
• Competitive patterns: Multiple agents solving the same problem, best solution wins
• Graph-based flows: Conditional routing, loops, and dynamic task generation

Edge AI on Raspberry Pi & IoT

Deploy intelligent agents on resource-constrained devices. Perfect for factories, smart homes, and field operations. We optimize models, implement local reasoning, and manage cloud fallbacks when needed.

A2A Communication

Agents that call other agents asynchronously. Error handling, retry logic, timeout management, and graceful degradation built in. Each agent maintains its own state and can operate independently or as part of a larger system.

RAG-Powered Agents

Agents with access to your knowledge bases. Semantic search, reranking, and fact-grounding ensure accurate context-aware responses. We combine vector search with business logic for reliable automation.

Tech Stack

• Languages: Python 3.11+
• Frameworks: Django, FastAPI, LangChain
• AI Models: Claude API, OpenAI API, Anthropic SDK
• Protocols: MCP SDK, REST, WebSockets
• Data: pgvector, Qdrant, Redis
• Deployment: Docker, Kubernetes, Raspberry Pi OS

Case Study: Jeeves

Multi-tenant B2B AI assistants platform. Hundreds of customer-specific agents running in parallel, each with custom tools and knowledge bases. Central orchestrator manages resource allocation, monitoring, and cost optimization. Agents handle sales queries, technical support, and process automation 24/7.

What's Included

• Architecture design and pattern selection
• Agent implementation with MCP support
• Orchestration logic and task routing
• Tool definition and integration
• State management and memory systems
• Error handling and recovery
• Monitoring, logging, and observability
• Testing and deployment pipelines

Cost: $8K-15K depending on complexity, team size, and infrastructure needs.