AI Agent Development & Multi-Agent Systems
We design and build production-grade AI agents that reason, plan, and execute complex workflows. From single-purpose agents to coordinated multi-agent systems, we bring autonomous AI to your business.
What We Do
Full-Lifecycle Agent Development
Agent Architecture Design
Design scalable agent systems for complex workflows. We define tool schemas, memory strategies, and reasoning patterns tailored to your domain.
Multi-Agent Orchestration
Build coordinated multi-agent systems with LangGraph. Agents that collaborate, delegate, and self-correct across complex business processes.
Production Hardening
Deploy and optimize agents for real-world performance. We implement observability, fallback strategies, and cost controls for production reliability.
Results
Proven Impact
8
Production agents deployed
40%
Cost reduction
<2s
Agent response latency
10x
Cost savings via model routing
Technologies
Our Stack
We're not loyal to any single vendor. We pick the right tools for your problem, your scale, and your budget.
Case Studies
Real-World Results
LangGraph Multi-Agent System
Built a coordinated multi-agent system with LangGraph for autonomous content workflows.
Dynamic Model Switching with LangGraph
Implemented intelligent model routing for cost-optimized inference across multiple LLM providers.
LangChain Platform Migration
Migrated a legacy LLM platform to LangChain v1 with production-hardened agent pipelines.
FAQ
Common Questions
What is a multi-agent AI system?
A multi-agent system uses multiple specialized AI agents working together to handle complex workflows. Instead of one monolithic agent trying to do everything, each agent focuses on a specific task — like a coding assistant, an evaluator, or a supervisor. The agents communicate through defined interfaces and share state through a managed workflow. This approach is more reliable, testable, and maintainable than single-agent architectures for complex use cases.
How much does AI agent development cost?
Our agent development engagements typically range from $30K-75K. A single-purpose agent (one focused task with tools) starts around $30K. Multi-agent systems with coordinated workflows, state management, and production monitoring are in the $50-75K range. This includes architecture design, implementation, testing, deployment, and knowledge transfer to your team.
What framework do you use for building AI agents?
We primarily use LangGraph for agent development. It provides state management, conditional routing, human-in-the-loop patterns, and persistence that are essential for production agent systems. LangGraph is built on top of LangChain and integrates with LangSmith for observability. For simpler use cases, we also use the Vercel AI SDK and direct API integrations.
How long does it take to build a production AI agent?
A single-purpose agent typically takes 3-5 weeks from design to deployment. Multi-agent systems with 3-5 coordinated agents take 6-10 weeks. Complex systems with 8+ agents, human-in-the-loop workflows, and advanced state management take 10-14 weeks. We deliver working agents incrementally — you see progress every 1-2 weeks, not just at the end.
Ready to build intelligent agents?
Let's discuss how AI agents can automate complex workflows and unlock new capabilities for your business.