Build autonomous AI agents
AI agents that reason, plan, and execute multi-step tasks. Tool-use, multi-agent orchestration, and human-in-the-loop workflows built by senior engineers.
Sound familiar?
- •Your chatbot answers questions but can't actually do anything - it can't look up orders, update records, or trigger workflows in your systems
- •You've seen demos of AI agents that look impressive, but your team doesn't know how to build reliable agents that handle edge cases and failures gracefully
- •Multi-step workflows still require human operators clicking through 5 different tools - AI should be handling the routine steps and only escalating exceptions
- •Your AI features are stateless - they don't remember previous interactions, can't maintain context across sessions, or learn from past decisions
What we build
Production AI agents with proper safety, observability, and reliability - not demo-ware.
Autonomous agent development
AI agents that reason through problems, break them into steps, and execute actions. ReAct patterns, chain-of-thought reasoning, and planning loops that handle complex multi-step tasks without human intervention.
Tool-use & function calling
Agents that interact with your APIs, databases, and third-party services. Proper tool definitions, parameter validation, error handling, and retry logic. Your agent doesn't just think - it acts on your systems safely.
Multi-agent orchestration
Specialized agents that collaborate - a research agent gathers data, an analysis agent processes it, a writing agent generates reports. Orchestration frameworks that manage agent communication, task delegation, and result aggregation.
Human-in-the-loop workflows
Approval gates for high-stakes decisions, escalation paths when agents are uncertain, and feedback loops that improve agent performance over time. AI handles the routine, humans handle the exceptions.
Agent observability
Full trace logging of every agent decision, tool call, and reasoning step. Dashboards showing agent performance, failure rates, and cost per task. Debug agent behavior in production without guessing.
Safety & guardrails
Action confirmation for destructive operations, rate limiting on tool calls, scope restrictions that prevent agents from accessing unauthorized resources, and kill switches for runaway agents.
Use cases teams hire us for
Customer support agents
AI agents that resolve support tickets end-to-end - look up order status, process refunds, update shipping addresses, and escalate complex issues to human agents. Integrated with Zendesk, Intercom, or your custom ticketing system.
Research & data gathering agents
Agents that search the web, extract data from documents, cross-reference multiple sources, and compile structured reports. Automated competitive analysis, market research, and due diligence workflows.
Internal knowledge assistants
Agents that answer employee questions by searching your documentation, Confluence, Notion, and Slack history. They don't just find documents - they synthesize answers and cite their sources.
Workflow automation agents
Agents that handle multi-step business processes - invoice processing, employee onboarding, compliance checks, and report generation. They interact with your existing tools and only escalate when something unexpected happens.
The agent stack we use
Frameworks and tools for building production AI agents.
LangGraph
Agent framework
CrewAI
Multi-agent
OpenAI / Anthropic
LLM providers
LangSmith
Agent tracing
FastAPI
Agent APIs
Redis
Agent memory
PostgreSQL
State persistence
Docker / AWS
Deployment
Frequently asked questions
How reliable are AI agents in production?
Can agents integrate with our existing tools?
How do you prevent agents from making mistakes?
What's the difference between a chatbot and an AI agent?
Ready to build AI agents?
Tell us about your use case and we'll design an agent architecture that works for your business.