AI Agent Development
Custom AI agents built on LangChain/LangGraph that plan, call tools, and complete multi-step work, not just answer questions.
We design and ship purpose-built AI agents that take real actions inside your existing systems: reading documents, calling internal APIs, updating records, and escalating to a human only when it genuinely matters. Built on LangChain and LangGraph for reliable, inspectable multi-step reasoning, with guardrails, logging, and human-in-the-loop checkpoints so the agent stays accountable in production.
What's included
- Agent architecture design (tools, memory, guardrails, escalation rules)
- LangChain/LangGraph implementation with structured tool-calling
- Integration with your internal systems, APIs, and data sources
- Human-in-the-loop review points for high-stakes actions
- Observability/logging so every agent decision is auditable
- 30-day post-launch tuning window
How it works
- 01Map the workflowWe shadow the current manual process and identify exactly which steps an agent can safely own.
- 02Design the agentTool access, memory, and escalation boundaries are scoped before a line of code is written.
- 03Build & testLangGraph state machine implementation, tested against real edge cases from your data.
- 04Deploy & tuneShips behind a feature flag, monitored closely, tuned against real usage for 30 days.
Stack
LangChainLangGraphPythonOpenAI/Anthropic APIsPostgres