LangGraph agent development
We build production AI agents with LangGraph and modern agent frameworks for US companies: multi-step, tool-using agents that are observable, testable, and reliable enough to run unattended. Agents that survive contact with real traffic, not demo-ware.
No sales script. You talk to the engineers who'd build it.
Our team works a shifted day so you get real-time standups and same-day turnarounds across US time zones, not next-morning replies.
Every line of code, model weight, and prompt is yours from day one. NDAs and clean IP assignment are standard, not an upsell.
You work directly with the engineers building your system. No account managers sitting between you and the people writing code.
We move from scoping to a working system in production in weeks. Most engagements ship something usable inside the first month.
What we build
Concrete systems we ship, tuned to your data and your stack.
Multi-step agents
Agents that plan, call tools, check their work, and recover from failures.
Observable by design
Full tracing of every step so you can see and debug what the agent actually did.
Tested like software
Evals and regression suites so agent changes don't quietly break in production.
Human in the loop
Approval gates and interrupts for the steps that carry real risk.
How we work
Scope & evals
We pin down what success means and build the evaluation set before writing the feature, so quality is measured, not guessed.
Build in the open
Weekly demos against real data. You see progress every week and can change direction before it gets expensive.
Ship & instrument
We deploy with logging, cost tracking, and guardrails in place, then tune against production traffic.
Hand off or stay
Take the keys with full docs, or keep us on for iteration. Either way you're never locked in.
Questions, answered
Why LangGraph over a simple prompt chain?
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Once an agent has loops, branches, retries, and human approval steps, a prompt chain falls apart. LangGraph gives you explicit, debuggable control flow, which is what production agents need.
How do you keep agents reliable?
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We trace every run, write evals for the critical paths, and design for failure with retries and fallbacks. Agents are tested like software, not shipped on hope.
Can you work with frameworks other than LangGraph?
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Yes. We use LangGraph, the OpenAI and Anthropic agent SDKs, or custom orchestration, whichever fits. The framework serves the problem, not the other way around.
Can the agent use our internal tools?
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Yes. We wire agents to your APIs, databases, and internal tools, often through MCP, so they act in your real systems with the right permissions.
Let's scope your build.
Tell us what you're trying to ship. We'll tell you honestly whether AI is the right tool and what it would take.
Start the conversation