AI Agent Development
We build AI agents that hold up in production, with tool calling, retrieval, evals, and monitoring engineered in from day one, not bolted on after the demo.
The Challenge
Most AI agents demo beautifully and fall apart in production. They hallucinate tool calls, fail silently, drift as prompts change, and have no way to measure whether a change made them better or worse. The gap between a working prototype and a system you can trust with real users and real data is where most projects stall.
Our Approach
We treat agents as software, not magic. That means typed tool interfaces, retrieval pipelines you can evaluate, guardrails on what the agent can do, structured traces of every decision, and an eval suite that turns "it feels better" into a number. The result is an agent that you can change with confidence and operate without surprises.
What We Deliver
Tool Calling & Integrations
Typed, validated tool interfaces against your internal APIs, databases, and SaaS platforms, with auth, rate limiting, and idempotency handled.
RAG & Retrieval
Ingestion, chunking, embedding, hybrid search, and reranking pipelines tuned and evaluated for your corpus, not a generic vector-store wrapper.
Multi-Step Workflows
Stateful agent graphs with branching, retries, human-in-the-loop steps, and durable execution using LangGraph, Google ADK, or direct SDKs.
Evals & Observability
Evaluation suites and structured tracing so every model decision and tool call is measurable, debuggable, and regression-tested.
Guardrails & Safety
Input/output validation, permission boundaries, and policy checks that constrain what an agent can do against real systems and real data.
Multi-Agent Systems
Coordinated agents with clear responsibilities, shared memory, and orchestration, when a single agent is the wrong abstraction for the problem.
How We Work
Scope & Evals
We define the workflow, the tools, and, first, how we will measure success. Evals come before code.
Build the Spine
Tool interfaces, retrieval, and the orchestration graph, wired against real systems in a sandbox.
Harden
Guardrails, retries, tracing, and failure handling until the agent behaves under messy real-world input.
Ship & Monitor
Production deployment with dashboards and alerts, plus a handoff so your team can iterate safely.
Frequently Asked Questions
We design and build autonomous and semi-autonomous AI systems that can call tools, retrieve context, make decisions, and complete multi-step tasks. That spans architecture, tool and API integration, retrieval pipelines, evaluation harnesses, guardrails, and production monitoring, not just prompt engineering.
Let's scope your build.
Tell us about your requirements. We'll respond within 24 hours with an initial architecture assessment.
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