Custom AI Agent Development Built Around Your Workflow

An off-the-shelf AI tool responds to prompts: it produces text. A custom AI agent can take actions: call your specific APIs, query your databases, write and execute code, and chain multi-step decisions to complete a goal end-to-end. Because it's built around your workflow rather than a generic use case, it can use your internal tools, follow your business logic, and produce output in exactly the format your team needs.

We work across the major providers: Anthropic Claude, OpenAI GPT-4o, Google Gemini, and open-source models (Llama, Mistral) for on-premise or cost-sensitive deployments. Model choice is driven by the task, not preference: Claude for reasoning-heavy tasks, GPT-4o for multimodal input, and open-source models for high-volume pipelines where API cost matters.

A single-purpose agent, for example a report-generation agent connected to your analytics APIs, takes 4 to 6 weeks from scoping to deployment. We always start with a 2-week discovery sprint to define the agent's task scope, tool requirements, and success metrics, and ship a working proof-of-concept before building out the full production system.

We design for failure from the start: human-in-the-loop checkpoints for high-stakes actions, structured logging of every agent step so failures are diagnosable, and confidence thresholds below which the agent escalates rather than acts. Every build includes 30 days of post-deployment support so we can catch failure patterns in real traffic before they become habitual.