AI agents

Custom AI Agents Built for Your Stack

Agents that take actions in your systems, with permissions, logging, and human approval where risk is high.

See case studies

Chatbots answer. Agents do work.

If you need research, ticket updates, CRM writes, or multi-step ops, you need tool-calling agents with clear boundaries, not an unbounded chatbot.

Agent capabilities

Purpose-built agents for support, sales ops, internal assistants, and workflow orchestration.

  • Tool calling into APIs and CRMs
  • LangGraph multi-step flows
  • Memory and audit logs
  • Guardrails and approval gates

For teams that need action, not chat

Product and operations teams ready to put AI behind authenticated tools.

How we deliver

  1. 1

    Discovery

    We map workflows, systems, success metrics, and constraints before writing a line of automation.

  2. 2

    Build

    We implement workflows, agents, and integrations against your real stack, with testing and documentation.

  3. 3

    Deploy

    We ship to production with monitoring hooks, access controls, and a clear handoff.

  4. 4

    Support

    Optional retainers cover updates, new workflows, and reliability as your tools evolve.

Related case studies

FAQ

Do you use LangGraph, OpenAI Assistants, or custom orchestration?

We pick the orchestration layer that fits the job. LangGraph is common for multi-step control; simpler agents use direct tool-calling APIs.

Next step

Book a discovery call

Tell us which workflow is costing time or revenue. We will map the stack, estimate effort, and connect you with the people who build it.

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Ready to automate?

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