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    AI Agent Development

    AI agents that do the work,not just demo well.

    Most agent projects die between the prototype and production. We build for the second part: real tool access, evaluated behaviour, and oversight where it matters.

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    Los Angeles & Geneva · 49-person team · 4.8★ on Clutch

    If you came here asking…

    • “Who can build a custom AI agent for my business?”
    • “How much does it cost to build an AI agent, and how long does it take?”
    • “Our prototype works but we can't ship it — what's missing?”
    • “Should we use an agent framework or build our own?”
    • “How do we stop an agent from doing something expensive and wrong?”

    …you are in the right place. Here is exactly what we do and what it costs.

    What we build

    Tool-Using Agents

    Agents wired into your real systems — CRM, database, ticketing, internal APIs — so they can act, not just answer. Tool design is most of the work and most of the risk.

    MCP & Custom Integrations

    Model Context Protocol servers and bespoke connectors that give an agent clean, scoped access to your data, with permissions that match your existing roles.

    Evaluation Harnesses

    Test suites for non-deterministic systems, so you can tell whether a prompt or model change made things better or quietly worse. This is what separates shipping from hoping.

    Guardrails & Oversight

    Scoped permissions, spend and action limits, approval gates on consequential steps, and audit logs. An agent that can act unsupervised needs a reason to be trusted.

    Multi-Agent Workflows

    Orchestrated agents for work too broad for one context — research sweeps, migrations, review pipelines — where decomposition genuinely beats a single call.

    Customer-Facing Agents

    Support and sales agents with retrieval over your real content, honest escalation paths, and defined limits on what they may promise on your behalf.

    Production
    Not proofs of concept

    Evaluated, monitored and permissioned — built to survive contact with real users.

    Model-agnostic
    Claude, GPT, Gemini

    We pick per workload and keep the swap cheap, because the frontier keeps moving.

    4.8★
    Clutch rating

    19 verified reviews across a 49-person team in Los Angeles and Geneva.

    How we run it

    1

    Scope — is an agent even the right answer?

    Plenty of problems are better solved by a deterministic script or a plain workflow. We will tell you when that's the case; it is a cheaper and more reliable answer than an agent.

    2

    Build the tools first

    Agents are only as good as the actions available to them. We design and harden the tool surface — scoping, validation, failure modes — before tuning any prompt.

    3

    Evaluate before shipping

    A test set drawn from your real cases, so behaviour changes are measured rather than guessed at. Non-deterministic systems need this more than ordinary software, not less.

    4

    Ship with oversight, then widen it

    Launch with tight permissions and human approval on consequential actions, then relax the gates as the evaluation data earns it.

    Pricing is per agent: a one-time setup fee of $2,500 per agent, then $2,500 per agent per month. Most engagements start with a single agent and add more once the first one is earning its keep. What we confirm on the scoping call is how many agents the work actually needs — not the rate.

    Frequently Asked Questions

    Tell us what you want the agent to do

    Bring the workflow and the systems it touches. You'll leave the call with a straight answer on whether an agent is the right tool, and what it would take to ship one.

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