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    G-ATAI / For business teams

    AI Agent Development Services

    Develop AI agents that retrieve information, use approved tools and help complete a defined business task. Design the workflow, permissions and evaluation alongside the agent itself.

    Book a strategy call What we scope and deliver ↓

    01 / When this service fits

    When this service fits

    Choose agent development for knowledge-intensive support, internal research, document handling or operations that need several connected steps. Start with a bounded task and an identifiable owner for the workflow.

    02 / What we scope and deliver

    What we scope and deliver

    • Agent workflow and knowledge retrieval design grounded in approved business sources.
    • Connections to selected APIs or tools with scoped permissions and approval steps.
    • Evaluation cases, failure handling, logging and a deployment plan for the pilot.

    How success is evaluated

    Test completed tasks against expected outcomes, including incorrect retrieval, missing context and tool errors. Measure task completion, grounded answers, latency, running cost and escalations to a person before increasing autonomy.

    What to bring to the first call

    • Example tasks, expected outputs and situations that require human approval.
    • Knowledge sources, API documentation and proposed tool permissions.
    • Users, deployment channels and requirements for logs or data retention.

    From discovery to delivery

    1. Define the business problem

      Map users, the current workflow, data access and constraints. Agree on the baseline, acceptance criteria and scope before choosing a model or committing to a build.

    2. Test a focused pilot

      Evaluate a representative task with your data and users. Check quality, error handling, latency and running costs before expanding access or automating critical decisions.

    3. Integrate and hand over

      Plan permissions, deployment, monitoring and human review with your team. Agree on documentation, training and ongoing support in the project scope.

    Explore related project work

    These project pages show capabilities and product concepts. They do not establish independently verified customer outcomes or promise a return on investment. GARC includes a floor-plan beta; LogiTwin is a logistics concept.

    FinSight AI ↗NouriPav ↗All projects ↗

    Before you start

    How much does an AI project cost?

    Pricing depends on the workflow, data readiness, integrations, security requirements and support scope. A strategy call helps define these inputs; a proposal should separate implementation work from model, cloud and third-party running costs.

    Can we start with our existing software?

    Yes. The first step is to assess available APIs, permissions and data access. A limited integration or pilot may be more suitable than replacing a working system. Feasibility and delivery dates are agreed after discovery.

    Will AI operate without human review?

    That depends on the risk and task. Define approval points, permissions, fallback behavior and audit logs before deployment. Sensitive actions should stay within the controls agreed with your team.

    Plan your implementation

    Share your workflow, current systems and target outcome. Choose a time for a strategy call to discuss feasibility, scope and the next step.

    Book a strategy call