G-ATAI / For business teams

    AI Business Automation Services

    Business automation that connects routine steps across documents, data and applications. Use AI where interpretation is needed and predictable rules where they are enough.

    01 / When this service fits

    When this service fits

    This service suits repetitive handoffs, document intake, reporting preparation and data entry across multiple systems. It is most useful when the current process has a clear owner and exceptions can be identified.

    02 / What we scope and deliver

    What we scope and deliver

    • Workflow map separating deterministic rules, AI-assisted steps and human approvals.
    • Integrations for selected systems, with validation and exception queues.
    • Pilot automation, operational reporting and a handover plan for the process owner.

    How success is evaluated

    Compare the pilot with the existing process using cycle time, manual steps, exception rates and output accuracy. Track what happens when data is incomplete or a connected service is unavailable; savings are measured, not assumed.

    What to bring to the first call

    • The current process, sample documents and the most common exceptions.
    • Systems involved, access owners and any existing automation.
    • Volumes, service expectations and the actions that require approval.

    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.

    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