AI agents that move work forward within clear rules

Some tasks need more than a fixed automation rule: read a request, interpret the context and prepare the next action. Studio IDD builds AI agents for those workflows, with defined permissions, approval steps and a record your team can review.

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IDEAS INTO EXPERIENCES

Clarity.
Character.
Craft.

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STUDIO IDD / AI AUTOMATION
Concept study · Trigger · Agent · Review · Action
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A GOOD PLACE TO START

Start with a recurring task that has a clear outcome

01

Examples include classifying support requests, preparing lead notes, drafting documents from templates and moving reviewed information between tools. Each workflow needs a definition of success and a route for exceptions.

01OUR EXPERTISE

The task, integrations and controls together

A considered approach, from the first question to the details that make it work.

01

Workflow mapping

We document inputs, decisions and actions, including the cases that currently require a person.

02

Agent and tool connections

The agent uses approved integrations to retrieve information and perform the scoped actions. Required API access is confirmed before implementation.

03

Human review

Approval steps keep consequential actions with your team. Unsupported or ambiguous cases can be routed for manual handling.

04

Evaluation and action records

Historical or representative cases help assess whether the workflow behaves as intended. Logging is designed around the information needed to investigate a result.

02HOW WE WORK

A gradual path to automation

Each stage moves the work forward. You see the decisions, review the progress and know what comes next.

  1. 01

    Map

    Define the task, baseline and exceptions.

  2. 02

    Build

    Connect the tools and implement the rules and approvals.

  3. 03

    Test

    Compare proposed actions against representative cases.

  4. 04

    Roll out

    Begin with reviewed actions and expand only where the results support it.

03BUILT TO HAND OVER

What your team receives

  • The scoped agent workflow, integration configuration, evaluation findings and operating guidance.

AI agent questions

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If inputs and decisions follow predictable rules, a conventional integration may be more appropriate. AI is useful where interpretation adds value.
Only within the agreed permissions and workflow. Approval rules are set before rollout.
The workflow needs defined retries, failure reporting and manual recovery appropriate to the task.
Running cost depends on tool access, case variety, approval requirements and the volume of work the agent handles. A plan with timeline and price follows the first conversation, once the workflow and integrations are defined. Estimating that cost early keeps the first version proportionate to the work.
You need a description of the recurring task, the trigger, the tools involved and what a completed case looks like. Examples of exceptions and the people who should review them are equally important. Required API access is confirmed before implementation begins.
An AI agent can connect to tools through approved integrations, such as the APIs of your business systems, where those APIs support the required actions. Permissions are set around each tool, so the agent only uses the tools it has been granted.

+KEEP EXPLORING

Good things work together.

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