Agentic workflow automation control workspace

Reduce manual repetition while keeping every automated step visible and reversible. For operations leads and small delivery teams automating repetitive computer tasks and multi-step workflows, convert plain-language requests, connected apps and approved access rules into reviewed, scheduled agent runs with reusable programs and rollback. The benefit is a testable hypothesis, measured through completed runs per operator hour and manual corrections per completed run; do not assume that AI output alone produces business value.

Confirm the buyer's problem and scope, collect plain-language requests, connected app credentials, approved access rules and scheduling preferences, then follow this sequence: 1. Accept plain-language requests. 2. Build workflows by drag and drop. 3. Define custom triggers and actions. 4. Connect approved apps and services. 5. Automate repetitive manual tasks. 6. Monitor runs live and handle errors. Resolve uncertain cases with qualified reviewers, approve reviewed agent runs with reusable programs and rollback, and measure completed runs per operator hour and manual corrections per completed run against a documented baseline.

How the AI works

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One approved app set and one scheduling policy; final approvals and external actions remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

Safeguards

Preserve source attribution, access permissions and audit accuracy. Named owners approve substantive changes and external actions. One approved app set and one scheduling policy; final approvals and external actions remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.

What to build first

Pilot scope: One approved app set and one scheduling policy; final approvals and external actions remain human. Implement one approved input format, a bounded representative case set and the first two task modules: accept plain-language requests; build workflows by drag and drop. Support the remaining modules with operator review: define custom triggers and actions; connect approved apps and services; automate repetitive manual tasks; monitor runs live and handle errors. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

What it can connect to

Customer-owned app accounts, authorized file sources and permitted scheduling services. Cloud storage, spreadsheet and document import/export and messaging destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

The screens in detail

Primary screens: Request and access setup, Workflow builder and run monitor, Outputs and audit log. Use a project list, a central drag-and-drop canvas, and a right-hand panel for triggers, connected apps, permissions and comments. Let users compare workflow versions side by side. Display draft, running, needs review and rolled back states. Provide a client preview link with comments anchored to the relevant run. Make the task-specific outcome reviewed, scheduled agent runs with reusable programs and rollback visible beside its evidence, review state and value baseline.