Managed browser task automation workspace

Reduce manual browser work while keeping task data and review inside the client's own environment. For IT and development teams automating repetitive web tasks such as form filling, data retrieval and online workflows, convert permitted target sites, task definitions, credentials and business rules into reviewed automation runs with structured extracted data and session evidence. The benefit is a testable hypothesis, measured through completed task runs per operator hour and manual interventions per hundred runs; do not assume that AI output alone produces business value.

Confirm the buyer's problem and scope, collect permitted target sites, task definitions, credentials and business rules, then follow this sequence: 1. Define browser tasks in natural language or a visual step editor. 2. Interpret page content with AI and computer vision. 3. Fill forms and complete multi-step online workflows. 4. Solve CAPTCHAs to keep approved runs moving. 5. Extract and structure data from target pages. Resolve uncertain cases with qualified reviewers, approve reviewed automation runs with structured extracted data, and measure completed task runs per operator hour and manual interventions per hundred runs against a documented baseline.

How the AI works

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three 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 target-site set and permitted credential scope; final submission and data-use checks remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

Safeguards

Preserve site terms, credential handling, data-use permissions and audit trails. Named owners approve task scope and external submissions. One approved target-site set and permitted credential scope; final submission and data-use checks 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 target-site set and permitted credential scope; final submission and data-use checks remain human. Implement one approved input format, a bounded representative case set and the first two task modules: define browser tasks in natural language or a visual step editor; interpret page content with AI and computer vision. Support the third module with operator review: fill forms and complete multi-step online workflows. 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

Client-owned task definitions, permitted credentials and authorized target sites. Cloud storage, ticketing and data 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: Task and site setup, Run monitor and session review, Extracted data and delivery. Use a task list with run status, a central live or recorded session view, and a right-hand panel for steps, extracted fields, errors and approvals. Let users compare runs side by side. Display draft, running, needs review and approved states. Provide a client preview link with comments anchored to the relevant run or extracted record. Make the task-specific outcome reviewed automation runs with structured extracted data visible beside its evidence, review state and value baseline.