Enterprise clients (finance, corporate) deny API access for security reasons. Browser-based automation bypasses the need entirely — GPT-4o Vision reads the screen like a human, Twin.so acts on it, and every run is fully audited.
0
IT tickets required
no API access needed
100%
audit trail
every run logged
Any
legacy system
if it has a UI
Days
→ Minutes
per data task
Typical build: 3–4 week sprint · Fixed price · Zero delivery risk
API needed
Zero
Audit trail
100% logged
IT tickets
None
Finance and corporate IT teams lock down API access by policy. Getting an API key approved requires months of security review, legal sign-off, and compliance documentation. For ongoing operational tasks, that process is simply not viable.
Without automation, humans navigate through clunky legacy UIs, read data from tables, and manually re-enter it into modern platforms. This is error-prone, time-consuming, and completely unnecessary — the data exists, it just can't be accessed programmatically.
Manual data extraction leaves no record of what was accessed, when, by whom, or whether it was accurate. Browser-based automation with screenshot logging creates a complete, reviewable audit trail that actually improves compliance versus manual processes.
This is the actual workflow Kovil AI engineers can build and deploy — not a diagram. Here is what runs inside every node.
The workflow can be triggered two ways: on a configurable schedule (daily, weekly, or on a specific cadence) or on demand via a Slack slash command. The Slack trigger allows operators to pass parameters — specific record IDs, date ranges, or task types — without opening n8n. When triggered, n8n validates the input parameters, checks for any currently-running browser sessions to prevent conflicts, and queues the task. A Slack confirmation message is posted to the operator: "Browser task queued — estimated completion in X minutes."
Twin.so spins up a fresh, isolated cloud browser instance for each workflow run. The browser navigates to the legacy enterprise system URL. Login credentials are stored in an encrypted secrets vault (never in plaintext in n8n or code) and injected securely at runtime. Twin.so handles 2FA flows, CAPTCHA challenges, and session cookie management automatically. Each browser session is completely isolated — no shared state between runs, and the session is terminated and destroyed after the workflow completes.
Twin.so takes a screenshot of the current page state and sends it to GPT-4o Vision. GPT-4o Vision analyzes the screenshot to identify: input fields and their labels, table structures and column headers, navigation buttons and menus, data values in each cell, and the current page context. This vision-based approach requires zero API documentation, zero DOM scraping, and zero reverse engineering. It reads the screen exactly as a human would — but in milliseconds and without fatigue.
Based on GPT-4o Vision's screen analysis, n8n directs Twin.so to execute specific actions: click a menu item at coordinates (x, y), type text into an identified input field, scroll down to load more table rows, select a date range from a date picker, or export a report to CSV. Each action is followed by a new screenshot and vision analysis — confirming the action succeeded before proceeding. If an unexpected modal or error appears, the workflow logs it and halts, posting an alert to Slack rather than proceeding blindly.
Extracted data from the legacy system is normalized by GPT-4o into a clean schema — dates standardized to ISO 8601, numeric fields stripped of formatting, text fields trimmed and encoded consistently. The normalized data is written to Airtable via API, or pushed directly to the client's preferred modern destination: a Google Sheet, a database via API, a Salesforce record update, or a webhook to any receiving endpoint. Data validation runs before write to flag any records that appear malformed or incomplete.
After the workflow completes, n8n compiles a complete audit package: a summary of all actions taken, screenshots at each key step, the raw data extracted, the normalized output written to the destination, and a run duration timestamp. This is posted to a designated Slack channel as a structured message with attachments. Every action is logged — nothing happens silently. If a run is ever questioned by the enterprise client's IT or compliance team, the full audit trail is available and exportable. Runs are stored for 90 days by default.
Cloud browser
Spins up isolated cloud browser sessions per run. Handles login, 2FA, CAPTCHA, and session management without local browser setup.
Screen reader
Reads screenshots to identify fields, tables, and buttons. Requires zero API documentation or DOM access — pure visual navigation.
Orchestration
Connects triggers to Twin.so, routes Vision analysis to action execution, manages error handling, and coordinates data write.
Data destination
Primary write destination for normalized data extracted from legacy systems. Configurable schema per enterprise client.
Data processing
Handles complex data normalization, format conversion, and validation before writing to the destination system.
Audit + triggers
On-demand workflow triggers via slash command. Full audit log with screenshots posted after every run. Alert on any failures.
Kovil AI engineers scope, build, test and deploy this browser automation workflow end-to-end. No IT engagement required from the client — the workflow works with their existing UI.
Twin.so deploys a secure isolated cloud browser that navigates web interfaces exactly as a human would — moving the mouse, clicking buttons, reading text on screen, filling forms, and scrolling through data tables. It does not require API documentation, credentials sharing beyond login details, or any changes to the enterprise system. From the legacy system's perspective, it sees a normal human browser session.
Yes. Twin.so runs in an isolated cloud environment separate from the agency's infrastructure. Login credentials are stored in an encrypted secrets vault, not in n8n directly. Every session is ephemeral — the browser instance is destroyed after the task completes. A full screenshot audit log is maintained for compliance and review. The enterprise client's IT team does not need to open firewall ports or grant any backend access.
Any system accessible via a web browser can be automated: legacy ERP systems, government databases, insurance portals, financial compliance platforms, custom-built intranets without APIs, and proprietary CRM systems from the 2000s. If a human can log in and use it through a browser, Twin.so with GPT-4o Vision can replicate that workflow.
GPT-4o Vision receives a screenshot of the current page state and a task description in plain English (e.g., 'Find the Q3 report in the Reports section and download it as CSV'). It identifies the relevant UI elements from the visual layout — buttons, menus, input fields, table headers — and instructs Twin.so where to click and what to type. No documentation, no selectors, no code changes required.
Book a 30-minute discovery call. Kovil AI engineers will review your legacy system UI, scope the Twin.so browser workflow, and define the data extraction and write-back logic — fixed price, zero delivery risk.
Typical sprint: 3–4 weeks · Fixed-price · Fully managed delivery · Post-launch support included