Managed browser task automation workspace

For

Product and operations teams that run repetitive browser workflows across web applications

Solves

Repetitive browser tasks such as form filling, data extraction and cross-app handoffs are done by hand or split across several rented automation tools.

Delivers

Reviewed, replayable browser routines with recorded evidence

Built in

about 6 weeks of creation time, MVP in 7 days

Investment

$14,500 for the MVP, $49,500 for the full product

Run it

Inside your business, or as part of your offer to clients

Reduce manual browser work while keeping a human in control of consequential steps.

1. Automate browser actions such as form filling, ordering and booking from user instructions.
2. Expose an API for embedding automation in client products.
3. Run automation in cloud sessions without local setup.
4. Rotate proxies for regional access and captcha handling.
5. Support multiple AI models for flexible task execution.
6. Pause for human intervention at critical steps.
7. Offer open-source components for customization.
8. Record browser sessions for playback and debugging.
9. Provide debugging insights during script execution.
10. Operate with stealth settings and captcha solving.
11. Call backend APIs directly instead of simulating UI clicks.
12. Run tasks locally in a browser extension to keep data on the device.
13. Chain data between different web applications.
14. Learn new app interactions by inspecting frontend code.
15. Fall back to UI clicking to discover obscured API calls.
16. Capture user interactions as repeatable routines.
17. Execute discovered APIs without per-run token costs.
18. Publish and run shared workflows from a marketplace.
19. Handle logins including OAuth and 2FA.
20. Build workflows from natural language commands.
21. Meet enterprise security standards such as SOC2 Type 2.

Everything these tools do, in one app

• Web task automation Automates browser actions like form filling, ordering, and booking based on user instructions.Found in Browser Use Cloud, Browserbase, Pluno and 2 more
• API integration Provides an API for developers to integrate automation into their own products.Found in Browser Use Cloud, Browserbase, Vectorly
• Cloud hosting Runs browser automation in the cloud, eliminating local setup and scaling needs.Found in Browser Use Cloud, Browserbase, Airtop Auth
• Proxy rotation Uses rotating proxies to bypass captchas and regional restrictions.Found in Browser Use Cloud, Browserbase
• Multi-model support Supports multiple AI models for flexible automation.Found in Browser Use Cloud
• Human-in-the-loop Allows users to intervene during critical steps for reliability.Found in Browser Use Cloud, Airtop Auth
• Open source Offers open-source components for customization and community support.Found in Browser Use Cloud, Vectorly
• Session recording Records browser sessions for playback and debugging.Found in Browserbase
• Debugging tools Provides detailed insights to diagnose issues during script execution.Found in Browserbase
• Stealth mode Operates with built-in proxies and captcha solving to avoid detection.Found in Browserbase
• API-first execution Directly calls backend APIs instead of simulating UI interactions.Found in Pluno, Vectorly
• Local runtime Runs tasks locally in the browser extension, keeping data on the user's device.Found in Pluno
• Cross-app chaining Moves data between different web applications automatically.Found in Pluno
• Adaptive learning Learns how to interact with new apps by inspecting their frontend code.Found in Pluno
• UI fallback Clicks through the interface to discover API calls when they are obscured.Found in Pluno
• Record-and-replay Captures user interactions as repeatable routines.Found in Vectorly
• Zero runtime token costs Executes discovered APIs without incurring per-run token expenses.Found in Vectorly
• Marketplace Allows publishing and running shared workflows for reuse.Found in Vectorly
• Authentication handling Manages login processes including OAuth and 2FA automatically.Found in Airtop Auth
• Natural language instructions Builds automation workflows using natural language commands.Found in Airtop Auth
• Security compliance Meets enterprise-grade security standards like SOC2 Type 2.Found in Airtop Auth

What goes in, what comes out

The workflow

1. In
   Start with

   Authorized web tasks, credentials, target sites and business rules

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect authorized web tasks

4. 3

   Credentials

5. 4

   Target sites and business rules

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Reviewed, replayable browser routines with recorded evidence

AI does the heavy lifting, people stay in charge

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 site list and credential set; final authorization and consequential submissions remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Task intake and site permissions, Editable run preview, Client proof and delivery. Use a thumbnail gallery for projects, a large central editing canvas, and a right-hand panel for references, constraints and comments. Let users compare versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant asset. Make the task-specific outcome reviewed, replayable browser routines with recorded evidence visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, asset versions, client comments, approval states, usage allowances, revision limits, download history and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.

Integrations and data access

Client-owned web applications, authorized credentials and permitted data sources. Cloud session infrastructure, proxy providers, model providers and destination systems. Start with file exchange and validate destination specifications before promising direct write access. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   7 days

   One buyer segment, one recurring use case; first modules: automate browser actions such as form filling, ordering and booking from user instructions; expose an API for embedding automation in client products. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   8 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   3 weeks

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will product and operations teams that run repetitive browser workflows across web applications use it to solve "repetitive browser tasks such as form filling, data extraction and cross-app handoffs are done by hand or split across several rented automation tools"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Completed tasks per operator hour and correction rate after review.
4. Measure, then decide. Track completed tasks per operator hour and correction rate after review; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Pilot scope: One approved site list and credential set; final authorization and consequential submissions remain human. Implement one approved input format, a bounded representative case set and the first two task modules: automate browser actions such as form filling, ordering and booking from user instructions; expose an API for embedding automation in client products. Support the third module with operator review: run automation in cloud sessions without local setup. 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.

After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around reviewed, replayable browser routines with recorded evidence. Retain the explicit scope boundary: One approved site list and credential set; final authorization and consequential submissions remain human.

What the build depends on. Task upload and preview, asynchronous automation jobs, editable version history, reviewer access and tested export formats. High-fidelity automation requires specialist QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One approved site list and credential set; final authorization and consequential submissions remain human.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test a USD 300-1,500 fixed pilot for one defined automation package. Offer a monthly production allowance after repeat demand. Quote complex multi-site or regulated workflows separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewed, replayable browser routines with recorded evidence. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.

Message to test

Reduce manual browser work while keeping a human in control of consequential steps. Demonstrate a concrete reviewed, replayable browser routines with recorded evidence using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Product and operations teams that run repetitive browser workflows across web applications professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample reviewed, replayable browser routines with recorded evidence from a small authorized input set, with a transparent calculation of completed tasks per operator hour and correction rate after review and no promised savings.

The first 30 days

1. Week 1: interview five product and operations teams that run repetitive browser workflows across web applications and inspect a recent example of repetitive browser tasks such as form filling, data extraction and cross-app handoffs are done by hand or split across several rented automation tools.
2. Week 2: prepare a consented or synthetic demonstration of the three task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure completed tasks per operator hour and correction rate after review, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.

Paid pilot

Agree quality and outcome thresholds before the pilot using this measure: Completed tasks per operator hour and correction rate after review. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.

Success metrics

Completed tasks per operator hour and correction rate after review; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs reviewed, replayable browser routines with recorded evidence. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.

Why clients would pick it

A reusable library of approved routines, site constraints and review examples, together with reliable delivery for a narrow automation niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for product and operations teams that run repetitive browser workflows across web applications. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Browser Use Cloud, Browserbase, Pluno, Vectorly and Airtop Auth. Compare this product with the buyer's present method on completed tasks per operator hour and correction rate after review. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Automation attempts, browser session compute, proxy usage, storage, reviewer hours, client revision rounds and licensed source assets. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of reviewed, replayable browser routines with recorded evidence. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve site terms, credential handling, data rights and audit trails. Operators approve consequential submissions and account changes. One approved site list and credential set; final authorization and consequential submissions remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.