Source-linked in-browser AI assistant console

For

Teams and individuals who do research, writing and routine web tasks in a browser and want assistance without switching apps

Solves

Browser help is scattered across extensions and subscriptions, and automated actions run without source links, approval gates or a clear record of what happened.

Delivers

Source-linked assistant outputs and approved browser actions

Built in

about 4 weeks of creation time, MVP in 5 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 app switching and manual browser work while keeping every AI action source-linked and reviewable.

1. Provide in-browser AI assistance without leaving the page.
2. Offer context-aware suggestions from the current page.
3. Summarize pages and videos with source links.
4. Answer questions from the browser interface.
5. Generate and rewrite text for emails, marketing copy and creative writing.
6. Automate routine browser tasks such as form filling, data extraction, clicking, typing and scrolling.
7. Help manage multiple tabs and workflows.
8. Deliver personalized recommendations from user preferences.
9. Surface shortcuts and navigation tips.
10. Support multiple operating systems and popular browsers.
11. Require account sign-in for personalized use.
12. Keep privacy-centric handling of user data.
13. Adjust tone and style of generated text.
14. Support multi-language content and translation.
15. Give real-time suggestions and corrections.
16. Record and replay reusable workflows.
17. Separate profiles for tabs, cookies, sign-ins and site data.
18. Save checkpoints so interrupted tasks resume.
19. Pause for explicit approval on sensitive steps such as form submissions and payments.
20. Log whether each run finished, stopped or failed.
21. Let users choose between different large language models.
22. Remember previous interactions across tabs and sessions.
23. Perform one-click actions such as page summarization and content insertion.
24. Provide universal shortcut access from any app or website.
25. Organize and manage prompts for frequent users.

Everything these tools do, in one app

• In-browser AI assistance Provides AI help directly inside the browser so users can get assistance without leaving the page.Found in Edge Copilot Mode, Microsoft Copilot, BrowserCopilot AI and 4 more
• Context-aware suggestions Offers relevant suggestions based on the current webpage or browsing context.Found in Edge Copilot Mode, BrowserCopilot AI, Aladin
• Content summarization Summarizes web pages or videos to help users quickly grasp the main points.Found in Edge Copilot Mode, Brave Leo AI, Brave Leo on iOS and 2 more
• Question answering Lets users ask questions and receive answers directly from the browser interface.Found in Brave Leo AI, Brave Leo on iOS
• Content generation Generates or rewrites text for writing tasks such as emails, marketing copy, or creative writing.Found in Nectar GPT, Brave Leo on iOS, Aladin and 1 more
• Task automation Automates routine browser tasks like form filling, data extraction, clicking, typing, and scrolling.Found in BrowserCopilot AI, Aye
• Multitasking support Helps users manage multiple tabs and workflows efficiently.Found in BrowserCopilot AI
• Personalized recommendations Delivers tailored suggestions based on user preferences and browsing habits.Found in Microsoft Copilot
• Shortcuts and tips Provides practical shortcuts and tips to navigate the web more quickly.Found in Microsoft Copilot
• Cross-platform support Works on multiple operating systems and popular browsers.Found in Microsoft Copilot
• Account sign-in Requires users to sign in with an account for a personalized experience.Found in Microsoft Copilot
• Privacy-centric design Respects user data and maintains privacy while providing AI assistance.Found in Brave Leo AI, Brave Leo on iOS
• Tone and style customization Allows users to adjust the tone and style of generated text to match different writing objectives.Found in Nectar GPT
• Multi-language support Enables content creation and translation in various languages.Found in Nectar GPT, Brave Leo on iOS
• Real-time suggestions and corrections Provides real-time suggestions and corrections to enhance text clarity and correctness.Found in Nectar GPT
• Reusable workflows Allows users to record workflows and save them for later execution.Found in Aye
• Profile separation Keeps tabs, cookies, sign-ins, and site data separate for different accounts.Found in Aye
• Checkpoint resumption Saves progress so tasks can resume instead of restarting if interrupted.Found in Aye
• Sensitive step approval Pauses and requires explicit user approval for high-risk actions like form submissions and payments.Found in Aye
• Work records Tracks whether each run finished, stopped, or failed, giving users a clear log of task outcomes.Found in Aye
• Model choice Lets users choose between different large language models to customize responses.Found in Brave Leo on iOS
• Unified memory Remembers previous interactions across tabs and sessions to reuse content easily.Found in Aladin
• One-click actions Performs actions like page summarization and content insertion with a single click.Found in Aladin
• Universal shortcut access Provides instant AI access via a keyboard shortcut from any app or website.Found in Promptify
• Prompt management Organizes and manages prompts efficiently for frequent AI users.Found in Promptify

What goes in, what comes out

The workflow

1. In
   Start with

   Permitted page content, user prompts, saved workflows and account settings

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect permitted page content

4. 3

   User prompts

5. 4

   Saved workflows and account settings

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Source-linked assistant outputs and approved browser actions

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 browser and one model provider; final content checks and sensitive approvals remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Assistant panel and page context, Workflow builder and run log, Admin console and data controls. Use a side panel for chat, summaries and suggestions, a central page view with source highlights, and a right-hand panel for prompts, models and workflow steps. Let users compare draft and approved text side by side. Display running, paused for approval, finished and failed states. Provide a client or team preview link with comments anchored to the relevant page or output. Make the task-specific outcome source-linked assistant outputs and approved browser actions 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

User-owned browser profiles, permitted page content and authorized workflow recordings. Cloud storage, identity providers and export 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.

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

   5 days

   One buyer segment, one recurring use case; first modules: provide in-browser AI assistance without leaving the page; offer context-aware suggestions from the current page. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   6 days

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

4. 4

   Full product

   10 days

   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 teams and individuals who do research, writing and routine web tasks in a browser and want assistance without switching apps use it to solve "browser help is scattered across extensions and subscriptions, and automated actions run without source links, approval gates or a clear record of what happened"?
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: Accepted assistant outputs per active user and approved automated actions per week.
4. Measure, then decide. Track accepted assistant outputs per active user and approved automated actions per week; 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 browser and one model provider; final content checks and sensitive approvals remain human. Implement one approved input format, a bounded representative case set and the first two task modules: provide in-browser AI assistance without leaving the page; offer context-aware suggestions from the current page. Support the third module with operator review: summarize pages and videos with source links. 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 source-linked assistant outputs and approved browser actions. Retain the explicit scope boundary: One approved browser and one model provider; final content checks and sensitive approvals remain human.

What the build depends on. Page capture and preview, asynchronous automation jobs, editable version history, reviewer access and tested export formats. High-fidelity browser support requires specialist QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One approved browser and one model provider; final content checks and sensitive approvals 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 browser-assistance package. Offer a monthly production allowance after repeat demand. Quote complex automation or multi-browser support separately. These are test prices, not market benchmarks. Package the initial sale as one bounded source-linked assistant outputs and approved browser actions. 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 app switching and manual browser work while keeping every AI action source-linked and reviewable. Demonstrate a concrete source-linked assistant outputs and approved browser actions using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Teams and individuals who do research, writing and routine web tasks in a browser and want assistance without switching apps professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample source-linked assistant outputs and approved browser actions from a small authorized input set, with a transparent calculation of accepted assistant outputs per active user and approved automated actions per week and no promised savings.

The first 30 days

1. Week 1: interview five teams and individuals who do research, writing and routine web tasks in a browser and want assistance without switching apps and inspect a recent example of browser help is scattered across extensions and subscriptions, and automated actions run without source links, approval gates or a clear record of what happened.
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 accepted assistant outputs per active user and approved automated actions per week, 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: Accepted assistant outputs per active user and approved automated actions per week. 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

Accepted assistant outputs per active user and approved automated actions per week; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs source-linked assistant outputs and approved browser actions. 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 prompts, workflow steps and review examples, together with reliable delivery for a narrow browser-assistance niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for teams and individuals who do research, writing and routine web tasks in a browser and want assistance without switching apps. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Edge Copilot Mode, Microsoft Copilot, BrowserCopilot AI, Brave Leo AI, Nectar GPT, Aye, Brave Leo on iOS, Aladin and Promptify. Compare this product with the buyer's present method on accepted assistant outputs per active user and approved automated actions per week. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Model calls, browser automation runs, 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 source-linked assistant outputs and approved browser actions. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve user voice, source attribution, quotation accuracy and usage permissions. Users approve substantive changes and publication scope. One approved browser and one model provider; final content checks and sensitive approvals remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.