In-app reading and writing assistant console

Reduce context switching while keeping the user's text and sources under their control. For support teams, knowledge workers and language learners who read and write inside web apps all day, convert the visible page content, selected text, connected knowledge sources and saved vocabulary into reviewed in-place text actions linked to their source. The benefit is a testable hypothesis, measured through accepted in-place actions per working hour and corrections after use; do not assume that AI output alone produces business value.

Confirm the buyer's problem and scope, collect permitted page content, selected text, connected knowledge sources and saved vocabulary, then follow this sequence: 1. Show a floating assistant inside the current app or website. 2. Read the visible on-screen content in real time. 3. Offer one-click write, improve, paraphrase, summarize, explain, translate and reply actions on selected text. Resolve uncertain cases with qualified reviewers, approve reviewed in-place text actions linked to their source, and measure accepted in-place actions per working hour and corrections after use 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 host application and one connected knowledge source; final replies, translations and published text remain human-reviewed. A model suggestion is never a verified fact, professional decision or authorization to act.

Safeguards

Preserve user voice, source attribution, quotation accuracy and usage permissions. Users approve substantive changes and publication scope. One host application and one connected knowledge source; final replies, translations and published text remain human-reviewed. 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 host application and one connected knowledge source; final replies, translations and published text remain human-reviewed. Implement one approved input format, a bounded representative case set and the first two task modules: show a floating assistant inside the current app or website; read the visible on-screen content in real time. Support the third module with operator review: offer one-click write, improve, paraphrase, summarize, explain, translate and reply actions on selected text. 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 help desks, CRMs, wikis and knowledge bases. Cloud document storage, browser extension surfaces 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.

The screens in detail

Primary screens: Assistant settings and sources, In-page floating assistant, Admin console and review queue. Use a compact floating panel over the host page, a side panel for sources and saved items, and a full console for administrators. Let users compare draft and edited text side by side. Display draft, changes requested and approved states. Provide a review link with comments anchored to the relevant text span. Make the task-specific outcome reviewed in-place text actions linked to their source visible beside its evidence, review state and value baseline.