Source-linked research answer workbench

Reduce time spent gathering and checking answers while keeping every claim linked to its source. For research teams, analysts and knowledge workers who need current, source-linked answers, convert permitted web sources, uploaded documents and team notes into reviewer-approved source-linked answers with citations. The benefit is a testable hypothesis, measured through accepted answers per research hour and corrections after review; do not assume that AI output alone produces business value.

Confirm the buyer's problem and scope, collect permitted web sources, uploaded documents and team notes, then follow this sequence: 1. Accept natural language questions. 2. Run real-time web search across permitted sources. 3. Generate concise AI summaries with source links. 4. Support follow-up questions that refine the answer. 5. Consolidate web, document and note data into one searchable space. Resolve uncertain cases with qualified reviewers, approve reviewer-approved source-linked answers with citations, and measure accepted answers per research hour and corrections after review against a documented baseline.

How the AI works

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate answers for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Final factual and citation checks remain with qualified reviewers. A model suggestion is never a verified fact, professional decision or authorization to act.

Safeguards

Preserve source attribution, quotation accuracy and usage permissions. Reviewers approve substantive claims and publication scope. One approved source set and one team workspace; final factual and citation checks remain with qualified reviewers. 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 source set and one team workspace; final factual and citation checks remain with qualified reviewers. Implement one approved input format, a bounded representative case set and the first three task modules: accept natural language questions; run real-time web search across permitted sources; generate concise AI summaries with source links. Support the remaining modules with operator review: follow-up questions, conversational interface, image upload, spam filtering, visual layout, reader view, private search, data consolidation, retrieval augmented generation, drafting assistance, team spaces, browser extension and scheduled delivery. 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 documents, permitted web sources and team note systems. Cloud storage, browser extension endpoints and email or app delivery. 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: Query and source intake, Editable answer preview, Team review and delivery. Use a thumbnail gallery for saved queries, a large central answer canvas, and a right-hand panel for sources, citations and comments. Let users compare answer versions side by side. Display draft, changes requested and approved states. Provide a shared team link with comments anchored to the relevant claim. Make the task-specific outcome reviewer-approved source-linked answers with citations visible beside its evidence, review state and value baseline.