Time-consuming search
Researchers spend expensive time moving from question to source, then from source to exact supporting passage.
Executive recommendation
Semantic Search Engine in 3 Months.
Introducing ReviewOS, a custom tool for MediGen to search, retrieve, cite, and assemble research and legal documentation.
~$600K
Modeled annual MVP value unlocked
~50K
Existing documents in scope
<120s
Target time to first useful source
>80%
MVP Stage 0 top-5 retrieval gate
Problem
Credible search and citations consume the workflow.
Researchers, reviewers, and legal/regulatory experts spend expensive time searching across repositories, opening long documents, hunting for exact passages, copying citations, and rebuilding context from prior work. That is the addressable workflow.
Recommendation
Implement an AI-Powered Semantic Search Engine Capability
Start building world-class AI search on existing documentation in a way that supports MediGen's workflow now and can scale into future workflows and teams.
Value case
The first value pool is search, retrieval, citation, and summarization.
The base case assumes a 25-person review/research team, about 29,600 annual document-heavy hours, and a $4.1-$4.5M loaded cost pool. MVP Stage 0 addresses the portion of that work spent finding, opening, citing, and summarizing evidence the organization already holds.
Current pain
Where the as-is workflow breaks down
Brittle search and retrieval
Keyword search, folder memory, naming conventions, and document-level matches miss relevant evidence or bury it in long files.
Manual multi-source synthesis
Teams manually reconcile documents, copy citations, and rebuild context across spreadsheets, notes, memos, and review packets.
Product roadmap
Search and Retrieval is the core product to master first.
AI semantic search engine
Search, retrieve, cite, and log evidence from existing documentation within the staged engagement.
Corpus maintenance
Add controlled ingestion so the search layer stays current for new research efforts.
Citation agent
Assemble evidence packets, check citations, and flag contradictions or gaps.
Workflow application
Standardize projects, queues, approvals, templates, exports, and audit once usage proves the pattern.
Risk posture
The credible product is cautious by design.
Unsupported claims
Require source citations for material claims and block uncited answer sections from export.
False confidence
Display source coverage, confidence, contradictions, and low-evidence warnings separately.
Sensitive evidence
Flag privileged, confidential, PII/PHI, and trade-secret candidates for human approval.
MediGen AI policy
Build to client-approved hosting, provider, data-handling, access, logging, and review policies from the first sprint.
Recommended Next Step
Approve the MVP Stage 0 build and pilot gate.
Ship the read-only Corpus API + MCP server, test it against a golden set, and open a pilot only if retrieval accuracy, citation coverage, latency, and safe-fail gates clear.