Start an AI Systematic Review Automation Platform

1. 1

   Map automation to the methodology, not around it

   PRISMA and Cochrane define exactly how a rigorous review is conducted and reported: protocol, search, screening, extraction, and risk-of-bias assessment. Your automation must map to each of these steps precisely, because reviewers and regulators judge the work by the methodology. Building to the standard, not a shortcut around it, is the entire value proposition.

2. 2

   Keep human experts in final control

   The credible positioning is AI that accelerates the review while human experts make and can override every final decision. Regulated buyers will not accept a black box that decides which studies are included. Design the workflow so automation proposes and humans dispose, with a full audit trail of every decision and override.

3. 3

   Prove and document the time savings

   The commercial promise is concrete: 35 to 50 percent time savings across deployments, and up to 85 percent faster screening in strong cases. Instrument the platform to measure and evidence these gains for buyers. Documented, defensible efficiency is what justifies seat prices cited around $600 per user per month.

4. 4

   Meet audit and regulatory expectations

   Reviews feed journal submissions and regulatory dossiers, so the output must be audit-ready and PRISMA-compliant, with a complete record of decisions. Auditability is a core feature, not a nice-to-have, because pharma and health-technology-assessment buyers require it. Trustworthiness under scrutiny is what lets your tool into high-stakes work.

5. 5

   Sell to pharma, device, and academic teams

   Your buyers are pharma and medical-device evidence teams, academic reviewers, and health-technology-assessment groups, sold per-seat and per-enterprise. Lead with compliance plus time savings, the two things they cannot get from a generic AI chatbot. Enterprise standardization across an evidence function is where the revenue compounds.

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