A retrieval-augmented grant development platform designed to support research infrastructure equity within learning health systems while preserving investigator judgment, data control, and NIH-aligned governance.
Overview
Advanced Idea Manufacturing has developed GrantBot, a retrieval-augmented generation platform designed to reduce structural inequity in academic grant development, and has made the architecture available to a learning health system operating within a major university system and large hospital group under AIM’s Benevolent IP framework.
Addressing Grant Development Inequity
GrantBot addresses a well-documented asymmetry in the NIH funding environment: with research project grant success rates at approximately 13 percent and proposal preparation requiring an estimated 200 to 500 person-hours per application, institutions with limited pre-award infrastructure face a compounding disadvantage that correlates poorly with the scientific merit of their investigators’ ideas.
Platform Architecture
The platform provides nine structured workflows spanning the full grant development cycle — from initial idea review and funding opportunity matching through IRB readiness assessment, regulatory compliance screening, multi-perspective reviewer simulation, narrative consistency auditing, and resubmission analysis — and produces provenance-cited concept packets for investigator review rather than submission-ready text.
On-Premises Data Governance
The system operates entirely on-premises within the institutional environment, with no investigator data or unpublished concept descriptions transmitted to external services. All model inference, vector retrieval, and structured memory functions run on institutional hardware.
The retrieval corpus spans NIH RePORTER from FY1985 to the present, PubMed, PMC Open Access, ClinicalTrials.gov, AHRQ evidence reports, FHIR/ONC standards, and OHDSI/OMOP methods documentation, embedded at 4,096 dimensions using Qwen3-Embedding-8B.
Specialist Model Council
A sequentially executed specialist model council — including triage, mechanism review, skeptical reasoning critique, quantitative feasibility assessment, and independent synthesis — routes each concept through role-appropriate evaluation before a chairman model generates a structured decision memo.
NIH-Aligned Governance
Governance compliance is architecturally enforced. GrantBot produces analysis artifacts, not draft narrative for submission, in explicit alignment with NIH NOT-OD-25-132. No submission pathway exists within the platform. All outputs are designed to prompt investigator revision and judgment rather than displace it.
Benevolent IP Qualification
GrantBot qualifies for AIM’s Benevolent IP framework under the Human Benefit and Ethical AI criteria: the platform directly advances research infrastructure equity within an academic health system organized around learning health system principles, deploys open-weight models on publicly accessible data sources, and is documented with sufficient specificity to support replication at resource-limited institutions beyond the initial deployment site.
The nominal license reflects AIM’s position that infrastructure of this kind should reach academic medicine at cost of adoption, not cost of access.
White Paper Status
A white paper describing the system architecture, governance framework, and evaluation strategy has been prepared for submission to a peer-reviewed informatics venue.