The command center for research funding.
AIGrantMentor matches your research to the right calls, shows what has actually won funding, positions your idea in the gaps, and prepares a submission that survives review.
No credit card · Institution-wide pilots available · Explore the Intelligence Layer
AI systems for adaptive health infrastructure
Horizon Europe · HORIZON-CL4-2026-DATA-02 · closes in 41d
92%Clinical decision support at the point of care
NIH R01 · PAR-25-118 · closes in 66d
84%Trustworthy autonomy in safety-critical systems
NSF CAREER · NSF-24-593 · closes in 12d
77%Materials informatics for clean energy
DST-SERB · CRG-2026 · open
71%
Why it matches
AI systems for adaptive health infrastructure
- Consortium of 3+ partnersmet
- TRL 4–6 at project startmet
- Open-science data planto do
Funded precedents
- GA-101094521 · €1.2M · 2024
- GA-101076883 · €870K · 2023
- GA-101119044 · €1.5M · 2025
Illustrative data.
- funded-project records
- 2.8M
- programmes normalized
- 96
- source families connected
- 14
Funding pipeline
One continuous path from profile to reviewer-ready submission.
Six stages, one evidence trail. Nothing is re-entered, and every step keeps the records it was based on.
- 01Profile
Your research, understood.
Publications, prior grants, and expertise become a live profile the engine can match against.
- 02Discovery
Every open call, ranked for you.
Alignment scoring against eligibility, priorities, and deadlines — not keyword search.
- 03Precedent
See what actually won.
Your idea is placed among previously funded projects to reveal what agencies rewarded.
- 04Positioning
Claim the white space.
Gap analysis across funded projects, patents, and publications finds the angle that is both novel and fundable.
- 05Refinement
A concept built to the call.
Objectives, work packages, and budget logic are assembled around the agency's own evaluation criteria.
- 06Review
Scored before you submit.
An AI panel reviews against guidelines, completeness, impact, and reviewer expectations while you can still fix it.
Intelligence
Know what gets funded before you write a word.
Matching is only useful when it is grounded in the record of prior awards. The intelligence layer connects profile fit, eligibility, funded precedents, and deadline pressure in a single view.
- Profile-aware call matching
- Funded-project database
- Eligibility screening
Who funds work like yours
Funded projects matching “AI for adaptive health systems”, 2021–2025.
| Horizon Europe | 142€168M | |
|---|---|---|
| NIH | 86$52M | |
| UKRI EPSRC | 54£41M | |
| NSF | 31$18M | |
| DST-SERB | 17₹38Cr |
Bar length = funded projects; the figure beside it is total awarded. Closest precedent to your idea: GA-101094521 · €1.2M · 2024. Illustrative data.
Where the funding has already gone
Funded projects by sub-topic and year. The pale row is the white space.
| Sub-topic | 2021 | 2022 | 2023 | 2024 | 2025 |
|---|---|---|---|---|---|
| Workflow automation | 28 | 34 | 41 | 39 | 44 |
| Decision support | 19 | 22 | 26 | 31 | 29 |
| Federated health data | 8 | 12 | 17 | 22 | 26 |
| Predictive triage | 6 | 9 | 11 | 14 | 12 |
| Explainable triage | 1 | 2 | 0 | 1 | 2 |
Explainable triage for low-resource networks — 6 funded projects in five years, the least crowded pocket that still clears the call's scope. Illustrative data.
Positioning engine
Find the white space between 2.8M funded projects.
Gap analysis places your idea against everything the agency has already paid for, then sharpens it into the angle that is both novel and fundable.
Before / after
AI tool for improving hospital workflows.
Explainable triage automation for resource-constrained care networks, aligned to open-science data obligations and health-system resilience criteria.
Preparation studio
From positioned idea to reviewer-ready submission.
The studio drafts against the call's own structure, keeps every claim attached to a source, and scores the result before a reviewer ever sees it.
- Structured drafting
- Automatic citations and policy alignment
- AI review against call criteria
Proposal outline
- Objectives
- WP1 · Evidence base
- WP2 · Prototype
- WP3 · Evaluation
- Budget
- Impact
Evidence rail
- Nature 2024
- EU Green Deal S3
- Funded: GA 101076xxx
- NIH Data Mgmt 2025
Built on data, not adjectives
The funded-project record becomes a working surface.
| Programme | Topic | Award | Year | Partners |
|---|---|---|---|---|
| Horizon Europe | Climate adaptation analytics | €1.4M | 2025 | 7 |
| NIH R01 | Clinical decision support | $612K | 2024 | 1 |
| NSF CAREER | Trustworthy autonomy | $579K | 2025 | 1 |
| ERC StG | Low-energy edge intelligence | €1.5M | 2023 | 3 |
| DST-SERB CRG | Materials informatics | INR 41L | 2025 | 2 |
| UKRI EPSRC | AI for resilient networks | £890K | 2024 | 5 |
Funded-project intelligence layer — 96 programmes, updated continuously. Illustrative data.
AI review scorecard
4.6 / 5"The methodology section should address data-management obligations under the call's open-science requirements."
Institutional trust
Data governance
Your proposals and ideas are never used to train models or shared across institutions. Tenant-isolated by design.
Security
Encryption in transit and at rest. Role-based access for research offices. SSO available on request.
Methodology
Every match, gap, and review score is explainable. The engine shows which calls, projects, and criteria drove its conclusion.
How the intelligence is built
Public funding databases, calls, publications, and patent records are normalized into one evidence layer.
Matching and gap analysis keep source records attached, so every conclusion can be inspected.
Refresh cadence and source coverage are visible throughout institutional pilots.
Who it is for
Research Offices
Run portfolio-level funding scans across every department and see where your institution is leaving money unclaimed.
Researchers & Labs
Turn a profile and a rough direction into ranked calls, funded precedents, and a positioned proposal concept.
Startups & SMEs
Find non-dilutive funding routes and shape technical roadmaps around the evidence agencies already reward.
Grant Consultants
Use funded-project intelligence, gap maps, and AI review to pressure-test more client proposals with less manual search.
Developers
Built inside a research office, for research offices.
Dr. Ramandeep Singh
Professor & Deputy Dean
Division of Research & Development
Lovely Professional University, India
Your next funded project is already in the data.
See what AIGrantMentor finds for your research profile in under five minutes.
No credit card · Institution-wide pilots available