Trusted by NIH-funded researchers

Your NIH grant, written
by experts.
Peer-reviewed before
you submit.

FrankGrant combines AI with 25 years of NIH grant writing expertise and $7M+ in awarded grants. We write your application, simulate peer review, and certify it before delivery.

🏆 $7M+ in NIH awards
🔬 Study Section simulation
✅ Three-pass quality review
The Process

How FrankGrant Works

From your research idea to a submission-ready NIH application — in 5 to 7 business days.

1

Describe Your Research

Tell us about your science in plain language using our intake form. Our system extracts your aims, mechanism, targeted NIH institute, and commercial potential. You provide the science — we provide the structure, compliance knowledge, and reviewer psychology.

2

We Write and Simulate Review

FrankGrant generates every section of your NIH application — from Specific Aims to Significance, Innovation, Approach, and Commercialization Potential. Then we simulate the peer review process: three independent reviewer personas score your grant before you ever submit.

3

Certified and Delivered

Every grant passes our mandatory three-pass quality review: scientific accuracy, NIH compliance, and reviewer simulation scoring. If the impact score is not competitive, we rewrite before delivery. You receive a complete, submission-ready package with all sections and citations verified.

Featured Capability

Peer Review Before You Submit

Our Study Section simulation identifies weaknesses before real reviewers do — so you fix them before they count.

Study Section Simulation Results
Mechanism: SBIR Phase I · Simulated: NCI SEP · FOA: PA-24-059
Impact Score
99
Competitive (Excellent)
Dr. Sarah Chen
Basic Scientist · Molecular Biology
2
  • Strong scientific rationale and clearly stated hypothesis
  • Excellent preliminary data supporting feasibility
  • Well-qualified PI with relevant track record
Innovation claim could be more precisely articulated in the context of existing literature
Dr. Marcus Williams
Translational Researcher · Oncology
3
  • Compelling clinical significance and clearly defined unmet need
  • Realistic timeline with measurable Phase I milestones
Sample size justification should include explicit statistical power calculation for primary endpoint
Dr. Patricia Rodriguez
Biostatistician · Clinical Trials Design
2
  • Well-designed experimental approach with appropriate controls
  • Alternative strategies clearly identified and justified
Missing data handling plan for primary endpoint needs to be specified
Certified for delivery — Impact score 24 is competitive. Weaknesses addressed before submission. Ready to submit to NCI.

How We Compare

Compared to human consultants and generic AI writing tools — across every dimension that matters.

Feature Human Consultant Generic AI FrankGrant
Cost $5,000–$15,000 $20–$50/mo $2,500 + 3% if funded
Timeline 4–8 weeks Instant (unreviewed) 5–7 business days
NIH grant expertise Varies widely None — generic 25 years · $7M+ awarded
Peer review simulation Not offered Not offered Always included
Citation verification Manual — inconsistent None — hallucinations common 5 databases verified
NIH compliance check Manual None FOA-specific automated
Quality certification None None Three-pass mandatory
You own the IP and science Yes Terms unclear 100% — always
Success-aligned pricing Full fee regardless Subscription regardless Success fee if funded
Early Access

What Researchers Say

From our first cohort of researchers who used FrankGrant for their NIH applications.

"The Study Section simulation caught three specific weaknesses in my approach section that I had completely missed. The final grant scored a 24 — we are waiting on Notice of Award right now."

S
Sarah K.
Assistant Professor · Biomedical Engineering

"I was skeptical that AI could handle the commercialization section for our STTR, but the commercial reviewer panel gave us feedback that was sharper than any grant consultant I have worked with previously."

M
Marcus T.
Co-founder · Oncology Therapeutics Startup

"The three-pass quality review is not a gimmick — it caught a citation that did not actually support the claim we were making. That kind of detail is what saves submissions from getting triaged."

P
Patricia R.
Research Director · Academic Medical Center

Simple, Aligned Pricing

We succeed when you get funded. That is why we charge a success fee — not a flat retainer regardless of outcome.

Self Service — SaaS
$149 /month
  • AI-powered grant writing tools
  • Study Section simulation engine
  • Three-pass quality review
  • FOA-specific compliance checking
  • Citation suggestions and verification
  • Export to DOCX format
  • Unlimited revisions
  • All NIH mechanisms supported
Try FrankGrant →

Phase II and Fast Track from $4,500. R01/R21 from $3,500. See full pricing →

Common Questions

Yes — completely and without reservation. FrankGrant prepares the writing based on your science, your data, and your research direction. Your intellectual property, your research, your data, and your grant application are 100% yours. We are a writing and review service, not a co-author, and we make no claim on any funded research that results from our work.
If your grant is funded, you pay 3% of the total award amount within 30 days of receiving your Notice of Award. This fee comes from your company or institution's operating funds — not from the grant itself. NIH policy prohibits contingency fees being paid from grant funds directly. We only earn the success fee if you get funded, which aligns our incentives entirely with yours. If you do not get funded, your total cost is only the upfront fee.
Most Phase I grants are completed in 5 to 7 business days from the time you submit your intake form with complete information. Complex mechanisms (Phase II, Fast Track, R01) may take up to 10 business days. We include a minimum of three rounds of revision within the quoted timeline. We strongly recommend engaging us at least 2 weeks before your target submission date to allow adequate review time.
Our Study Section simulation is built on 25 years of reviewer psychology, NIH scoring rubrics, and analysis of funded grants across multiple institutes. It is designed to identify the same weaknesses that real reviewers consistently flag — vague innovation claims, underpowered experiments, missing alternative strategies, and compliance issues. While no simulation can guarantee a specific outcome, applications that score competitively in our simulation consistently perform better in real review.

View all questions →

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