01
Winning language disappears
When it goes into ChatGPT, your center no longer owns the trail. You can’t open the original file, and the language that already won funds becomes hard to find again.
The grant memory your research center can use to get more grants.
Upload past proposals and source materials. Organize them as private, Markdown-based institutional memory. Ask questions and get answers from your admitted library—not the open web.
ADMITTED LIBRARY02 / 05
Evaluation plan
2025 proposal
“Our evaluation design pairs implementation evidence with measurable participant outcomes...”
Winning language should not vanish into ChatGPT.
02
Every cycle starts over
Logic models, boilerplate, and reviewer feedback get rewritten or lost—even when your team already proved what works.
03
Guesswork replaces proven sources
Grant writers need reliable sources that have already helped win grants—not generic answers pulled from the open web.
Putting your proposals into ChatGPT means your team can’t open the source, can’t see who approved the wording, and can’t trust the next draft won’t reinvent work you already won with.
See the library, not just the pitch.
Illustrative records shaped like a real grant history—so you can see how GrantMemory surfaces reusable language, outcomes, and citations before anyone opens a blank page.
won65 hrs to write
Adaptive Feedback Supports for Early Reading: A Randomized Study for Students with Learning Disabilities
IES · NCSER Special Education Research Grants (ALN 84.324A)
A 4-year efficacy study testing adaptive digital feedback layered onto Tier 2 reading intervention for students with learning disabilities in grades 2–4.
submitted48 hrs to write
Preparing Special Education Leadership Personnel for Rural and High-Need Districts
OSEP · Leadership Personnel Preparation (CFDA 84.325D)
A 5-year doctoral leadership-personnel program building a pipeline of special education administrators for rural and high-need districts.
lost80 hrs to write
Statewide Coaching Model to Scale Multi-Tiered Systems of Support
OSEP · State Personnel Development Grants, SPDG (CFDA 84.323A)
A 5-year statewide scale-up of on-site MTSS coaching; not funded—reviewers cited insufficient evidence of coaching-model cost-effectiveness at scale.
Where the hours come back: language that already worked.
2023 · OSEP · lost
Rural districts serving fewer than 500 students report average annual special education staff turnover above 25 percent, and more than a third of building principals report no formal preparation in evidence-based tiered instruction. Without sustained, on-site coaching, statewide MTSS implementation stalls at the adoption stage.
2025 · OSEP · submitted
Rural and high-need districts report special education staff turnover exceeding 25 percent annually, and most building leaders enter their roles with no formal preparation in evidence-based tiered instruction or special education leadership. Without a sustained pipeline of trained leadership personnel, these districts cannot build or sustain systems-level supports.
Illustrative only. Shared framing carried from a prior cycle into a personnel-pipeline case—hours saved on needs-statement drafting and re-citation.
Cited chat over the admitted library
Ask: Where did we describe rural special education turnover for a needs statement?
Two admitted applications share that framing: the 2023 SPDG package (lost) and the 2025 leadership personnel package (submitted). Both cite ~25% annual special education staff turnover and limited principal preparation in tiered instruction. Prefer the 2025 wording if you are building a personnel pipeline case; keep the 2023 reviewer note about cost-effectiveness if you reuse coaching language.
SPDG statewide coaching model2023 · OSEP · lost · needs-statement.md
Leadership personnel preparation2025 · OSEP · submitted · needs-statement.md
See the graph: how your library connects.
Every admitted proposal, section, funder note, and outcome becomes a node. The graph is how you find language that already worked—without digging through Drive.
Live preview: library hub linking needs, methods, funders, and outcomes.
A Markdown second brain: from file pile to a citation trail.
- 01
Collect
Past grants, logic models, budgets, bios, funder language, reviewer notes, and related documents.
- 02
Convert
Files become Markdown with structured metadata and live in a secure backend.
- 03
Admit
Someone on your team confirms each item before it enters the library.
- 04
Ask
Questions and answers stay inside your admitted library—not the open web. Every answer carries sources.
- 05
Improve
Upload your grant responses—wins or losses—after each application so the next one starts smarter.
It is not a shared folder. It is not a public chatbot. It is your center’s grant memory with controlled access and a citation trail—built only on your information, not random data from the web.
Your center’s history, with citations you can open.
Upload & organize
Store proposals, source materials, budgets, bios, funder language, and reviewer notes as private Markdown with metadata in a secure backend.
Admit before it counts
Someone on your team confirms each item before it enters the library. Nothing becomes “memory” until a person says so.
Ask with sources
Question-and-answer stays inside the admitted library. Every answer points back to your documents—not an anonymous web model.
Close the loop
Upload your grant responses—wins or losses—after each application so the next one starts smarter.
ChatGPT, Drive, and custom AI—versus GrantMemory.
ToolWhat you actually get
ChatGPTGeneric AI answers from the open web and training data. You can’t open the original proposal, and language that already won funds gets mixed with everything else.
Shared DriveYou hunt folders for one file. GrantMemory surfaces relevant options while you write each part of the application—with sources attached.
Custom AI buildMonths of engineering and still hard for grant writers to use. GrantMemory is ready for the grant cycle: funder, year, status, seats, and reviewer notes.
GrantMemoryPrivate library of your admitted materials. Answers only from your history. Citations you can open. Built for how grant teams actually work.
Simple pricing for your center.
PRIMARY
GrantMemory
Workspace for your team: upload, organize, and cited chat over your admitted grant library.
$5,000 / year
Positioned to return far more than that—up to 100×—through shared tools and institutional memory you stop rebuilding every cycle.
OPTIONAL
White-glove
Setup help, conversion quality assurance, and team training when you do not want to self-serve the first library.
Talk with us
Private by default.
- Workspaces are not public or shared across institutions.
- Your content is not used to train public foundation models.
- Seat-based access, export paths, and deletion paths are built in.
Scholar Second Brain is the personal tool.
For individual scholars who want a private writing memory. People can plug personal memory into a center’s GrantMemory when they choose—sharing both ways by consent. GrantMemory stays the institutional product.