Opportunity radar
Refresh and filter current calls by sponsor, department, deadline, award size, priority, tags, and other criteria.
Free desktop software · Local AI · v2.2.86
Funding intelligence — and a tiny local AI — that lives on your machine.
TIGER Funding Radar brings current funding opportunities, faculty evidence, NSF/NIH awards, LSU SPA analysis, historical funded-project discovery, and built-in on-device AI for research-idea matching into one focused local workspace.
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One radar. Multiple funding signals.Opportunities · evidence · awards · matching · discovery
v2.2.86
Product walkthrough
See TIGER in action.
A guided walkthrough of the real v2.2.86 interface, including readiness states, opportunity workflows, sponsor awards, SPA analysis, Idea Match, Discovery, and matching.
Created by Ibrahim (Abe) Baggili. The demonstration is packaged locally with this site.Approx. 5 minutes
What it does
From opportunity discovery to evidence-backed matching.
TIGER is designed around the real decisions research leaders and faculty make when identifying calls, understanding historical funding, and building credible teams.
Faculty evidence
Start with an empty local roster, import faculty/researchers from the TIGER Excel template or add them manually, then update scholarly evidence through sources such as OpenAlex and Crossref.
Download the blank faculty template →NSF & NIH awards
Analyze sponsor-side funded-project history separately from institutional SPA accounting and compare institutions, colleges, or departments.
LSU SPA intelligence
Import an authorized SPA workbook locally, validate it, compare colleges and units, and inspect fiscal-year, sponsor, and credited-funding patterns.
AI Idea Match & Discovery
Use TIGER's built-in neural MiniLM model to compare an abstract or research concept against current opportunities, then explore a local historical NSF/NIH discovery index.
Evidence Fit matching
Combine scientific evidence with bounded historical-funding signals, de-duplicate award evidence, and identify Best Fit and Novel Bridge teams.
Tiny AI inside TIGER
Small model. Focused job. Local by design.
Idea Match uses TIGER MiniLM-L6-v2 INT8, a compact neural embedding model that runs locally in the browser inside the TIGER desktop app. After a one-time model setup, TIGER can reuse the local model without an AI API key.
Multi-view semantic matchingTIGER analyzes the whole idea, its scientific core and methods, and program identity instead of relying on a single keyword score.
Full open-catalog coverageThe built-in neural model supplies semantic similarity across the current open opportunity catalog before TIGER applies deeper funding checks.
AI plus explicit evidenceNeural similarity is combined with scientific-objective, domain, program-intent, and funding-mechanism checks so the result is not just an opaque AI score.
Purpose-built, not generativeThe local AI is used to help rank semantic fit between a research idea and funding opportunities. Proposal writing, award prediction, and final funding judgments remain outside this model's role.
What this AI is — and is not.It helps rank idea-to-opportunity fit. It does not write your proposal, does not predict whether an award will be funded, and does not replace the evidence and mechanism checks built into TIGER. In built-in mode, the pasted research idea is not sent to an AI provider.
Built-in Neural AI
Local MiniLMNo AI API key required for built-in Idea Match
Core workflow
A repeatable funding-intelligence loop.
TIGER separates data preparation from matching so you can see exactly what is ready before generating results.
01
Refresh opportunitiesBring current calls into the local opportunity workspace.
02
Verify faculty evidenceMaintain the roster and update scholarly evidence.
03
Refresh NSF / NIHUpdate sponsor-side funded-project history.
04
Import SPAOptionally import an authorized LSU SPA workbook.
05
Perform matchingRun when the required readiness states are satisfied.
06
Analyze & discoverReview opportunities, teams, comparisons, and ideas.
Download
Choose the build for your computer.
Version 2.2.86 is free to use under the TIGER Free Use License below. Clean installs start with no faculty preloaded. The packages contain no source code and no LSU SPA Excel workbook.
Windows
Windows x86-64 · GUI + diagnostic build
Download WindowsmacOS · Apple Silicon
For Apple M-series Macs
Download Apple SiliconmacOS · Intel
For Intel-based Macs
Download Intel MacLinux
Linux x86-64 · portable local app
Download LinuxNeed more than one platform?
Cloudflare Pages-readyDownload any combination of the four platform packages above. Each package includes the latest user manual and a blank faculty-import template.
Clean start by design. TIGER ships with no faculty preloaded and no SPA workbook. Import faculty with the blank template or add people manually; authorized SPA users import their own institutional workbook inside TIGER.
SHA-256 checksums
Windows
cfe707e2df74c22f39971ce55f976d72fec1560d64c6b23fb468886e78b1d48eLinux
fd73b5f4e349a9e93ea5d1c324d03b41f24ebd53ca53d47bda6cd81a53356313macOS Apple Silicon
1e1cef6cb59cee2e993bb4a203a12210468496e00a1a0543639a0c29803b967cmacOS Intel
93c8bc7fe0258774a70bb781251e52deaec8c097fc673f27d560aaac86c7faa3Scholarly evidence setup
Connect OpenAlex with a free API key.
TIGER can use OpenAlex to strengthen faculty identity validation and scholarly evidence. OpenAlex says creating an account is free, the API key is available from your account settings, and the free tier currently includes daily API usage without requiring a payment method.
OpenAlex
Get your free key in about a minute.
- Create a free OpenAlex account.Register at openalex.org.
- Open API settings.After signing in, visit openalex.org/settings/api.
- Copy the key into TIGER.Faculty → Optional OpenAlex API key → Save OpenAlex key.
- Refresh scholarly evidence.Choose OpenAlex or Both when you want OpenAlex included.
Why TIGER uses it
OpenAlex gives TIGER another evidence source for publication history, topics, and researcher identity. It complements Crossref; it does not replace your local faculty roster.
Keep the key private.TIGER stores the saved key locally. Do not include it in screenshots, support tickets, repositories, or public exports.
Read OpenAlex authentication guidance →
Documentation
The full v2.2.86 user manual.
Installation, first-run setup, opportunities, faculty evidence, NSF/NIH awards, SPA import and accounting, comparisons, Idea Match, Discovery, matching, source health, privacy, and troubleshooting.
20-page illustrated guide
The current manual is included with every platform package and is also available separately here.
Download the manualFrequently asked questions
Quick answers before you start.
The most common setup, privacy, readiness, and workflow questions are also included in the updated user manual.
What AI does TIGER use for Idea Match?
TIGER uses its built-in TIGER MiniLM-L6-v2 INT8 neural model. It runs locally in the browser inside the desktop app, creates multi-view semantic representations of the idea and the open opportunity catalog, and combines that signal with TIGER's explicit scientific, program-intent, domain, and funding-mechanism checks. The built-in mode requires no AI API key; after the one-time model setup, the local model is reused. The pasted abstract is not sent to an AI provider in this mode.
Do I need an OpenAlex API key?
Only if you want to use OpenAlex evidence. Create a free OpenAlex account, copy the key from OpenAlex API settings, and save it in the Faculty tab. Crossref can be used independently.
Does TIGER come with faculty preloaded?
No. A clean v2.2.86 installation starts with zero faculty preloaded. The LSU hierarchy remains available as a starting structure, but faculty and researchers are added only by Excel import or manual entry. Existing user data is preserved when you continue using the same TIGER data folder.
What is the easiest way to load a faculty roster?
The fastest workflow is to download the TIGER faculty Excel template, give that workbook to an AI chatbot, provide the official webpage that lists the faculty for your institution, college, department, or research unit, and ask the chatbot to fill the template from that page while preserving TIGER's column headers. Review the completed spreadsheet carefully for names, hierarchy, titles, emails, profile URLs, research expertise, and Include in Matching values, then import it in TIGER's Faculty tab. The AI chatbot is a convenient data-entry aid; you should validate the roster before import.
When does the Faculty readiness light turn green?
After a usable scholarly-evidence refresh completes for the loaded roster. Having names in the roster alone is not enough; the scholarly-evidence prerequisite must be established.
When does Perform Matching become available?
When Opportunities, Faculty Verification, and Funded Projects are all usable and TIGER detects that matching is due because relevant data changed since the last run.
Does Evidence Fit predict whether a proposal will be funded?
No. Evidence Fit is an evidence-alignment score, not a probability of award. It explains alignment based on the evidence TIGER has loaded.
Is an LSU SPA workbook included?
No. Public distributions intentionally include no SPA Excel workbook. Authorized users import their institutional workbook manually.
Does Idea Match send my full research idea to the cloud?
The built-in local MiniLM workflow is designed to keep the full idea on your machine. Review any optional external configuration before entering confidential or restricted information.
Where does TIGER store its data?
TIGER uses a portable data directory beside the executable or application bundle. Back up that directory if you need to preserve imports, local state, keys, and matching history.
Can a research office use TIGER?
Yes. TIGER is intended for both faculty and research-development or research-administration teams that need a transparent workflow for opportunities, evidence, historical awards, institutional comparisons, and team discovery.
Ibrahim (Abe) Baggili, Ph.D.Creator of TIGER Funding Radar
About the creator
Built from a problem I kept seeing in academic research.
Division Chair & Roger Richardson Professor, Computer Science & Engineering, Louisiana State University.
Finding the right funding opportunity is one of the most important parts of academic research, but it is also a surprisingly difficult problem. Faculty may have strong ideas and strong teams, yet the funding landscape is fragmented across sponsors, solicitations, deadlines, historical awards, institutional data, and scholarly profiles.
As an academic administrator, I found this challenge repeating itself for both faculty and the research offices trying to support them. I created TIGER Funding Radar to make that process more transparent, evidence-based, and usable: help faculty locate opportunities that fit their work, understand why they fit, discover potential collaborators, and give research offices a clearer view of the funding landscape.
TIGER reflects the way I think research development should work: combine good data, local context, explainable evidence, and tools that make people faster without hiding the reasoning.
Policies
Free to use. Clear about privacy.
TIGER is distributed as a local desktop application. The policies below explain the software’s privacy model and the rights granted for free use.
Privacy Policy
TIGER is designed to run locally. Application state is stored beside the executable, and local views and matching remain available without sending your local application state to a central TIGER service.
- No account is required by TIGER.
- This website uses privacy-friendly GoatCounter analytics for aggregate visits and download counts; no advertising tracker is used.
- Network access is used when you choose functions that query external sources or enable background opportunity updates.
- SPA workbooks are not bundled with public distributions and must be imported manually when authorized.
- Built-in Idea Match is intended to keep the full research idea on your machine.
Free Use License
Version 2.2.86 is provided free of charge for personal, educational, academic, research, government, and internal organizational use, subject to the license terms.
- You may use unmodified binary distributions without a license fee.
- You may share unmodified copies for free when the copyright, license, and attribution remain intact.
- You may not sell, relicense, white-label, or offer TIGER as a paid hosted service without written permission.
- No warranty is provided; users remain responsible for validating results and complying with source-data terms.