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How One Research Platform Plans to Find Money
A plain-language version of “QNFO Funding Strategy — Verified Funder Landscape & Shortlist”
The short version
QNFO is a one-person research project that uses AI to write open science papers. It needs money to keep going. This paper checks which funders might help and ranks the best matches.
What QNFO is and what it needs
QNFO is a two-year-old project run by one person. It uses AI tools to help write research papers. The papers are free for anyone to read. The project has made about one thousand papers so far. They cover seven topics, including physics and how we know what we know.
Running this costs money. The main AI tool costs four hundred to six hundred dollars each month. Sometimes tests cost extra. Right now, the founder pays everything from personal savings. This cannot continue.
The project asks for twenty-five thousand to sixty thousand dollars per year. This would keep the work going, make the papers easier to find without central control, and turn the checking methods into free tools for everyone.
What the project already has
The project has two checked and registered papers that prove quality work. It has a live website. It has a method for finding gaps in knowledge, called the Universal Ignorance Audit. It has put papers on a decentralized storage system before. It has a social media presence. It also has careful spending rules with hard limits.
What is still unknown
Some facts could block bigger funding later. The founder has no registered company. Some funders need one. The founder's home country and tax situation are unknown. This matters for tax on grants and for one German program. Some funders publish winner names, so the founder must decide if they want public identity. The real monthly costs are higher than hoped-for future estimates. Applications must use honest numbers. Some funders pay in digital money, which needs special accounting.
Which funders were checked and ranked
The paper checked twenty-six web pages live on one day. It found eleven active funders and ranked them by three things: can one person apply, does the topic match, and how easy is applying.
The top match is NLnet NGI Zero. It funds individuals, loves open internet tools, and opens calls on September third with a November third deadline. Second is Emergent Ventures, which decides fast and takes rolling applications. Third is Foresight Institute, which cares about how we know things and decides monthly.
Some funders were set aside for later because they need a company or have annual cycles. Several programs were found closed or unverified.
How to ask each funder
Each funder needs a different story. Emergent Ventures gets a one-page pitch about making knowledge production into public infrastructure. NLnet gets a plan to open-source the tools and mirror papers on decentralized storage. Filecoin gets the real problem of keeping one thousand papers safe forever.
The plan over time
The founder should apply to Emergent Ventures now while drafting the NLnet proposal for September. Foresight and Gitcoin follow in fall. Filecoin comes after the papers are mirrored. A German fellowship waits until twenty twenty-seven. Big foundations wait until a company exists.
What could go wrong
Saying "nearly one thousand papers" without context sounds like spam to serious funders. Lead with the two checked papers and the audit method. The project runs on one company's servers now, so be honest: decentralization is the goal, not the current state. Typos in early notes must never reach applications. Some funders publish winners, which exposes identity. Digital money grants need tax planning first. Funders buy specific deliverables, not big dreams.
What this paper does not show
This paper does not prove any funder will say yes. It does not resolve the unknowns about company, home country, or tax. It does not check funders beyond what their web pages said on one day. The ranking uses weights the author chose. The cost-cutting target of one hundred to two hundred dollars monthly is not the real spending now. The paper does not test whether any pitch actually works.
Words used here
- corpus
- a collected body of written works, like a library
- decentralized
- stored across many computers rather than one company's servers
- eligibility
- whether you are allowed to apply
- epistemics
- the study of how we know what is true
- fiscal sponsorship
- using another group's legal status to receive money
- IPFS
- a way to store files so no single company controls them
- rolling applications
- you can apply anytime, not just on one deadline
Learn more in plain language
- DecentralizationSimple English Wikipedia
This plain-language version was written by an AI model from the text of the paper and checked against plain-language rules: everyday words, no mathematics, no unexplained names. It leaves details out and can still be wrong; the paper is the source of record. To report a problem, open the paper, select the passage and choose Report.
For specialists: the technical digest, quoted from the paper
In the paper's words
This paper presents a verified funder landscape and fit-score shortlist for sustaining QNFO, a two-year-old, solo-run, AI-assisted research platform that has produced an open corpus of approximately 1,000 method papers across seven program areas. Every funder fact was verified by live HTTP retrieval on 2026-08-13 across twenty-six pages spanning Web3 and IPFS ecosystem grantors, open-science philanthropy, and decentralized-science programs; anything not verified live is explicitly flagged. The analysis scores eleven funders on eligibility for an unaffiliated individual, topical fit with decentralized and epistemics-oriented research, and application friction, yielding a weighted ranking led by NLnet NGI Zero (calls open September 3, 2026; deadline November 3, 2026, 12:00 CEST) and Emergent Ventures, followed by the Foresight Institute, Filecoin Foundation, the Ethereum Ecosystem Support Program, Gitcoin, and the Effective Altruism funds.
The abstract, verbatim, and its opening sentence is the claim. Every line below is quoted from the text.
Numbers it reports
Actual spend is $ 400–600/month for the DeepChat AI stack alone (a Claude evaluation PoC cost $ 400 in under a week), with an optimized Cloudflare AI-infrastructure target of $ 100–200/month — an optimistic cost-cutting projection, not the current total.
from 1. The Ask (One Paragraph)Budget floor — RESOLVED (2026-08-13) — actual spend is $ 400–600/month for the DeepChat AI stack alone , with a $ 400-in-under-a-week Claude evaluation PoC spike; the $ 100–200/month figure is an optimistic cost-cutting projection for optimized Cloudflare AI infrastructure only , not the current total.
from 3. Application-Readiness Gaps (Phase-0 Ignorance Audit — what we do NOT know)Funder Status (verified 2026-08-13) Eligibility Amount Deadline URL Emergent Ventures (Mercatus) ACTIVE — low-overhead, rolling Individuals worldwide, age 13+ Grants, [VERIFY] typical $ 1k– $ 100k+ Rolling mercatus.org/emergent-ventures NLnet / NGI Zero ACTIVE — "calls open September 3, 2026 , deadline November 3, 2026 12:00 CEST " (verified on nlnet.nl/propose) "Individuals and organisations of any type" Micro-grants €5k–50k Nov 3, 2026 (then every 2 months, odd months) nlnet.nl/propose/ Foresight Institute ACTIVE — "Application deadlines at the end of each month" Individuals/teams Grants + prizes Month-end, monthly foresight.org/engage/grants/
from Tier 1 — Apply Now (rolling or near-term deadlines)Window Action Aug 2026 Draft EV application + gather readiness-gap answers (entity, residency, budget floor) Sep 3, 2026 NLnet calls open → submit proposal early (deadlines are hard) Sep–Oct 2026 Foresight month-end application (if epistemics-aligned topic); Gitcoin GG24 listing Nov 3, 2026 NLnet deadline (12:00 CEST) Q4 2026 Filecoin Builder Next Step (after IPFS corpus milestone) Q1–Q2 2027 STA Fellowship window (watch sovereign.tech/programs/fellowship); Templeton/Sloan only if entity formed
from 7. Sequencing Calendar
How it is done
This paper presents a verified funder landscape and fit-score shortlist for sustaining QNFO, a two-year-old, solo-run, AI-assisted research platform that has produced an open corpus of approximately 1,000 method papers across seven program areas.
from Abstractfunding strategy; decentralized science; AI-assisted research; open knowledge infrastructure; grant landscape; Web3 Date: 2026-08-13 Source note: QNFO research note (2026-08-12), included in this deposit as source-note-2026-08-12.md (funding manifesto) Method: All funder facts below were verified by live HTTP fetch on 2026-08-13 (26 pages, status + title + keyword extraction).
from KeywordsQNFO is a two-year-old, solo-run, AI-assisted research platform that has produced an open corpus of ~1,000 method papers, organized across seven program areas (ultrametric physics, laws of form, information physics, paradigm engineering, consilience, platform, demos), with a documented audit discipline (citation audits, post-publication adversarial review, ignorance auditing) and an existing decentralized deployment history (IPFS).
from 1. The Ask (One Paragraph)Deliverable: (1) open-source the QNFO research pipeline (audit tools, ignorance-audit method, generation-detection), (2) IPFS-mirror the full corpus with content-addressed citations, (3) publish the protocol as libre-licensed content.
from 6. Per-Funder Pitch Skeletons
What would falsify it
The paper's text states no explicit falsification criterion; the limits below are what it says about where the claim stops.
Where the claim stops
This paper presents a verified funder landscape and fit-score shortlist for sustaining QNFO, a two-year-old, solo-run, AI-assisted research platform that has produced an open corpus of approximately 1,000 method papers across seven program areas.
from AbstractEvidence records (verified live, HTTP 200): the QNFO archive https://papers.qnfo.org/papers/universal-ignorance-audit/ — "The Universal Ignorance Audit: A Fifteen-Question Method for Systematic Inquiry into the Structure of Not-Knowing" the QNFO archive https://papers.qnfo.org/papers — "Knowing What We Do Not Know: Ignorance Auditing, AI-Generation Detection, and the Epistemic Lessons of an AI-Assisted Research Pipeline"
from KeywordsThey do not block Tier-1 applications but must be resolved before Tier-3: Legal entity — no registered entity known.
from 3. Application-Readiness Gaps (Phase-0 Ignorance Audit — what we do NOT know)
Where to read
- Abstract177 words · 1 min
- Keywords107 words · 1 min
- 1. The Ask (One Paragraph)170 words · 1 min
- 2. Applicant Assets (citable evidence)153 words · 1 min
- 3. Application-Readiness Gaps (Phase-0 Ignorance Audit — what we do NOT know)197 words · 1 min
- 4. Verified Funder Landscape524 words · 2 min
- 5. Fit-Score Matrix192 words · 1 min
- 6. Per-Funder Pitch Skeletons296 words · 1 min
- 7. Sequencing Calendar68 words · 1 min
- 8. Risks & Framing Cautions153 words · 1 min
- 9. Next Actions (agent-executed, per user standing preference for autonomous outreach)57 words · 1 min
Read from the paper itself: 16 sections, 2,094 words. Nothing in this digest is written by a model; a line that is not a sentence of the paper is not shown. Have a specific question? Ask this paper.
The full text · Ask the whole corpus
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