New startup ideas · AI for people who run the AI themselves · Analysts, researchers and creators running their own stack
startup concept
Stackfeed
A personal data pipeline that repairs itself when sources change
A self-maintaining pipeline for analysts who keep proprietary datasets current by hand: point it at recurring sources such as SEC filings, agency releases and earnings transcripts, and it builds extraction schemas, detects when a source's format shifts, patches its own extractor, and delivers dated diffs to the analyst's dataset.
- Software subscription
- Small business
- Rides the Fall 2026 YC Request for Startups 'Self-Maintaining APIs'
4
similar startups, last 2 years (9 all-time)
yes
8 matching federal grants and programs
Direction supported by government programs and grants
Test it before you build it
$600 · 4 weeks · 25 prospects
For $600 and 4 weeks, prove that solo filing-tracking analysts will prepay $149/month for machine-maintained diffs they did not build themselves.
Riskiest assumption · A solo analyst who has been burned by breaking scrapers will pay before launch for machine-maintained numbers - trusting dated, flagged diffs they did not produce themselves - rather than insisting on re-verifying every figure by hand, which the stated risk says one silent bad patch would destroy forever.
1Focus group: who and where
A solo financial or policy analyst - an independent equity researcher, a paid finance newsletter author, or a one-person research shop - who maintains a proprietary dataset from SEC filings and lost hours this past quarter re-fixing a broken scraper or copy-paste routine when a filing format changed.
where to find 25 · Value Investors Club and MicroCapClub (communities of exactly these analysts, message members whose write-ups cite filing data), the Substack Finance leaderboard (a public list of paid finance newsletters - authors' emails are on their About pages), r/SecurityAnalysis, and CFA Society New York chapter events for in-person conversations. FinTwit on X for warm replies to analysts who publicly complain about EDGAR parsing.
2Sell first, build later
A founding-analyst subscription: we keep your SEC-filing dataset current through the Q3 2026 filing season - structured pulls from the 10-Ks, 10-Qs and 8-Ks of your tickers, delivered as dated diffs within 24 hours of each filing, with every format shift flagged loudly and held for your approval, never silently patched. First delivery within 5 business days of you approving the inferred schema.
the ask · $149 per month, founding price locked for 12 months (list price will be $249)
a real yes · A real yes is a paid $149 invoice with tickers and schema submitted. Not a yes: 'this would save me hours', an unpaid trial request, an offer to intro other analysts, or a promise to subscribe at launch.
3Small experiments
The first one attacks the riskiest assumption; each ends with a number that says whether to run the next.
1. Sell the founding month on calls
$250 · 14 days
Hand-build one sample artifact from real Q2 2026 filings: three quarters of 10-Q line items for 5 widely-held tickers, shown as a dated diff with a change log, pulled from EDGAR by hand. Book 15 calls with analysts from Value Investors Club, MicroCapClub and Substack Finance authors, walk through the sample, and end every call by invoicing $149 for the first month, payable by card or ACH. Founder runs every call.
keep going if · 4 of 15 called analysts pay the $149 invoice within 48 hours
2. Silent-patch versus flagged-diff probe
$0 · 5 days
Email the 10 most engaged prospects two versions of the same diff after a simulated format shift: one where the extractor silently patched itself, one where affected fields are marked 'unverified - source format changed' and held out of the dataset. Ask which version they would keep paying for and what one silently wrong number would do to their trust. This tests the card's stated risk directly and sets the product's failure behavior.
keep going if · 8 of 10 choose the flagged version and say a silent wrong number would end the subscription
3. Their-own-tickers diff drop
$350 · 10 days
For 10 prospects who did not pay after the call, hand-build one real diff covering 3 tickers they actually track (visible in their published work), including one earnings transcript pull, and email it free with a second $149 invoice attached. This isolates whether trust requires proof on their own data rather than a demo dataset.
keep going if · 3 of 10 previously unconverted prospects pay after seeing their own tickers
4Collect a deposit up front
Tesla took $1,000 refundable reservations for the Model 3 and $100 for the Cybertruck before building either: the deposit is the measurement, not the revenue.
$149
per prospect, refundable
how · First month prepaid: a $149 invoice sent at the end of the call, payable by card or ACH. A subscription buyer should pay like a subscriber from day one - no reservation gimmick, because delivery of the (initially hand-run) service starts within a week, so the natural instrument for this small-business buyer is the first month up front at a founding price locked for a year. set up: Stripe Invoicing ↗
what it reserves · One of 10 founding slots for the Q3 2026 filing season, the $149/month price locked for 12 months, and their exact tickers and schema set up first
refund · Full refund any time before the first diff is delivered, and a full refund of the current month if any delivered number is shown to be wrong.
target · 8 paid first months from 25 prospects within 28 days
Go: build it if
8 of 25 prospects prepay $149 within 4 weeks, and 8 of 10 in the probe demand loud-fail behavior - build the extractor with flag-and-hold as the core loop.
Kill: stop if
Fewer than 3 prepayments after 15 calls plus 10 personalized diffs, or a majority of prospects say they would re-verify every delivered number by hand regardless - then the trust the product depends on cannot be bought and the idea dies.
5 Scripts to run itoutreach message, landing copy, deposit terms · click to open
outreach message
If you keep a dataset current from SEC filings, you probably lost an evening this quarter re-fixing an extraction after a filing format changed. I keep that dataset current for you: structured pulls from your tickers' 10-Ks, 10-Qs and 8-Ks, delivered as dated diffs within 24 hours of filing - and when a format shifts, the affected fields are flagged and held, never silently patched. First month is $149, locked at that price for a year for 10 founding analysts. Can I take 20 minutes this week to see your current setup and show you a sample diff?
landing page
Your SEC filing dataset, kept current, every change flagged $149 for your first month: dated diffs from your tickers' 10-Ks, 10-Qs and 8-Ks within 24 hours of filing, founding price locked for 12 months Prepay your first month - 10 founding slots for the Q3 2026 filing season
deposit terms
Your $149 prepays your first month and reserves one of 10 founding slots for the Q3 2026 filing season, at $149/month locked for 12 months. You get a full refund any time before your first diff is delivered, and a full refund of the current month if any delivered number proves wrong. First delivery lands within 5 business days of your schema approval.
Would you run this test?
One tap. The yes-share feeds the Demand pillar of this idea's score; nobody sees who answered.
Budgets are out-of-pocket estimates for a team of one to three, US market. Size the deposit to the deal, and check the terms before taking money in a regulated line.
Scorecard
Ranked against every idea in the catalog: trend, demand and 100x potential from the corpus, competition relative to the other ideas. A generated concept has no judges or swipes yet, so its pillars use the data signals only.
27
Idea Score, 0-100 · raw 16.8 x 1.61
Active
competition: more crowded than 57% of ideas · headwind x0.71
+3.8
government priorities, secondary (31 matching grants)
Trend
18
Is the wave forming now? 2025-26 entrants vs 2023-24, rounds since 2025, the sector's live-batch direction, the 2026 trend analyst.
- Entrants 2025-26 vs 2023-24 (similar companies)3
- Rounds announced 2025+ in the sector0
- Sector direction (live batch)50
Demand
53
Does anyone want it? YC's current RFS, companies already paid for something similar, the operator judge, founders' yes-rate in decks, readers who would run the test.
- YC asks for it (current RFS: idea / sector)30
- Someone already pays (similar companies, recent / all-time)75
100x potential
6
Can it return a fund? The venture judge (double weight), market-size and moat axes, neighbours still alive, the technologist judge.
- Neighbours still alive6
Score = 100 x cbrt(Trend x Demand x 100x) x (1 - 0.5 x crowding) + government bonus (max 5), calibrated so the 95th-percentile idea scores 90 (order never changes). A geometric mean: a weak pillar cannot be papered over. Percentiles are among the 382 ideas in the catalog; the terms matched were personal, pipeline, repairs, itself, sources, change, self-maintaining, analysts.
The concept in full
- What
- A self-maintaining pipeline for analysts who keep proprietary datasets current by hand: point it at recurring sources such as SEC filings, agency releases and earnings transcripts, and it builds extraction schemas, detects when a source's format shifts, patches its own extractor, and delivers dated diffs to the analyst's dataset. In the first hour the user adds three source URLs, approves the inferred schema, and gets their first structured pull with a change log.
- Grounded in (2025-2026 signals)
- 'Self-Maintaining APIs' is a current Fall 2026 YC RFS theme. n8n raised a $180 million Series C at $2.5 billion in October 2025 on revenue past $40 million growing tenfold, proving people wiring their own automated workflows pay at scale. 2025 cohort companies Hanji ('Turn your hardest documents into reliable data'), Clidey ('Turn scattered data into one platform for decision-making') and Libretto ('Turn website workflows into reliable APIs') mark the adjacent territory.
- What it rides
- Rides the Fall 2026 YC Request for Startups 'Self-Maintaining APIs': the same self-repair pattern applied not to a product API but to the private dataset an individual analyst maintains and monetizes.
- Why now
- YC put self-maintaining data plumbing on its Fall 2026 RFS list, and n8n's October 2025 round at $2.5 billion showed self-run automation is a venture business; yet the brief's keyword data shows 'self-serve' in only 7 pitches from the last two years, so the individual-analyst version is open.
- Wedge: first customer and entry point
- Solo financial and policy analysts who currently lose hours a week re-fixing scrapers and copy-paste routines; entry point is one source type, quarterly SEC filings, done end to end with diffs.
- Closest real companies, as the generator saw them
- Hanji converts hard documents to data as a one-time transformation; Clidey aggregates scattered data for team decision-making; Libretto turns website workflows into APIs for products. Stackfeed differs by maintaining one person's recurring dataset over time, with self-repair as the core loop rather than initial extraction.
- Main risk
- Format-shift self-repair that silently produces wrong numbers is worse than breaking loudly, and one bad patch loses the analyst forever.
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Public money in this direction
US federal grants and open opportunities matched to the concept's terms.
National Science Foundation · I-Corps · $50K
NIH / NIDDK · SBIR phase I · $314K
NIH / NHLBI · SBIR phase I · $314K
NIH / NIEHS · SBIR phase I · $306K
NIH / NIAAA · SBIR phase I · $307K
National Science Foundation · HBCU-EiR - HBCU-Excellence in · $256K
National Science Foundation · HBCU-EiR - HBCU-Excellence in · $101K
National Science Foundation · MATHEMATICAL BIOLOGY · $674K
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