New startup ideas · AI and software · Data for AI
startup idea
Groundfeed
A marketplace where ordinary people sell everyday real-world recordings to AI labs.
A consumer app plus an embeddable SDK that lets anyone record mundane real-world data - chores on camera, receipts, handwriting, phone screen sessions - and sell it into standing dataset orders from model builders.
- Marketplace
- Consumer
- $1-10B market
- Platform others build on
- Global from day one
3/5
venture judge
2
similar startups, last 2 years (16 all-time)
96%
of 4 nearest real companies still alive
yes
7 matching federal grants and programs
Direction supported by government programs and grants
Test it before you build it
$1,200 · 4 weeks · 25 prospects
For $1,200 in 4 weeks, prove that at least two US robotics or world-model labs will pay real money for household video collected by ordinary consumers, before any app, SDK or marketplace exists.
Riskiest assumption · A robotics or world-model lab data lead will pay for household-task video collected by uncontracted consumers, rather than insisting on the contracted, controlled collection that DeepReach and Human Archive already sell them.
1Focus group: who and where
The data acquisition lead or research engineer who owns manipulation training data at a US robotics or world-model lab of 20 to 500 people, currently paying contracted collectors and short of egocentric household footage for the next training run.
where to find 25 · The Hugging Face LeRobot Discord, where robotics data people discuss dataset gaps daily; the corresponding-author emails on the DROID, Open X-Embodiment and Ego-Exo4D dataset papers plus the YC directory filtered to robotics and world-model companies; the public speaker rosters of the Humanoids Summit in Mountain View, cross-referenced to reach the data leads on X, where embodied-AI researchers announce datasets.
2Sell first, build later
A 100-hour first-person video corpus of household tasks (cooking, cleaning, laundry) collected from US consumers to the lab's written spec, QC graded and PII scrubbed, delivered 30 days after the scope is signed.
the ask · $3,000 per 100-hour pilot corpus; repeat orders quoted at $25 per QC-passed hour.
a real yes · A signed pilot scope with the $1,500 invoice paid counts. Requests for the free sample reel, 'interesting, keep us posted' replies and offers to share data for free do not.
3Small experiments
The first one attacks the riskiest assumption; each ends with a number that says whether to run the next.
1. Sell the corpus spec
$150 · 10 days
Write a one-page datasheet for a 100-hour first-person household-task video corpus: camera spec, task taxonomy, QC thresholds, PII scrubbing method, $3,000 pilot price, 30-day delivery. Email it to 25 named data leads pulled from the paper author lists and Discord, asking for a 20-minute spec call. One founder runs all outreach and calls.
keep going if · 6 of 25 book a spec call and 3 of those ask for sample footage or pilot terms
2. Prove consumer supply exists
$450 · 7 days
Post a paid recording gig on r/beermoney, Craigslist Gigs in two metro areas, and Prolific: $30 for 2 hours of first-person phone footage of dishes, laundry and cooking. Pay the first 12 usable submitters and cut a 3-minute sample reel for the lab calls.
keep going if · 150 applicants within 7 days and 12 of the first 15 accepted submitters deliver clips that pass a written QC checklist
3. Close two paid pilots
$600 · 14 days
Send every lab that took a call a one-page pilot scope: 100 hours to their written spec, QC graded, delivered in 30 days, $3,000 total with $1,500 invoiced on signature. Fund the collection run from the deposit plus budget, using the Experiment 2 contributor pool.
keep going if · 2 of the labs that took calls sign the scope and pay the $1,500 invoice
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.
$1,500
per prospect, refundable
how · A 50 percent deposit ($1,500 of the $3,000 pilot) invoiced against a one-page scope the lab's research or data lead signs; labs already pay small data vendors by invoice, so a signed scope plus a paid invoice is the natural instrument for this buyer, not a consumer-style reservation. set up: Stripe Invoicing ↗
what it reserves · A dedicated 100-hour collection run against the lab's written spec with a delivery date 30 days out and agreed QC thresholds.
refund · Refunded in full within 5 business days if the delivered corpus misses the QC thresholds written into the scope.
target · 2 paid $1,500 deposits from 25 labs contacted within 30 days
before taking money · Footage shot inside homes triggers state recording-consent laws and can capture minors, so require written consent from every person on camera and reject any clip showing a child before a single frame is sold.
Go: build it if
2 labs pay the $1,500 deposit within 30 days, and the supply test draws at least 150 applicants with 12 usable submitters at a payout under $8 per usable hour.
Kill: stop if
0 deposits after 25 labs contacted and at least 6 spec calls held, or 5 or more calls end with 'we only buy through contracted collection vendors' and none asks for pilot terms.
5 Scripts to run itoutreach message, landing copy, deposit terms · click to open
outreach message
You are training manipulation or world models and egocentric household video is the bottleneck; DROID and Ego4D only go so far. I run a US consumer collection network and will deliver a 100 hour first person corpus of real household tasks, shot to your written spec, QC graded and PII scrubbed, in 30 days for $3,000. A 3 minute sample reel is ready now. Do you have 20 minutes this week to go through the spec sheet?
landing page
First person household task video, collected to your spec $3,000 buys a 100 hour pilot corpus, QC graded and PII scrubbed, delivered in 30 days Book a 20 minute spec call and reserve your collection run with a $1,500 deposit
deposit terms
Your $1,500 deposit reserves a dedicated 100 hour collection run against your written spec, with delivery 30 days after signature; the remaining $1,500 is due on delivery. If the corpus misses the QC thresholds in the signed scope, the deposit is refunded in full within 5 business days.
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
One score that balances how trendy the idea is, the demand for it and its potential for 100x, with competition measured relative to every other idea in the catalog. Recent startup trends first, government priorities second.
60
Idea Score, 0-100 · raw 37.0 x 1.61
Warm
competition: more crowded than 32% of ideas · headwind x0.84
+2.2
government priorities, secondary (7 matching grants)
Trend
46
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)17
- Rounds announced 2025+ in the sector15
- Sector direction (live batch)100
- 2026 trend analyst50
Demand
52
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)100
- Operator judge: real pain25
100x potential
31
Can it return a fund? The venture judge (double weight), market-size and moat axes, neighbours still alive, the technologist judge.
- Venture judge50
- Market size axis33
- Moat axis20
- Neighbours still alive6
- Technologist judge25
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 272 ideas in the catalog; the terms matched were marketplace, ordinary, sell, everyday, real-world, recordings, consumer, plus.
The idea in full
- What
- A consumer app plus an embeddable SDK that lets anyone record mundane real-world data - chores on camera, receipts, handwriting, phone screen sessions - and sell it into standing dataset orders from model builders. Consumers join self-serve anywhere in the world, an automated QC and PII-scrubbing pipeline grades every clip, and third-party app developers embed the collection SDK to monetize their own users, taking a revenue share like an ad network for data. Field teams run collection campaigns in regions where a lab's coverage gaps demand density.
- Why now
- YC's Fall 2026 RFS names Data for the Real World, and the cluster added 61 new companies in 2025 and 40 already in 2026 - but nearly all of them (DeepReach, Hub, Human Archive) sell to labs B2B with contracted collectors, leaving the consumer supply side unbuilt; the only crowded phrase is 'training data' at 7 companies, all lab-facing.
- Wedge: first customer and entry point
- Start with one dataset labs already pay for but cannot buy at scale - first-person video of household tasks - recruit 5,000 contributors in three countries through the app, and sell the first standardized corpus to a single robotics lab.
- Path to 100x
- Real-world data collection is a $1-10B market growing with every new robotics and world-model lab, and the winner is whoever aggregates the largest verified consumer supply base - liquidity begets liquidity, since labs post orders where contributors already are. The SDK turns thousands of third-party apps into collection endpoints the company does not have to build, which is the platform leverage that takes one team to global scale.
- Ceiling
- If frontier labs consolidate to a handful of buyers who each build in-house collection, demand concentration caps the take rate and the outcome below $1B.
- Closest real companies, as the generator saw them
- DeepReach Inc. builds a real-world data network for robots but sources through B2B partnerships; Luel turns everyday words and actions into training data as a lab-facing product; Human Archive runs a physical AI data lab with its own collectors. Groundfeed differs by making the consumer the seller and by letting any third-party app become a collection surface through the SDK.
- Main risk
- Labs may keep preferring contracted, controlled collection over open consumer supply, leaving the marketplace with sellers but no repeat buyers.
Five judges
Each judge scores every idea in the catalog with a named rubric; the venture judge decides whether a card is shown at all (4-5 is venture-grade).
Venture investor
3/5
Consumer supply could aggregate fast, but the card admits no moat and a handful of labs as buyers, which caps the take rate.
Bootstrapper
1/5
Revenue only after three years of R&D plus field teams in three countries, and the buyer pool is a handful of labs.
Operator
2/5
Labs already prefer contracted collectors, so the paying buyer must abandon controlled collection for consumer clips it did not ask for.
Technologist
2/5
QC and PII scrubbing is standard pipeline work, and the card admits no moat yet while DeepReach and Human Archive already hold the lab relationships.
Risk
2/5
Demand sits with a handful of frontier labs that prefer contracted collection, and 101 cluster entrants since 2025 means no defensible position on either side.
trends
3/5
Same 'Data for the Real World' tailwind as peers, but three R&D-first years and labs preferring contracted collection push revenue past the open window.
Similar startups in the directory
Companies whose pitch matches most of the idea's terms (marketplace, ordinary, sell, everyday, real-world, recordings, consumer, plus): 16 all-time, 2 from the last two years. Same matching as Idea Check.
Personal AI healthcare agent, powered by clinical and wearable data.
Atorie: Luxury Without the Price Tag
AI Native Consumer Loan Servicer
OS for global e-commerce expansion of brands & manufacturers
Transform Images And Videos Into Immersive 3D With AI
A direct to consumer marketplace and influencer network for brands
The platform for buying, selling and managing residential construction
Operator of a customer engagement platform designed to help businesses leverage their data and improve the quality of their engagement with their customers. The company's platform uses open-source technologies with machine learning to bring new data models to market in record time and foster collaboration among business managers to build a broad range of enterprise applications, enabling businesses to create effective run-time consumer models and scores for fraud detection, churn-management, caller-agent mapping, recommendations and cross-sell applications.
Provider of an online marketplace designed to sell fashion apparel and accessories for women. The company's online marketplace stitches garments at scale with full integration into mobile distribution and supply, enabling consumers to get products of their choice at a low cost.
Operator of an e-commerce platform intended to sell handcrafted fine jewelry for everyday use. The company's direct-to-consumer e-commerce platform features products such as rings, pendants, earrings, bracelets, and other luxury jewelry made up of precious and semi-precious stones, enabling women to buy handcrafted accessories online.
Operator of an online retail marketplace intended to sell music band merchandise. The company's marketplace allows fans to discover and buy merchandise such as clothes, accessories, bags, digital video discs, and vinyl from their favorite music artists, enabling fans to buy their desired accessories and merchandise at a reasonable price range.
Sell to people nearby.
The generator's reference companies
Real companies the model named as closest when it wrote the card, with their fate. A check mark is a company the radar could verify in its directory.
Public money in this direction
US federal grants, SBIR/STTR awards and open opportunities from the radar's public-money feed, matched to the idea's terms; the sector totals give the context.
7
grants and programs matching the idea
189
startup-relevant grants in Data for AI
$182M
awarded in the sector, tracked
10
opportunities open now in the sector
- Developing a Learning Platform to Support Minimally Verbal Individuals with Autismawardhigh relevance
NIH / NIDCD · STTR phase I · $313K · posted 2026-07-01
- Collaborative Research: CSR: VERITAS: Secure Vehicular Systems through Intelligent Information Flow Verificationawardmedium relevance
National Science Foundation · CSR-Computer Systems Research · $300K · posted 2026-07-29
- Collaborative Research: CSR: VERITAS: Secure Vehicular Systems through Intelligent Information Flow Verificationawardmedium relevance
National Science Foundation · CSR-Computer Systems Research · $300K · posted 2026-07-29
- Collaborative Research: CSR: VERITAS: Secure Vehicular Systems through Intelligent Information Flow Verificationawardmedium relevance
National Science Foundation · CSR-Computer Systems Research · $400K · posted 2026-07-29
- HCC: Technology-mediated positive emotions for well-being and consumer product sustainabilityawardmedium relevance
National Science Foundation · HCC-Human-Centered Computing · $657K · posted 2026-07-28
- CAREER: Bolt-On Scalable Systems for AI-Powered Query Processing over Structured and Unstructured Dataawardmedium relevance
National Science Foundation · CSR-Computer Systems Research · $667K · posted 2026-07-20
- III: Web-Scale Hand-Object-Centric Video Dataset Sourcing and Aggregation with Video-Based Data Retrieval for Robot Learningawardmedium relevance
National Science Foundation · Info Integration & Informatics · $894K · posted 2026-07-20
Market signal
What the radar sees in Data for AI: new companies by cohort year, the forming YC batch, and outcomes since the February snapshot.
Data for AI · 50 → 35 → 67 → 62 → 57 new companies 2022 → 2026 · 91% aliveYC F26 live: 8 in this cluster, 6% of the batch (was 4% in S26)Since February, of 167 YC companies here: 1 acquired, 2 shut down, 31 rewrote their pitch
Design attributes
The card is one cell of a designed set: every axis below was chosen before the text was written, and the text had to realize it.
- Buyer
- Consumer
- Business model
- Marketplace
- Path to 100x
- Platform others build on
- Market size
- $1-10B market
- Capital intensity
- Capital-medium (ops, field teams)
- Speed to revenue
- R&D first, revenue after 3 years
- Technical depth
- Real engineering
- Go-to-market
- Self-serve
- Moat
- No moat yet
- Geography
- Global from day one
- Regulation
- Unregulated
- Vibe
- Boring business
Listed under
An idea sits in its own sector and in any sector its text clearly touches.
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