Household robotics training data sourcing
What would kill this
Robotics engineers confirm they need depth-calibrated rigs and cannot use phone footage.
- Paid for today
- Yes
- Proof
- Dated Jul 2026
0
ideas pressure-tested
Clarno finds who has the problem you want to solve, what they pay to fix it today, and what to build for them first.
Robotics engineers confirm they need depth-calibrated rigs and cannot use phone footage.
Grasping models rely entirely on teleoperation data, not video of human hands.
Generative simulation removes the need to collect real-world video.
Watch public AI research forums and dataset requests. Do manipulation teams download raw 2D video, or demand depth-calibrated sensor data?
A newly trained model passes every simulation benchmark and completely fails its first physical test in a real living room.
A pipeline for unscripted daily routines, not a lab-controlled capture studio.
Their last dataset purchase criteria. Walk away if they only buy lab-captured motion data.
Hard reach drops this below viability, despite a simpler buyer profile.
Heavy build requirements and massive privacy hurdles make this too complex for a solo founder.
A small custom batch of usable robotics training data.
1 sellerFirst-person household video with exclusive dataset rights.
1 sellerA large task-specific robotics data program with richer capture and annotations. Sold by quote.
2 sellersSeller prices. No public buyer payment was found.
Test a narrow household-data pilot with buyers. Procurement may demand stronger rights and QA than a solo app can provide.
Simulated buyers, built from this group. Each one has its own reason to say no.
Raw smartphone video lacks calibrated depth, wrist poses, and tactile proprioception.
The footage includes accurate 3D hand pose tracking and camera data.
The volume from an early-stage app is too small next to open datasets such as Ego4D.
The platform delivers tens of thousands of diverse home chore hours at lower unit cost.
Contributor reward apps risk wage-and-hour issues or unclear copyright ownership.
Airtight work-for-hire contracts assign clear, perpetual commercial rights to buyers.
How exact the footage must be, or how varied. Aris wants exact. Elena wants varied. Gareth wants it legal.
Your focus on supplying data splits into three different approaches to the same market.
If robotics teams will not buy crowdsourced phone video, the business fails immediately.
Robotics engineers confirm they need depth-calibrated rigs and cannot use phone footage.
Paid for today: Yes · Proof: Dated Jul 2026
Grasping models rely entirely on teleoperation data, not video of human hands.
Paid for today: Yes · Proof: Dated Jul 2026
Generative simulation removes the need to collect real-world video.
Paid for today: No sign · Proof: None found
Watch public AI research forums and dataset requests. Do manipulation teams download raw 2D video, or demand depth-calibrated sensor data?
Ask any chat model about your idea and it will find a way to love it — optimism is baked into the training. Clarno is built the other way around: skepticism is enforced by architecture, not requested by prompt.
| A chat model | Clarno | |
|---|---|---|
| Default answer | "Great idea — here's how to start." | A graded verdict, evidence attached |
| Arithmetic | Inside the model, where it drifts | Never inside the model — LAW ZERO |
| Market view | Whatever you told it | 50 simulated buyers who owe you nothing |
| Skepticism | Available on request, fades by turn three | Structural — no self-graded honesty |
| Incentive | Keep the conversation going | End it with a decision |
Clarno walks your idea from first doubt to first traction. At every fork you choose the direction, from cards Clarno has already pressure-tested. What you cannot choose is the evidence. The judgments about the market are Clarno's, and they do not negotiate.
The market will run these six beats on your idea either way. Clarno just runs them first.
The cohort is Clarno's core instrument: up to 50 market agents that behave like a market instead of an audience. They push back for their own reasons, not yours. Each dot behind this text is on its own clock.
Each agent carries a persona and episodic memory: what you claimed, what they doubted, what changed. Inconsistencies get noticed, and held against you.
The cohort advances on a tick clock. Each agent acts, remembers, and updates between rounds, so later answers come from a lived history, not a blank profile.
At 50 agents the cohort deliberates as a group, under a moderator that scores positions instead of smoothing them. Consensus has to be earned, never assumed.
Every scan ends in a verdict you can act on: cited, unsentimental, and clear about what it could not find. Disconfirming evidence comes first, because that is the part you are paying to hear.
The common outcome: narrower, smaller, alive.
Kill the wrong idea in an afternoon instead of discovering it a year of evenings from now.
Pressure-test the wedge, the pricing, and the story while they are still cheap to change.
Run the whole pipeline through one standard of evidence. Build the survivors.
Screen decks against up to 50 market agents before the partner meeting screens them against opinion.
Clarno showed me the weakness in my idea in July. My cofounder still launched it without me and is now struggling. Cheapest no I ever bought.SECOND-TIME FOUNDER · B2B SAAS · PILOT COHORT
Scan. Argue. Verdict. A judgment with its evidence, while your idea is still cheap to change.