Companies · Robotics

SieveWinter 2022Active

San Francisco · CA, USA · Robotics · founded 2022 · https://sievedata.com/

Diligence memoA one-page analyst read on Sieve — recommendation, valuation, rhythm, risks.
Total raised · real
0
Rounds
Latest step-up
Top 66%
Sector rank · raised
Latest stage · inferred

Sieve: limited disclosed financing to assess.

Synthesized from the figures below est. — every claim rests on a number shown on this page.

Where it sits in Robotics

Sieve is one of 327 Robotics companies tracked from San Francisco, CA, USA, on record since 2022. By capital raised it ranks in the long tail (ahead of 35% of sector peers), and in the long tail by modeled valuation est..

Ranking is computed against this company's own sector cohort — reported capital is fact; valuation tiers are modeled.

AI analyst read est. — model-extracted from this company's public description, not a verified fact. 30%

operates a technology-led product inferred from public copy

Grounded in: “You are a venture analyst

Video datasets for frontier AI

Sieve is the only AI research lab exclusively focused on video data. Video already makes up 80% of internet traffic and has become the dominant medium driving creativity, communication, gaming, AR/VR, and robotics. Unlocking the ability to truly model video is the key to breakthroughs across all of these domains but progress has been bottlenecked by one thing: high-quality training data. That’s where Sieve comes in. We bring together exabyte-scale video infrastructure, novel video understanding techniques, and dozens of diverse data sources to create datasets that push the frontier of video modeling. This unique combination allows us to deliver data with unmatched precision, quality, and speed which has earned the trust of frontier AI labs, Fortune 100 companies, and fast-growing generative AI startups.

AIData EngineeringData LabelingDeveloper ToolsVideoai/mlgamingrobotics
Find Sieve online

As reported in public records reported — not modeled.

US
Jurisdiction
Amount raised vs valuation, by round

Solid bars are reported offering amounts reported; hatched bars are the modeled post-money valuation est. — both on one shared scale so you can read raise-vs-worth at each round directly. Use the toggles to overlay data labels and the niche-peer / market average value lines.

No round amounts on record to chart.

Financing ladder & sequence gaps

No staged rounds to sequence.

Modeled valuation trajectory
Base estimate est.
Conservative case
Upside case
Modeled post-money

Round size and date are reported; the stage label is inferred from round size. Valuation is modeled from stage benchmarks. Directional, not a quoted figure.

Not enough modeled valuation points to chart a trajectory.

Financing rhythm
Avg between rounds
Capital velocity
On record since
First round
0
Rounds on file
How it compares to the market

Benchmarked against 327 companies in Robotics. Each bar is a median (the middle company, not an average — outliers don't skew it). Two yardsticks: real money raised (reported on Form D) and modeled value (our estimate est.). These are whole-sector medians across all stages, except the per-stage row.

Total raised — vs sector median (real $, all stages)
This company
Sector median$6.3M
Modeled value — vs sector median (estimate, all stages)
This company
Sector median$34.4M

Raised more than 35% of sector peers (real $). Modeled value above 35% of peers (estimate).

Full financing history

Stage is inferred from round size est., not reported on the filing — a round's dollar size maps to a bucket: Pre-Seed <$1.0M · Seed $1.0M–$4.0M · Series A $4.0M–$15M · Series B $15M–$40M · Series C $40M–$100M · Series D+ $100M–$400M · Growth/Late >$400M.

StageAmount · realAnnouncedPost-money · estValue · estConf.
No rounds recorded.
Intelligence
Modeled next raise
Modeled next size est.
Last step-up
Capital velocity

Predictive signals are modeled est. from this company's own cadence and step-up, plus sector benchmarks — directional, not advice. Peer set and a CSV export live in your analyst workspace.

Registry & provenance

Sieve is an official record sourced from the U.S. Securities and Exchange Commission (SEC). U.S. data is aggregated from SEC Form D filings.

United States
Country of record
US
Jurisdiction
Similar companies

Nearest neighbours across the whole database — matched on sector, stage and capital scale, and on shared operators (officers or directors named at both companies in public filings). A discovery shortlist, not a valuation cohort — verify before acting, the same way modeled figures are directional.

CompanySectorStageRaised · realValue · estWhy similar
3Laws Robotics Inc.RoboticsSeed$2.0M$21.7Msame sector
6thSenseRoboticssame sector
Accel Robotics CorpRoboticsSeries A$11.4M$138.1Msame sector
Advanced Image Robotics, Inc.RoboticsSeed$2.5M$19.9Msame sector
Advanced Metal ResearchRoboticssame sector
Aerones Inc.RoboticsSeries B$38.9M$417.0Msame sector
Agility Robotics, Inc.RoboticsSeries D+$157.5M$2.5Bsame sector
AiM Medical Robotics Inc.RoboticsSeries A$11.7M$22.7Msame sector
Semantically similar

Matched by meaning, not labels — a local language model reads each company's name, sector and description and ranks the closest in that learned space. This catches look-alikes that cross sector boundaries; the structured list above explains its matches, this one trusts the text. Directional, like every modeled signal here.

CompanySectorStageValue · estMatch
Eventual
Building the AI data engine for any modality and scale
AI / ML78%
Vision Lab
Industrial data layer for robotics training
Robotics76%
Cortex AI
Large-scale real-world robot & human data for embodied AI
Robotics76%
Halluminate
Data and RL environments to automate knowledge work
AI / ML75%
The LLM Data Company
Frontier models for critical domains
AI / ML75%
Playment
Mechanical Turk for enterprises.
Space / Aerospace75%
DataSuite
Dataset Management for AI Trainers
AI / ML75%
Velvet
The multimodal data lab.
74%
Frequently asked
What does Sieve do and where is it based?
Sieve operates in the Robotics sector, based in San Francisco, CA, USA. Video datasets for frontier AI
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