{"id":"92d65a9c-5021-4bd7-a49a-527d50da9bb2","name":"Midcentury","slug":"midcentury","description":"Physical AI data and simulation company. Exited stealth in September 2026 with a $15M seed round. Claims a large labeled egocentric dataset and Matrix agentic simulation for policy evaluation and RL. Team background cited from Stanford, OpenAI, DeepMind, and NVIDIA. Dataset scale claims are company-claimed.","status":"private","founded":null,"hq":null,"hqLat":null,"hqLng":null,"hqGeocodedAt":null,"hqAddress":null,"hqPrecision":null,"website":"https://www.midcentury.xyz/","fundingTotal":"15000000","type":"brain","roles":[],"reviewStatus":"reviewed","heatIndex":0,"lifecycleState":"active","supersededByCompanyId":null,"sources":[{"url":"https://x.com/MidcenturyAI/status/2102412610071339414","title":"Midcentury exits stealth with $15M seed","sourceName":"Midcentury"},{"url":"https://www.midcentury.xyz/","title":"Midcentury: Data and Simulation Infra for Physical AI","sourceName":"Midcentury"},{"url":"https://www.midcentury.xyz/datasets/","title":"Midcentury datasets","sourceName":"Midcentury"},{"url":"https://www.midcentury.xyz/blog/mc-egohands","title":"Introducing MC-EgoHands · Midcentury","sourceName":"Midcentury","publishedAt":"2026-10-02"},{"url":"https://x.com/robotsdigest/status/2106098905402454406","title":"Robots Digest: Midcentury MC-EgoHands","sourceName":"X (@robotsdigest)","publishedAt":"2026-10-02"},{"url":"https://www.midcentury.xyz/blog/akari","title":"Akari: Learned Rendering for Robotics Simulation","sourceName":"Midcentury","publishedAt":"2026-10-21"},{"url":"https://x.com/MidcenturyAI/status/2112922749320548735","title":"Midcentury introduces Akari","sourceName":"Midcentury on X","publishedAt":"2026-10-21"},{"url":"https://runtimewire.com/article/midcentury-akari-learned-renderer-robotics-simulation","title":"Midcentury launches Akari, a learned renderer for robotics simulation","sourceName":"Runtime Wire","publishedAt":"2026-10-21"}],"keyFacts":[{"label":"Seed round (company-claimed)","value":"Sep 2026: $15M."},{"label":"Focus","value":"Physical AI data and simulation infrastructure."},{"label":"Egocentric data (company-claimed)","value":"2M+ hours of unscripted first-person video across 50+ environments, with hand pose, depth and task annotations."},{"label":"Upcoming products (company-claimed)","value":"MC-Motion (3D motion reconstruction), MC-Shade (photoreal rendering) and MC-PhysBench (physics benchmark), releasing soon."},{"label":"MC-EgoHands (company-claimed)","value":"Oct 2026: Turns first-person video into robot-learning episodes, exported as LeRobot v3 for Panda/LIBERO and Yam arms."},{"label":"MC-EgoHands accuracy (company-claimed)","value":"Oct 2026: Hand-pose error of 3.7-5.2 mm PA-MPJPE across four benchmarks, on the company's own evaluations."},{"label":"Akari renderer (company-stated, Oct 2026)","value":"Learned renderer that turns physics engine scene data into photoreal camera frames for robot sim, about 0.46 s per frame on one RTX 5090. Offered only through Matrix."},{"label":"Akari test basis (company-run, Oct 2026)","value":"Fidelity was measured against Unreal Engine renders, not real camera footage. Effect on real robot policies not yet tested."}],"aliases":[],"collisionRisk":"low","reviewNote":null,"atsProvider":null,"atsSlug":null,"factoryLocations":null,"manufacturingCapacity":null,"orgType":null,"burnSignal":null,"litigationEvents":null,"insurancePostureDisclosed":null,"unitEconomicsDisclosed":null,"tickerSymbol":null,"stockExchange":null,"secCik":null,"revenueUsd":null,"revenueBasis":null,"revenueAsOf":null,"employeeCount":null,"employeeCountBasis":null,"employeeCountAsOf":null,"marketCapUsd":null,"marketCapAsOf":null,"marketCapSource":null,"createdAt":"2026-09-22T20:38:05.072Z","updatedAt":"2026-10-21T21:00:48.065Z","jsonLd":{"@context":"https://schema.org","@type":"Organization","@id":"https://registry.deploy.report/companies/midcentury","url":"https://registry.deploy.report/companies/midcentury","name":"Midcentury","description":"Physical AI data and simulation company. Exited stealth in September 2026 with a $15M seed round. Claims a large labeled egocentric dataset and Matrix agentic simulation for policy evaluation and RL. Team background cited from Stanford, OpenAI, DeepMind, and NVIDIA. Dataset scale claims are company-claimed.","identifier":"92d65a9c-5021-4bd7-a49a-527d50da9bb2","publisher":{"@id":"https://deploy.report/#organization"}},"framework_metadata":{"framework_schema_version":"0.1.0","verification_status":"verified","maturity_stage":null,"lifecycle_state":null,"architectural_position":{"cohort":null,"sub_cohorts":[]},"within_cohort_verified_vs_claimed_pair":null,"cap_flags":[],"verification_depth":{"sources_count":8,"primary_source_types":[]}}}