Robo Index
50.4/ 100
Recomputed nightly from public data. Missing data is skipped, never zero-filled — and rankings are never for sale.
3 of 7 signals present
How the Robo Index is scoredDeployment footprintnot yet scored35%
Company financial health9120%
Spec completeness3120%
Media mentions (trailing 12 months)not yet scored10%
User reviewsnot yet scored5%
Market availabilitynot yet scored5%
Company maturity253%
Overview
Cortex 2.0 extends our original Cortex architecture by introducing a world model into the learning loop. It uses a world model to predict a set of future scene rollouts in video latent space, helping the robot to evaluate potential futures and choose the most promising actions, thus avoiding costly failures and improving efficiency in robotic manipulation tasks.
Flagship features
- Cortex 1.6 improves success rate by 6–9% over Cortex 1.5 and by 15–25% over previous models
- Recovery success rates improved from ~45% (baseline) to ~80% (Cortex 1.6)
- Dense rewards allow for faster learning, with up to 3× quicker convergence time compared to the baseline
- Designed to continuously improve while performing tasks in real-world settings, utilizing feedback from operational data
Buyer decision signals
Viability
$140.0M raisedest. 2021
Series B funding raised
Availability
available
Specifications
Category: Cobot- Type
- other
- Force limiting
- Yes
- F/T sensing
- none
- API / SDK
- No
VerifiedSelf-reportedEstimated
Company profile
- Funding raised
- $140.0M
- Founded
- 2021
Detailed specifications
Compute1
- Ros Compatible
- false
Other8
- Price Tier
- 150K+
- Applications
- pick_and_place,returns_handling,kitting
- Deployment Notes
- Cortex 2.0 has been deployed in various settings, including return handling, kitting, parcel closing, and item handling. Notable customer implementations include Active Ants, Deltilog, Arvato, and Radial.
- Industries Served
- warehouse,logistics
- Availability Status
- available
- Compatible Grippers
- Robotiq 2F-140
- Programming Interface
- drag_and_drop
- Additional Information
- - Cortex 1.6 improves success rate by 6–9% over Cortex 1.5 and by 15–25% over previous models. - Recovery success rates improved from ~45% (baseline) to ~80% (Cortex 1.6). - Dense rewards allow for faster learning, with up to 3× quicker convergence time compared to the baseline. - Designed to continuously improve while performing tasks in real-world settings, utilizing feedback from operational data.
Company milestones
- Apr 2026FundingSeries B funding raised
- 2026DeploymentCortex 2.0 deployed in live production environments with zero supervision
- 2026DeploymentMS Direct and Sereact automate night-shift picking
- 2026MilestoneSereact launches Cortex 2.0: Grounding World Models in Real-World Industrial Applications
- 2026MilestoneSereact reports 50+ deployments
- 2026LaunchSereact raises $110M to scale Cortex 2 world model for robotic manipulation
- 2025FundingSeries A funding raised
- 2025DeploymentKnuspr and Gurkerl live ops with Sereact
Compare with peers
Reviews for Cortex 2.0
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