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Investor Presentation · September 2026
Robotic DataAI Has Left the Screen.
The Shift
Lane 01AI transformed what machines can think. Physical AI transforms what machines can do.
The last decade
Intelligence on a screen
Models trained on text, images and video scraped from the internet. The data already existed.
The next decade
Intelligence in the world
Robots, vehicles and drones must act in physical space. That data does not exist yet — it has to be captured.
The Bottleneck
Lane 02The next generation of robots won't be limited by hardware. They'll be limited by data.
- Actuators, compute and models are commoditizing fast.
- Real-world data is the scarce input: environments, sensors, people, interactions.
- Every embodied program eventually hits the same wall — not enough representative, structured, AI-ready data.
What real-world data requires
The right environmentsThe right peopleThe right sensorsThe right interactionsFailures and recoveriesScale and repeatability
The Company
Lane 03Robotic Data exists for one purpose: creating the world's best real-world data for robots.
Heritage
A decade in the field
Built as Voxelmaps, a leading provider of geospatial data for autonomous systems.
Expansion
Beyond mapping
Human behavior, interaction and task-learning data for humanoids and embodied AI.
Standard
Engineered, not scraped
Geospatial engineers, roboticists and AI specialists design and validate every dataset.
The Product Surface
Lane 04Six capabilities customers buy.
01
Navigate
Spatial datasets for localization, HD maps and safe movement.
02
Perceive
Multi-perspective capture of roads, sites and complex environments.
03
Manipulate
Structured task episodes — including failures and corrections.
04
Interact
Human movement, speech, intent and human-robot collaboration.
05
Simulate
Digital twins, Gaussian splats and synthetic-data source material.
06
Scale
Repeatable programs across cities, countries and populations.
Two Data Pillars
Lane 05Two pillars. One physical world.
World Data
Teach machines where they are
- Street-level LiDAR, imagery and precision positioning
- Aerial capture: LiDAR, orthophotography, terrain and surface models
- Indoor and pedestrian mapping of the places vehicles can't reach
Human Data
Teach machines what people do
- Multimodal task episodes: egocentric video, mocap, hand and object tracking
- Interaction data: movement, gesture, speech, intent, collaboration
- Built for VLA models, imitation learning and humanoid manipulation
Track Record
Lane 06When leading AI companies need exceptional data at exceptional scale, they call us.
26Countries with geospatial operations delivered
12Countries of human data collection
8+Years supporting leading AI and robotics companies
Hundreds of thousands of hours of human interaction data captured · Austin · San Francisco · Mexico City · London · Porto · Taipei
The Infrastructure
Lane 07Services are the entry point. Infrastructure is the destination.
World Data · USA
SYMBO Network
Building the physical index of the United States as a repeatable, expanding capture network.
Platform
Digital Twin Platform
Making reality searchable — one intelligent 4D twin to explore, analyze and query the physical world.
Human
Human Data Programs
Global participant recruitment and structured capture protocols operated as an ongoing program.
The Precedent
Lane 08Five Physical AI sectors. Zero coordination. The same arc.
01Autonomous VehiclesHardware → Sensor data → AI models → Recurring software revenue
02Digital Twins & SpatialData collection → Digital twins → Analytics → Subscription platforms
03Industrial AIEquipment & services → Data → AI applications → Enterprise subscriptions
04Robotics & Physical AIRobotics → AI models → AI agents → Autonomous platforms
05AI Data InfrastructureLabeling services → AI evaluation → Enterprise infrastructure → Strategic supplier
Physical AI Precedents
Lane 09Across Physical AI, the same evolution is already underway.
Autonomous VehiclesTesla · Waymo · Aurora · Wayve · Mobileye
Digital Twins & Spatial IntelligenceMatterport · Bentley · Hexagon · Nearmap
Industrial AI & Asset IntelligencePalantir · C3 AI · Samsara · Siemens · GE Vernova
Robotics & Physical AIFigure · Physical Intelligence · Skild AI · Apptronik · Applied Intuition
22 precedent transactions · 20+ companies · one commercialization pattern
The Closest Precedent
Lane 10Not a sector match — a business-model match.
CompanyStarting pointDestination
Scale AIData labeling services→ AI infrastructure
Surge AIHuman annotation→ Enterprise AI data platform
LabelboxData-labeling tools→ Enterprise AI data operations
Robotic DataReal-world data capture→ Physical AI data infrastructure
Strategic Implication
Lane 11The precedent is established.
01Services create access.
02Access creates proprietary data.
03Data creates products.
04Products create recurring revenue.
05AI infrastructure creates strategic value.
Robotic Data is applying this proven commercialization model to the data layer of Physical AI.
Why Now
Lane 12The grid is set. The lanes are being claimed this cycle.
Demand side
- Humanoid and embodied programs are moving from research to deployment.
- VLA and foundation-model training is data-bound, not model-bound.
- Buyers need one partner across world, human and simulation data.
Supply side
- Capture capacity is physical: fleets, sensors, participants, permissions.
- Multi-country operations take years to build — we already run them.
- Early datasets compound into a defensible index of the real world.
The Ask
Lane 13Capitalizing the shift from services to infrastructure.
Round
[RAISE — replace]
[ROUND TYPE, VALUATION, LEAD — replace]
Capture capacity
Expand SYMBO Network coverage and sensor fleets.
Human data scale
Additional collection geographies and participant supply.
Platform
Digital twin and data-operations platform engineering.
Go-to-market
Enterprise coverage of foundation-model and robotics buyers.
Bracketed items are placeholders pending final round terms.
Close
FinishEvery robot learns from data
before it learns from experience.
Robotic Data is building the real-world data infrastructure for Physical AI. Let's build the future together.
roboticdata.comAustin · San Francisco · London · Taipei