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Wave 1 segment

Real-world capture for teams training models that need grounded spatial understanding.

Roam helps world-model, multimodal video, and physical-AI teams procure real-world environments with clear formats, manifests, QA expectations, and review materials before a live program starts.

Likely buyer teams

World-model labsMultimodal video model teamsPhysical AI platform teams

What teams usually need to confirm

  • Manifest structure, checksums, and delivery packet examples
  • Open-format outputs tied to downstream training and evaluation workflows
  • Clear line between public demo proof and NDA-only production review

First pains to address

Data diversity is the bottleneck, not model ambition.

Synthetic pipelines still need ground-truth calibration and evaluation data.

Procurement needs proof that the output contract is real before mobilization.

Example program shapes

Warehouse and industrial interiors for model post-training

Campus and retail environments for world-model evaluation

Indoor and outdoor geometry-rich corpora for multimodal grounding

Deliverable fit

Output families that fit this workflow.

Open full deliverables matrix

Raw sensor data

Camera, LiDAR, calibration, pose, and trajectory data for teams that need first-order inputs rather than post-processed visuals alone.

Authoritative for
Training corpora, reprojection, calibration review, and downstream reconstruction pipelines.
Preview use
Subset validation, pose sanity checks, and pipeline bring-up.
Image/video framesPCAP / raw LiDAR exportsTrajectory / pose filesCalibration bundles

Point clouds

Structured geometry for measurement, mapping, simulation prep, and change review.

Authoritative for
Measurement-adjacent review, geometry QA, GIS intake, and reconstruction baselines.
Preview use
Subset exploration, coverage checks, and visual inspection.
LAZ / LASCOPCE57PLY

Gaussian splats

Neural-representation deliverables for fast scene review and model-facing visualization workflows.

Authoritative for
High-fidelity visual scene review and neural rendering research workflows.
Preview use
Web previews and human review.
PLYSPZglTF + extension

OpenUSD scenes

Scene-graph packaging for simulation, twin ingestion, and composition-aware workflows.

Authoritative for
Simulation and scene composition where OpenUSD is the agreed delivery container.
Preview use
Scene inspection, layer review, and asset organization checks.
USDA / USDC / USDZLayer manifests

Materials you can review now

public exampleOpen asset

Sample manifest

Example manifest structure showing delivery versioning, formats, checksums, and CRS metadata.

Why review it: Roam can describe delivery structure in a machine-readable way before a live program starts.

Boundary: This is an illustrative public example, not a customer-specific delivery commitment.

public exampleOpen asset

Checksum example

Example checksum file showing artifact validation format.

Why review it: Roam can expose integrity checks as part of the delivery packet.

Boundary: Checksums shown here are example values for public proof only.

demo-onlyOpen asset

Sample dataset catalog

Live demo datasets, manifests, and gated artifact downloads.

Why review it: The public demo routes are real and runnable today.

Boundary: Demo subsets are not equivalent to a production program or customer packet.

demo-onlyOpen asset

Sandbox and readiness APIs

Short-lived demo keys, sample dataset listing, and readiness scoring.

Why review it: Technical evaluators can verify endpoint behavior and sample shapes now.

Boundary: Not a production API commitment.

Likely objections

We do not need another scanning vendor.

Roam is positioned around delivery packets, manifests, QA expectations, and handoff structure, not a generic capture gallery.

We need training fuel, not a one-off demo.

Roam is built for repeatable dataset programs and environment refreshes, not one-off demo scans. Production scale is scoped directly with the team.

Ways to engage

Technical evaluation

Start with docs, sample data, format references, and the sandbox before opening a live program.

Audience: ML engineers, simulation leads, GIS analysts, platform teams

Available now: Public and available now through developer docs, sandbox APIs, and sample-data examples.

Validate technical fit

Live program scoping

Scope environments, outputs, review constraints, and timeline through an intent-first intake path.

Audience: Founders, VPs, robotics PMs, autonomy leads, operations buyers

Available now: Public intake is available now; commercial and operational specifics are finalized in the engagement.

Start program scoping

Security, privacy, and legal diligence

Bring data handling, deletion, privacy-sensitive capture, and diligence questions in early.

Audience: Security reviewers, privacy counsel, legal, procurement

Available now: Public diligence materials are available now; customer-specific review expands under NDA when needed.

Start diligence review

From evaluation to scoping

Review sample delivery proof

Inspect sample artifacts, manifests, and gated downloads before starting a live conversation.

Raise NDA, security, privacy, and delivery constraints in the first conversation instead of after procurement restarts the process.

Need immediate scheduling? Use the programs inbox.