Problem

Datoric addresses a central bottleneck in frontier multimodal AI: labs need authentic human-generated data, but open-web and conventional third-party sources often provide unclear rights, missing consent, weak provenance, and exposure to legal, reputational, fraud, and security risk. Quality and provenance also become harder to control as collection scales, while compromised training data can contribute to unsafe model behavior and expensive rework.

The killer use case is difficult, project-specific data that off-the-shelf corpora do not provide, especially for voice models, robots, world models, physical-AI systems, and computer-use agents. Examples include multilingual speech, egocentric video, action-conditioned interactions, and browser or GUI trajectories collected under tightly defined requirements.

Product / Service

Datoric is a licensed multimodal data company that combines a dataset catalog with build-to-spec collection programs. It sources contributors directly, establishes consent and licensing at the point of contribution, offers fair compensation, and links samples to verifiable provenance. Its private apps and isolated project environments are designed to keep customer programs separate and limit unauthorized or manipulated submissions.

The delivery model runs from specification through recruitment, collection, labeling, modality-specific quality review, piloting, and delivery with rights attached. Customers define the modalities, tasks, labels, environments, and acceptance criteria; contributors then record the required voice, video, computer-use, robotics, or physical-AI data with structured metadata. The result is data that is more tailored to the model objective and easier for legal, security, and model-quality teams to evaluate and defend.

Market

Datoric competes in the AI training-data, data-collection, annotation, and multimodal data-infrastructure market, with a specialization in licensed, provenance-first data for frontier models. Its broader competitors include established providers such as Appen, which offers collection and annotation across text, image, audio, video, and geospatial data, and Scale AI, whose Data Engine supplies labeled data and domain-expert workflows. Datoric's differentiation is its emphasis on origin-level consent, engagement-specific licensing, project isolation, and custom multimodal data that may not exist yet.

Datoric is not pre-revenue. In its July 29, 2026 Y Combinator launch, the company reported nearly seven figures of revenue in the preceding 30 days, a major quality improvement versus other providers, and a network of more than 300,000 active contributors. These figures are company-reported rather than independently audited, and the public evidence does not identify customer names or contract economics. The broader data-collection and labeling market was estimated at $3.8 billion in 2024 and projected to reach $17.1 billion by 2030, providing a large market backdrop for Datoric's specialized offering.