The frontier has moved. AI must now operate in the world, not describe it. Clairva turns behavioural video into structured training signal for world models, embodied agents, robotics and multimodal reasoning.
Not raw footage. Not scraped data. Live in production today.
Supported by global AI and startup ecosystems as we build real-world data infrastructure for the next generation of AI.
Every model shipping today is already a snapshot of the past. The frontier is moving toward systems that understand the physical world: how people move, handle objects, speak and interact in real environments. That can only be learned from grounded, frame-level behavioural video, not text scraped off the web. Optimising for today's benchmarks is a dead end. The advantage belongs to whoever supplies the signal the next generation of models will need.
Solving for today's benchmarks is a dead business. Models are evolving toward spatial, physical and behavioural understanding. That is the signal we structure for.
Objects, hands, depth, scene, speech and behaviour, annotated at frame-level fidelity. The structured signal models learn from, not raw footage.
Native coverage of the languages, environments and everyday behaviour of Southeast Asia and the wider Global South, where the next billion users live and where today's data barely reaches.
Clairva builds the data layer for the model that comes next.
Raw video is media. Clairva turns it into training signal: every clip processed and annotated across visual, human, audio and behavioural layers at frame-level fidelity. The output is not a clip library. It is model-ready behavioural intelligence the next generation of models can actually learn from.
Rights-aware video and first-person capture, licensed at the source and turned into structured training signal for world models and embodied AI.
Objects, hands, depth, scene, speech, motion, intent and cultural context, annotated frame by frame.
Structured outputs delivered through secure pipelines and APIs for training, fine-tuning and evaluation.
Designed for AI labs, data infrastructure companies, robotics teams and enterprise model builders.
From real-world video to model-ready behavioural signal.
We source rights-aware video from professional libraries, first-person capture and consented cohorts across the Global South. The footage is raw material. What we sell is the signal we pull out of it.
Every clip runs through Clairva's annotation pipeline and comes out as structured, model-ready signal at frame-level fidelity. Not raw footage. Not tags on a clip.
For world models, lived context is not metadata. It is the training surface.
Clairva is designed for enterprise AI workflows where provenance, control and delivery matter. Raw video can remain governed. Rights can be tracked. Usage can be bounded. Derived intelligence can be delivered securely.
Each datapoint is captured under user consent, behaviourally annotated by an in-house team, and delivered as structured signal, not raw video.
Most future AI users will live in markets that remain underrepresented in today's training data. Dense streets. Informal markets. Multilingual homes. Crowded retail. Domestic routines. Regional gestures. First-person movement. If models fail here, they do not scale globally. They only scale cosmetically.
India, Sri Lanka, Bangladesh, Pakistan
Indonesia, Philippines, Vietnam, Thailand, Singapore
MENA region, Sub-Saharan Africa
Brazil, Mexico, Colombia, Argentina
Built where the next billion AI interactions will happen.
Clairva is the contextual intelligence layer for video AI. We convert real-world video into structured behavioural signal for world models, embodied AI and multimodal systems.
No. Capture is only one input. Clairva's core product is the intelligence layer: annotation, structuring, provenance, behavioural enrichment and model-ready delivery.
Behavioural signal is the structured information inside video that models can learn from: movement, gesture, speech, intent, task sequence, interaction, environment and cultural context.
Clairva works across cinematic video, egocentric first-person capture and cohort-generated real-world data. These are transformed into structured datasets for training, fine-tuning and evaluation.
AI labs, data infrastructure companies, robotics teams, multimodal model builders, enterprise AI teams and organisations building world models or embodied AI systems.
Because most of the world lives there, and much of AI's training base does not adequately represent its environments, languages, behaviours and cultural contexts.
Clairva is built around rights-aware supply, consent frameworks, provenance trails, usage boundaries and secure delivery. We are designed for AI buyers who need data that can survive legal, technical and commercial diligence.
Through structured formats, secure pipelines and APIs for training, fine-tuning and evaluation workflows.
Clairva will scope the intelligence layer.
Or write to hello@clairva.ai