Powering decisions that win
The brands your competitors are watching
Eight data types, collected to your requirements
Multimodal
Two or more signals captured together and delivered as a linked set.
Multimodal data built to your spec
The paired data your model needs, captured in sync.
Why do multimodal models fail?
When the pieces are paired loosely or pulled from different places, the model misreads how they fit together.
Looks fine on tidy pairs. Breaks when the pieces fall out of sync.
Holds up where the pieces arrive together.
What does stitched multimodal data miss?
Rwazi captures it together, so your model trains on data that was linked from the start.
What does a multimodal sample look like?
Your pack arrives as linked pairs for your task. Every record carries demographic metadata and a shared identifier, dropped straight into your cloud.
Audio with video, captured together as one clip.
Request accessImage with text, joined by a shared identifier.
Request accessLocation with metadata, aligned in the same record.
Request accessCustom combinations, assembled per job.
Request accessWhat we capture to your spec
Two ways to pair your data
We cover both ends: ready-made pairs or custom-assembled. You pick how the pieces come together.
Ready-paired capture
For combinations we collect together. Audio and video as one clip, captured and linked at the source.
Assembled per job
For custom combinations. Specific sets paired and synced to a tight brief.
Real-world multimodal data from 190+ countries
Most multimodal sets come from a handful of mature markets, so models stumble elsewhere. Rwazi pairs the data across 190+ countries and 100+ languages, captured by local contributors where it actually happens.
- 190+ countries
- 100+ languages
- audio, video, image, text, and location
- paired at capture
- real-world or controlled
What sets Rwazi multimodal data apart?
Built for the multimodal AI you are shipping
Vision-language models and VQA
Vision-language models need real image-text pairs at scale.
Image and text joined by a shared identifier, collected to your spec.
Multimodal datasets for the task you are training
We build multimodal training data for machine learning, scoped to your task.
From your spec to your cloud, in four steps
Run it as a one-off project or a recurring refresh, weekly or monthly.
How Rwazi compares to other providers
The same data, captured in the real world. Here is how that stacks up against the alternatives.
Every paired record earns its place in your dataset
You write the pass-or-reject criteria. People review each paired record against those criteria and log who captured it, where, and when. We report what passed before the set reaches you.
Tell us your scope or book a live demo with us
Contact The Rwazi AI Datasets Team
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Questions teams ask before they buy
What is multimodal data?+
Data that pairs two or more signals, such as audio with video or image with text, is used to train multimodal and vision-language models. Rwazi builds it to your brief across 190+ countries.
What combinations can you collect?+
Audio with video, image with text, and location with metadata, plus custom combinations assembled per job.
How are the modalities linked?+
Audio and video are captured together as a single clip; images and text are linked by a shared identifier; and location and metadata are stored in the same record.
Are sets ready or assembled per job?+
Some combinations are ready, such as audio with video. Specific combinations are assembled per job to your spec.
What languages and coverage do you have?+
100+ languages across 190+ countries, captured from real contributors.
Does it include labeling or captioning?+
The paired data is the deliverable. Labeling, captioning, and alignment can be added as a paid layer.
What formats and delivery do you support?+
MP4, JSON, and paired files, delivered to your S3, Azure Blob, GCS, or SFTP.
How is it priced?+
We quote per project. The drivers are combinations, volume, languages, exclusivity or licensing, and add-ons. Send your brief, and we will price it.
How do you handle consent and ownership?+
Contributors capture every pair under explicit consent through Rwazi. The set is Rwazi-owned, yours to license or take outright, with provenance on each record.
How does this compare to stitched multimodal data?+
Stitched data pairs modalities after the fact and drifts out of sync. Rwazi captures them together, aligned at the source.
What does a delivery look like?+
Linked pairs in the formats you choose, quality checked and consistently named, each tagged with age, gender, and location, delivered to your cloud.
Where can I buy multimodal or image-text datasets?+
Rwazi scopes a bespoke multimodal dataset, paired to spec and licensed or owned outright.