Service
Multimodal AI
Annotation and evaluation across image, video, audio and text — including OCR, VQA and cross-modal reasoning.
Problems we solve
When teams bring us in
- Vision or multimodal models need reliable labeled data.
- Cross-modal reasoning quality is untested.
- OCR or VQA output accuracy is unknown on real inputs.
What you receive
Deliverables
- Annotated image / video datasets
- Multimodal evaluation sets and rubrics
- Accuracy and failure-mode reports
- Edge-case collections
What we do
Capabilities
- Image Annotation
- Video Annotation
- Image Evaluation
- Video Evaluation
- Text + Image Evaluation
- Audio + Text Evaluation
- Multimodal Model Testing
- OCR Evaluation
- Computer Vision Evaluation
- Visual Question Answering Evaluation
- Cross-Modal Evaluation
Quality
How we keep results reliable
- Annotation guidelines with examples
- Calibration tasks
- Sampled review
- Agreement metrics
Related programs
Fixed-scope ways to start
- AI Model Health Check
A rapid evaluation of an AI system across accuracy, consistency, safety and failure modes.
- AI Data Accelerator
Rapid collection, annotation, validation and dataset creation.
Scope your multimodal ai project
Send us what you are building. We will scope the data, evaluation, benchmarking or testing program and come back with a proposal.