Multimodal Processing
Combining insights across text, images, audio, and more.
Multimodal Processing enables AI systems to understand, reason, and act based on information from multiple data types simultaneously, just like humans do.
At Dot Square Lab, we design AI solutions that intelligently integrate text, images, audio, video, and structured data, creating richer, more context-aware applications that outperform single-source models.
By unlocking synergies between diverse data streams, we help organizations build smarter, more capable AI systems.
What we build with
Create shared representations across modalities for seamless understanding and reasoning.
Combine image and text processing for tasks like visual question answering, captioning, and retrieval.
Enable intelligent search and matching across different data types (e.g., text-to-image, image-to-text).
Integrate and align data from multiple sources at feature, intermediate, or decision levels.
Process spoken language and environmental sounds alongside text and visual data for richer context.
Develop models capable of generating complex outputs across multiple formats (e.g., text and image generation).
Applications
Build assistants that can see, listen, read, and respond with greater context-awareness and precision.
Combine imaging data, patient records, and clinical notes for more accurate and holistic diagnoses.
Enable customers to search products using text descriptions, photos, or even voice commands.
Integrate video feeds, audio detection, and textual data to enhance security and situational awareness.
Leverage user interactions across video, audio, text, and imagery to deliver more personalized recommendations.
Equip autonomous vehicles, drones, and robots with the ability to interpret multimodal sensory inputs for safer navigation and decision-making.
