Intelligent assistants and chatbots
Build systems that can “see and talk”, answering questions about images, diagrams, and real-world scenes using natural language.
Build visual AIVision-Language models
Multimodal models that understand images and language together for reasoning, description, and information extraction.
Qwen2.5-VL – vision-language foundation model
Qwen2.5-VL reads images and text together to understand visual content, reason about scenes, and work with text-rich or real-world imagery. It's a solid base for vision-language applications.
// Why Qwen2.5-VL at Keylabs- Multimodal reasoning: Simultaneously interprets images and natural language to answer questions, describe scenes, and extract contextual meaning beyond simple detection.
- Visual understanding at scale: Analyzes complex images, including documents, UI screens, charts, and real-world scenes with strong semantic comprehension.
- Instruction following: Supports natural-language prompts for tasks such as visual Q&A, content explanation, and structured information extraction.
InternVL2 – vision-language foundation model
InternVL2 pairs image and text understanding for scene reasoning and analysis of text-rich or real-world imagery. As an open model, it suits self-hosted vision-language work.
// Why InternVL2 at Keylabs- Multimodal reasoning: Interprets images alongside natural language to understand scenes, answer questions, and perform deep visual reasoning beyond basic recognition.
- Document and UI understanding: Excels at analyzing structured and unstructured visual content such as documents, dashboards, interfaces, and charts with strong contextual awareness.
- High-performance open VLM: Strong vision-language capabilities in an open-source stack, suited to enterprise deployment and self-hosted AI systems.
Choose your path
Pick the multimodal path that fits your project.
Screens, invoices, dashboards, and forms
Extract meaning from structured and unstructured visual content with contextual reasoning beyond OCR.
Understand visualsAI assistants with perception capabilities
Enable agents that combine language reasoning with image interpretation for real-world decision-making.
Deploy agentsDataset creation for multimodal AI
Pre-annotate and enrich image datasets using vision-language understanding to accelerate annotation workflows in Keylabs.
Accelerate labelingReady to build multimodal AI systems?
Talk to our multimodal team to get started.
Custom solution? hello@keylabs.ai
