EMBED
Activate your enterprise data with secure AI retrieval
Embed turns text and images into embeddings to enable semantic retrieval in search systems, RAG architectures, and agentic applications — powering answers, insights, and action across the enterprise.
Trusted by industry leaders and developers worldwide
Transform fragmented data into actionable knowledge
From fetching relevant content for Q&A to surfacing task-critical context for agents, Embed enables fast, accurate retrieval across your data.
- AI Agents
- RAG Accuracy
- Upgraded Search
Fuel enterprise AI agents
Power AI agents that understand your business — retrieving the right data to support reasoning, tool use, and generation across enterprise domains.
The foundation for semantic retrieval in real-world AI systems
Built to handle complexity and scale, Embed delivers precise retrieval across noisy, multilingual, and multimodal data.
Built for business documents
Generate a single embedding for mixed-modality docs containing text, graphs, and tables — simplifying your pipeline and improving accuracy by eliminating data pre-processing.
Multilingual by design
Embed retrieves relevant content in 100+ languages even when queries and source languages don’t match — returning accurate results without any need to identify language or translate.
Advanced image understanding
Map visual assets and written content into the same embedding space — making charts, dashboards, and design files just as searchable as any block of text.
Industry-specific performance
Embed handles high-context business content with precision — from financial filings to healthcare records — surfacing what’s most relevant, not just what matches the query keywords.
Secure, fast, reliable — Everything you need for production-ready retrieval
- Privately deployable: Run Embed in your virtual private cloud (VPC) or on-premises environment to keep sensitive data secure — or deploy via major cloud services.
- Efficient at scale: Compress embeddings by up to 96% without sacrificing quality — reducing vector database storage costs and improving performance at the scale of billions of embeddings.
- Robust in production: Deliver accurate results across noisy, multilingual, and multimodal enterprise data — even on fragmented or domain-specific data.
Workplace solutions built on Embed
North
Powered by Command A, Compass, Embed, and Rerank, North helps you transform the way you work with secure AI agents, advanced search, and leading generative AI - all in one place.
Learn more
Compass
Unlock the potential of your data with an intelligent search and discovery system that doesn't compromise on security.
Learn more
Global organizations choose Embed for search and retrieval
"Hunt Club's Atlas product lets customers navigate their sprawling professional networks and find talent within them. AI is essential in searching across complex candidate profiles and making sense of messy data to find ideal matches. Cohere's Embed 4 enables us to search these profiles more precisely, showing a +47% relative improvement over the already-strong performance of Embed 3. We are extremely impressed!"
— James Kirk, VP of AI
Ready to put your data to work?
Talk to our team to learn how Embed can integrate with your stack, improve retrieval accuracy, and scale to production.
Discover how Embed performs across your languages, formats, and domains
Explore how Embed, Command, and Rerank can work together in RAG and agentic pipelines
Determine the right deployment path for your infrastructure and security needs
Get support integrating Embed and scaling semantic search and retrieval to production