Conference Presentation, Panel, Fireside Chat
Cohere, Adobe, Teneo: Revolutionizing Enterprise Search with AI. Unlock The Potential of Your Data
- Partnership Announcement: Adobe and Cohere have formally partnered to integrate Cohere's AI embedding and re-ranking models into Adobe's Document Cloud, specifically powering the Adobe Acrobat AI Assistant.
- Strategic Goal: The collaboration aims to transform enterprise search from simple document retrieval to "intelligent action" by unifying fragmented data across systems (e.g., Salesforce, SharePoint, S3) to support the development of next-generation AI agents.
- Adobe's Implementation: Adobe selected Cohere specifically because its models met specific performance, cost, and quality benchmarks for their "trust pipeline," which attributes AI-generated answers back to specific source document components.
- Technical Mechanism: The system utilizes a two-stage approach involving Cohere's embedding models to understand query intent and meaning (rather than exact keyword matches), followed by re-ranking models to order results by contextual relevance.
- Multilingual Capabilities: The integrated technology now supports multilingual search across over 100 languages, with Adobe immediately unlocking French, Spanish, Italian, Japanese, and Brazilian Portuguese for Acrobat users.
- Multimodal Processing: The solution processes mixed document types, including text, images, diagrams with overlay text, PDFs, spreadsheets, and Office files, providing context for non-textual elements without requiring captions.
- Deployment Flexibility: Cohere deploys its models via cloud partners like AWS, but also offers full private on-premises or private cloud deployment in any region to satisfy strict enterprise security and compliance requirements.
- AI Agent Enablement: The partnership positions enterprise search as the critical "maps" layer for AI agents, providing the up-to-date, context-rich, and multimodal data necessary for agents to perform autonomous tasks like compliance checking and policy interpretation.
- Future Roadmap: Adobe and Cohere anticipate the partnership will evolve to rapidly leverage emerging model architectures, such as Cohere's "Embed 4" model, which consolidates multilingual and multimodal capabilities into a single architecture.
- Trust & Safety: To address enterprise concerns regarding hallucinations (e.g., providing outdated information like 2022 data in 2025), the system enforces RAG (Retrieval-Augmented Generation) practices that require citations to original source passages before presenting answers.
- Market Challenge Identification: Participants identified three primary barriers to enterprise AI adoption: data silos across disparate systems, the limitations of traditional lexical search, and security/compliance hurdles that prevent full data access by IT teams.