Coveo Launches RAG-as-a-Service for Enhanced AWS AI Solutions
On December 1, 2025, Coveo, renowned for its innovative AI-Relevance solutions, introduced its latest offering: Retrieval Augmented Generation (RAG)-as-a-Service, specifically designed to integrate seamlessly with AWS agentic AI services. This groundbreaking service is supported by a Coveo-hosted Managed Cloud Platform (MCP) server and aims to enhance the precision, security, and scalability of generative AI within enterprises.
The significance of this service lies in its ability to empower organizations to ground AWS agentic AI capabilities, such as Amazon Bedrock AgentCore, faced with the challenge of ensuring that AI responses are not just automated but also factual, context-rich, and compliant with organizational standards. According to Sebastien Paquet, Coveo's Vice President of AI Strategy, the growing accessibility of large language models (LLMs) in the market highlights the necessity for enterprises to ensure relevance in their outputs. He stated, ‘While LLMs have become widely available, their enterprise value depends on relevance, how effectively they can ground responses in factual, secure, and permission-aware data.’ Thus, RAG-as-a-Service will allow developers to innovate with greater speed, alleviating the complexities of data retrieval while relying on Coveo’s extensive expertise in enterprise relevance.
The Coveo RAG-as-a-Service suite features a variety of tools accessible via a fully managed MCP server, which include:
As part of its debut at the AWS re:Invent conference, Coveo is demonstrating this permission-aware RAG-as-a-Service model, highlighting how it can facilitate the secure and scalable integration of Amazon Bedrock AgentCore and Amazon Quick Suite functionalities into corporate environments. Developers interested in leveraging this enterprise-ready foundation for their generative AI or AI agents projects will have access through an exclusive invitation-only early access program.
Coveo is committed to delivering transformative AI-relevance solutions that enhance interactions for both customers and employees, leading to improved business outcomes. By personalizing each experience according to the specific context and needs of users, Coveo sets a high standard within a competitive landscape.
In conclusion, the launch of RAG-as-a-Service signifies a major advancement in the enterprise AI realm, elegantly bridging AWS capabilities with Coveo's robust relevance platform, ultimately ushering in a new era of secure, grounded, and efficient generative AI applications. For ongoing updates and insights, one may follow Coveo’s blog and social media channels on LinkedIn and YouTube.
The significance of this service lies in its ability to empower organizations to ground AWS agentic AI capabilities, such as Amazon Bedrock AgentCore, faced with the challenge of ensuring that AI responses are not just automated but also factual, context-rich, and compliant with organizational standards. According to Sebastien Paquet, Coveo's Vice President of AI Strategy, the growing accessibility of large language models (LLMs) in the market highlights the necessity for enterprises to ensure relevance in their outputs. He stated, ‘While LLMs have become widely available, their enterprise value depends on relevance, how effectively they can ground responses in factual, secure, and permission-aware data.’ Thus, RAG-as-a-Service will allow developers to innovate with greater speed, alleviating the complexities of data retrieval while relying on Coveo’s extensive expertise in enterprise relevance.
The Coveo RAG-as-a-Service suite features a variety of tools accessible via a fully managed MCP server, which include:
- - Passage Retrieval: This function returns the most pertinent segments of enterprise knowledge to effectively ground LLM prompts, ensuring that the AI-generated content is not only accurate but also relevant to the organization's context.
- - Answer Generation: This tool utilizes organizational data to produce accurate and tailored answers, supported by Amazon Nova's capabilities, adding a layer of intelligence and specificity to AI output.
- - Search Functionality: An advanced search feature retrieves ranked results, providing context and facilitating exploration within the enterprise’s knowledge base.
- - Document Fetching: For tasks that require elaborate reasoning or detailed research, this facility supplies complete document texts, empowering users to achieve deeper insights and understanding.
As part of its debut at the AWS re:Invent conference, Coveo is demonstrating this permission-aware RAG-as-a-Service model, highlighting how it can facilitate the secure and scalable integration of Amazon Bedrock AgentCore and Amazon Quick Suite functionalities into corporate environments. Developers interested in leveraging this enterprise-ready foundation for their generative AI or AI agents projects will have access through an exclusive invitation-only early access program.
Coveo is committed to delivering transformative AI-relevance solutions that enhance interactions for both customers and employees, leading to improved business outcomes. By personalizing each experience according to the specific context and needs of users, Coveo sets a high standard within a competitive landscape.
In conclusion, the launch of RAG-as-a-Service signifies a major advancement in the enterprise AI realm, elegantly bridging AWS capabilities with Coveo's robust relevance platform, ultimately ushering in a new era of secure, grounded, and efficient generative AI applications. For ongoing updates and insights, one may follow Coveo’s blog and social media channels on LinkedIn and YouTube.
Topics Business Technology）
【About Using Articles】
You can freely use the title and article content by linking to the page where the article is posted.
※ Images cannot be used.
【About Links】
Links are free to use.