Today’s enterprises are inundated with vast amounts of data spread across numerous formats, languages, and systems. The challenge lies not just in retrieving this data but in making it actionable, particularly in new generative and conversational experiences.
The rise of large language models (LLMs) has opened new possibilities for processing and understanding this data, but these models are only as good as the information they can access – and this problem compounds as the number of AI initiatives grows by the day.
With the Coveo Relevance-Augmented Passage Retrieval API, the Coveo Platform now provides an LLM friendly API capable of powering all of an enterprise’ s RAG applications in addition to the existing AI Search and Relevance Generative Answering capabilities. With one relevance platform, enterprises can provide data to all their AI experiences, without having to copy data in multiple systems or managing complex data workflows.
Enterprises require AI systems that can understand intent, provide contextually relevant information, and integrate seamlessly with existing technologies. The Passage Retrieval API addresses these needs head-on, providing a bridge between vast data repositories and the intelligent applications that need to access them.
Why Intelligent Retrieval is Crucial for Enterprise RAG Strategies
RAG represents a significant advancement in how enterprises can leverage AI to generate more accurate, contextually relevant content. However, the success of RAG strategies hinges on the quality and accessibility of the underlying data.
In RAG systems, enterprises can ground LLMs in their proprietary data and knowledge sources. However, the retrieval process — the “R” in RAG — is notoriously the most challenging aspect. It involves extracting the most relevant and accurate information from vast, fragmented data across the entire enterprise, which is complex and slows down generative AI initiatives. This process is vital, as it directly influences the accuracy and security of AI-generated responses.
Coveo’s Passage Retrieval API is designed to meet this need, providing the foundational layer that makes RAG not just possible, but powerful.
For enterprises, the implications are profound. By integrating the Passage Retrieval API into their RAG strategies, businesses can achieve a level of personalization and efficiency that was previously unattainable. This translates to more effective customer interactions, quicker access to critical information, and a competitive edge in a landscape where digital transformation is no longer optional but essential.
In addition to the above, companies have multiple AI initiatives that require access to their data. They have other custom LLM applications specialized for their business, and they probably use applications and software ecosystems that provide their own “assistant” or “copilot” that can do actions in their specific ecosystems.
Soon, enterprises will have multiple AI applications (copilots, custom AI apps, search pages with question answering and more), all of which require secured access to the enterprise data. The Coveo Platform, with the addition of the Passage Retrieval API, can now empower these otherwise siloed generative AI experiences with full enterprise knowledge. Using Coveo as the knowledge provider for all these AI applications is a more practical solution for an enterprise than to copy all the data in all these ecosystems.
And, as enterprises continue to grapple with the challenges of growing those same AI initiatives over time, the Passage Retrieval API offers a solution that is both scalable and secure. Its enterprise-grade security features ensure that sensitive data remains protected, while its scalability means that as the business grows, the API can grow with it.
The Power of Coveo’s Relevance-Augmented Passage Retrieval API
Coveo’s Passage Retrieval API makes the Coveo Relevance Platform capabilities accessible to enhance the capabilities of LLMs, by providing passages in a LLM friendly format, making them more effective in real-world enterprise applications.
The API’s ability to index and process documents in various formats, respect data permissions, and generate multilingual embeddings ensures that it can handle the complexity and scale of modern enterprises.
It combines the precision of keyword search with the broader understanding enabled by semantic search, creating a hybrid system that excels in both speed and relevance. This dual approach is crucial for enterprises where both performance and accuracy are non-negotiable.
Its integration with Coveo’s broader platform allows for unified personalization and AI-driven recommendations. This synergy not only improves the immediate user experience but also contributes to a continuous feedback loop, where the system learns and evolves over time, further enhancing its relevance and accuracy.
Real-World Impact: How Leading Companies Use the Passage Retrieval API
Coveo’s Passage Retrieval API is the foundation for real-world generative AI experiences that are reshaping support, service, and productivity. Here’s how three leading organizations are putting it to work:
Alation: From overwhelming ticket volume to AI-powered self-service
Alation needed to scale customer support without compromising quality. With only a small team managing a high volume of tickets, they introduced Alamigo, a generative chatbot built with Coveo’s PR API. This hybrid approach combines Alation’s large language model with Coveo’s precise enterprise retrieval to ground answers in real support content.
The result? Alamigo now deflects over 50% of support cases — giving customers instant answers and agents more time to focus on complex issues.
Xero: Delivering generative support across social channels
Xero wanted to elevate their digital support experience and extend self-service to social platforms like Facebook Messenger. After a rigorous evaluation of RAG and LLM technologies, they chose Coveo’s Relevance Generative Answering — powered by the PR API — to ensure fast, accurate responses grounded in trusted content.
Integrated with Salesforce Service Cloud, the solution led to a 30% reduction in cases requiring specialist support, an 80% drop in time spent monitoring Messenger, and a 75% decrease in messages handled manually by the social team.
Global Software Enterprise: Powering RAG at scale with precision
A $16B software company was developing its own retrieval-augmented generation (RAG) solution but found its existing internal search engine fell short on precision and relevance. Instead of rebuilding from scratch, the team embedded Coveo’s PR API as the retrieval layer.
This enabled them to maintain full control of the generative logic while achieving a 73% accuracy improvement in generated answers in just 2 weeks — with the added benefit of production-ready security, scalability, and content governance out-of-the-box.
The Future of Enterprise Intelligence
To date, more than 30 enterprises have chosen Coveo’s full out-of-the-box solution to solve their generative question answering needs and much of the market will prefer to buy out of the box. However, for companies that have chosen to invest in their own LLMs and in copilots, they can now leverage this API.
The launch of Coveo’s Relevance-Augmented Passage Retrieval API is more than just a new tool — it is a paradigm shift in how enterprises approach data retrieval and AI integration. As the demand for more intelligent, responsive, and secure applications continues to rise, the Passage Retrieval API will undoubtedly play a pivotal role in rapidly enabling knowledge-hungry AI applications without requiring complex and expensive data copies.
For organizations looking to stay ahead, adopting this API is not just a strategic move; it is a necessity. By empowering their LLM-powered applications with the capabilities of the Relevance-Augmented Passage Retrieval API, enterprises can rapidly unlock new levels of innovation, efficiency, and customer satisfaction, ensuring they remain at the forefront of their industry.
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