News
The Gist
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New service launch. Coveo introduces RAG-as-a-Service for AWS agentic AI integration.
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Enterprise data grounding. Service lets organizations ground AI with secure, permission-aware data.
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Developer impact. Developers gain a managed foundation for building compliant, contextually relevant GenAI applications.
Coveo launched RAG-as-a-Service for AWS AI agents on Dec. 1, providing a managed retrieval layer to ground enterprise generative AI in secure organizational data.
The cloud-native offering integrates with Amazon Bedrock AgentCore, Amazon Bedrock Agents and Amazon Quick Suite. Company officials said the service builds on Coveo’s search heritage, enabling organizations to anchor AI agents in proprietary knowledge via a hosted MCP Server.
Table of Contents
- Impacted Audiences
- Enterprise RAG Shifts Focus to Security & Scale
- Core RAG Architecture & Benefits
- Addressing Enterprise Deployment Challenges
- Emerging Platform Capabilities
- Amazon Bedrock Means Efficient Generative AI
- Coveo Background
Impacted Audiences
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Enterprise developers building generative AI applications.
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IT leaders managing AI security and compliance.
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Digital commerce and customer service teams deploying AI agents.
Enterprise RAG Shifts Focus to Security & Scale
RAG strategies are shifting from experimental pilots to secure production architectures. These deployments prioritize data governance and retrieval accuracy over speed alone.
Core RAG Architecture & Benefits
Retrieval-augmented generation (RAG) blends static LLM training data with real-time search capabilities. External data sources augment query context before prompts reach the model to enable grounded responses.
This approach reduces hallucinations while providing verifiable sources. It delivers the reliability enterprises require for trustworthy AI deployments.
Studies demonstrate RAG can increase base model accuracy by 40%, with similar improvements becoming standard. Even when quality gains are modest, RAG enables auditing by modularizing knowledge bases.
Addressing Enterprise Deployment Challenges
Accuracy & Data Quality
Basic vector databases often fail to meet enterprise needs. Organizations require advanced hybrid retrieval and AI ranking to ensure precision.
Coveo framed this approach as "Relevance-Augmented Retrieval." The vendor emphasized the need to rapidly pinpoint contextually relevant insights from vast amounts of structured and unstructured data.
Content Unification & Access
Tech lock-in remains a hurdle where AI tools restrict access to single-vendor platforms. Enterprises need an agnostic AI layer that securely connects information from internal and external sources.
Security & Permissions
Production deployments must deliver information quickly while respecting existing security frameworks. This requires tight integration with enterprise identity systems and data governance policies.
Emerging Platform Capabilities
New SaaS-based RAG platforms now offer multilingual support and multi-LLM integration. Semantic search across unstructured data and verifiable outputs with source attribution are also essential.
Current Adoption Reality
As enterprises move beyond AI experimentation, adoption realities are sobering. While 88% of organizations actively monitor generative AI’s evolution, only 10% of deployments have moved into production.
Security, privacy and reliability remain the primary obstacles. IT departments face pressure to implement governance frameworks ensuring accuracy and compliance.
Amazon Bedrock Means Efficient Generative AI
By combining Coveo's proven relevance platform with models delivered via Amazon Bedrock, enterprises can deploy secure, grounded, and high-performing GenAI applications in record time.
- Eric Immermann, practice director for search and retrieval
Perficient
RAG-as-a-Service Feature Breakdown
The new offering delivers four configurable tools through a fully managed MCP Server:
| Capability | Description |
|---|---|
| Passage Retrieval | Returns relevant enterprise knowledge for LLM prompts |
| Answer | Generates responses from organizational data via Amazon Nova |
| Search | Retrieves ranked results for context and exploration |
| Fetch | Provides complete documents to support reasoning tasks |
Coveo Background
Coveo targets digital commerce, customer service and digital workplace leaders at enterprise and upper-midmarket organizations. The company was founded in 2005.
Platform Capabilities
Its AI-powered platform delivers search, recommendations, personalization and generative answering across commerce, service, partner and employee portals. The modular design integrates with major enterprise systems.
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Market Focus
Coveo positions itself in the enterprise AI search and digital experience market. The platform is typically adopted by organizations seeking to unify content and improve digital interactions.
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