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AI Agents + RAG = Agentic Retrieval

Transforming Enterprise AI with Agentic Retrieval

Why Agentic Retrieval Matters for Enterprises

Enterprises are moving away from traditional search methods to meet rising expectations for faster, smarter and more intuitive AI solutions. 

The goal is clear: save time, enable self-service, deliver proactive employee and customer care and create better experiences. 

Users now demand ChatGPT-like interactions—seamless, context-aware, and highly relevant. 

Agentic retrieval addresses these needs by replacing static, rule-based systems with dynamic, intelligent agents that adapt to complex queries, streamline operations, and enhance satisfaction. 

For businesses, this shift is critical to stay competitive in an era where efficiency and personalization are non-negotiable.

What Agentic Retrieval Delivers

Agentic retrieval redefines enterprise search and AI interaction by offering…

Accuracy and Efficiency

Dynamic AI Agents enhance accuracy by leveraging hybrid search, contextual retrieval and reranking to deliver precise responses from indexed data or runtime searches via MCP or API-based methods, though processing may be slower compared to direct retrieval.

Cost Efficiency
Automation reduces manual intervention, lowering operational costs while maintaining high performance.

Seamless Knowledge Integration
Blending structured (for example CRM data) and unstructured (for example emails, documents) data ensures comprehensive responses.

Simplified Maintenance
Continuous learning and teachable models improve retrieval over time, reducing upkeep efforts.

Segregated Internal and External Use
Tailored pipelines separate internal knowledge management (for example employee support) from external-facing applications (for example customer service), ensuring relevance and security.

This transformation applies to enterprise search broadly, with potential for deeper exploration in internal knowledge management versus customer-facing applications in separate discussions.

Feature

Description

Relevance to Agentic Retrieval

Blending Data

Integrates structured and unstructured data

Ensures comprehensive knowledge base for retrieval

Role-Based Access Controls

Manages permissions across systems

Enhances security for sensitive data retrieval

Large-Scale Volume Handling

Handles high data volumes with enterprise security

Supports scalability in retrieval operations

Customizable Pipelines

Tailored extraction and retrieval pipelines

Enables dynamic, agentic processing

Intelligent Context Augmentation

Augments responses with context from various sources

Improves relevance in retrieval

Multimodal Content Handling

Ingests and retrieves text, voice, images

Supports diverse data types for comprehensive retrieval

Multi-Vector Retrieval

Uses weighted scoring for complex, multi-system retrieval

Prioritizes relevant information in heterogeneous data

Evaluation of Effectiveness

Subjective and objective assessment of retrieval

Ensures continuous improvement in retrieval accuracy

Continuous Learning

Teachable models improve with feedback

Enhances agentic retrieval over time

How Kore.ai’s Agent Platform Enables Agentic Retrieval

Kore.ai’s Agent Platform is purpose-built to deliver agentic retrieval, empowering enterprises with a robust suite of features…

Blending Structured and Unstructured Data

The platform integrates data from enterprise systems and unstructured sources like documents, enabling AI agents to provide holistic, context-rich responses. For example, it can combine CRM customer data with email threads for personalized support.

Role-Based Access Controls

With enterprise-grade security (SOC2 Type2, HIPAA-compliant), Kore.ai ensures sensitive data is accessible only to authorized users, maintaining compliance across systems.

Scalability for Large Volumes

Designed for enterprise-scale operations, the platform handles massive data volumes without compromising performance, ensuring reliability in high-demand scenarios.

Customizable Extraction and Retrieval Pipelines

Agentic flows allow businesses to tailor data processing and retrieval to specific needs, automating complex tasks and optimizing outcomes.

Intelligent Context Augmentation

AI agents enhance responses by pulling context from diverse sources, ensuring relevance in customer service and employee productivity use cases.

Multimodal Content Support

The platform ingests and retrieves text, voice, and images, enabling versatile applications like contact center integrations and agent desktops.

Multi-Vector Retrieval with Weighted Scoring

For complex queries across heterogeneous systems, Kore.ai prioritizes relevant information using advanced retrieval techniques, ensuring accuracy.

Continuous Improvement

Teachable models learn from human and AI feedback, refining retrieval effectiveness over time. The Evaluation Studio provides subjective and objective metrics to fine-tune performance.

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Implications for Enterprises

The shift to agentic retrieval has profound implications for enterprises…

Enhanced Productivity

Faster, more accurate responses empower employees and customers, reducing wait times and boosting efficiency.

Competitive Advantage

Offering intuitive, ChatGPT-like experiences meets modern expectations, strengthening brand loyalty.

Cost Savings

Automation and simplified maintenance lower operational expenses, freeing resources for innovation.

Compliance and Security

Robust access controls and enterprise-grade security ensure data protection, critical for regulated industries like healthcare and finance.

Scalability

The ability to handle diverse data types and large volumes supports growth without compromising performance.

By adopting agentic retrieval, enterprises can transform internal operations and customer interactions, positioning themselves as leaders in AI-driven innovation.

Impact on the Kore.ai Platform

Kore.ai’s Agent Platform is at the forefront of this evolution, aligning with agentic retrieval’s demands for adaptability, security, and scalability. 

Its AI Agents Marketplace, offering pre-built templates like BankAssist and HealthAssist, accelerates deployment for industry-specific needs, reducing time-to-value. 

The platform’s focus on multimodal content, customisable pipelines and continuous learning ensures it meets diverse enterprise requirements, from contact centers to knowledge management. 

By integrating advanced techniques like hybrid search and multi-vector retrieval, Kore.ai solidifies its position as a leader in enterprise AI, delivering solutions that are both innovative and practical.

Conclusion

Agentic retrieval is revolutionising enterprise AI by addressing the need for speed, relevance and personalisation.

Kore.ai’s Agent Platform embodies this transformation, offering tools to blend data, secure access and scale operations while continuously improving. 

For enterprises, adopting this approach means better experiences, lower costs, and a competitive edge. As expectations for intelligent, proactive AI grow, Kore.ai provides the foundation to meet and exceed them, redefining what’s possible in enterprise search and interaction.

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