Transforming Support with SearchUnify AI Agents & Model Context Protocol (MCP)

Empowering seamless, secure, and intelligent AI interactions across your enterprise ecosystem

Seamless Integration with Enterprise and Open-Source Systems

MCP provides standardized APIs that allow SearchUnify AI Agents to effortlessly connect with enterprise platforms like Salesforce, ServiceNow, and Zendesk, as well as open-source tools such as OTRS and GLPI enabling real-time data fetching and dynamic contextual retrieval across diverse systems.

Intelligent Workflow Automation & Proactive Self-Service and Support

MCP powers AI Agents to automate triage, escalation, and ticketing while enabling self-service through the Intelligent Front-Door Framework. In KCS environments, it also drives AI-based knowledge creation, retrieval, and recommendations for faster resolutions and smarter knowledge management. generation, and system updates can be seamlessly executed using integrated tools.

Enhanced Security and Scalability

Security is foundational to MCP. Encrypted communication and role-based access control ensure compliance and transparency. Coupled with SearchUnify’s Governance Layer, AI interactions are monitored through audit trails, explainable AI insights, and human-in-the-loop validation. This architecture also ensures scalability, allowing AI Agents to interact with multiple systems simultaneously without creating integration bottlenecks.

Improve Employee Onboarding Experience and Reduce Delays
in Obtaining HR Assistance

Real-Time Analytics and Insights

MCP facilitates the retrieval and analysis of real-time support metrics, enabling data-driven decision-making. AI Agents can access actionable insights to inform strategies and improve support outcomes.

Advanced Capabilities Unlocked by MCP

Federated Retrieval-Augmented Generation (SearchUnifyFRAG™)

AI Agents deliver rich, precise answers by securely accessing multiple federated sources in real time, boosting relevance while keeping data decentralized and compliant.

SearchUnify Contextual Relevance Engine (SCORE Framework)

MCP helps AI Agents harness contextual signals to personalize search results in real time, surfacing the most relevant content based on persona, journey, and intent.

Forecasting for Tickets and Escalation Prediction

By analyzing historical data trends, AI Agents forecast future support volumes and risks, enabling proactive escalation handling, improved resource planning, and SLA performance.

Classification for Auto-Triage and Smart Routing

MCP lets AI Agents use classification models to tag and prioritize tickets based on urgency, topic, or tone—streamlining case triage and enhancing routing accuracy.

Quick Clustering for Pattern Recognition

Real-time clustering enables AI Agents to detect and group similar issues or tickets instantly, supporting faster bulk resolutions and uncovering trends or knowledge gaps.

Real-Time Orchestration of ML Pipelines

AI Agents orchestrate multiple ML models—clustering, classification, and generation—seamlessly through MCP, enabling complex workflows without added latency.