Find My AI Tool Logo
All tools

SearchUnify AI Agents

SearchUnify AI Agents are purpose-built AI agents for customer service and support that answer customers, draft replies for reps, route tickets, flag escalations, and audit cases, retrieving and citing sources from enterprise systems before acting.

ProductivityCustomer SupportCustomer ServiceAI AgentsKnowledge Management

About SearchUnify AI Agents

SearchUnify AI Agents

SearchUnify positions its AI agents as a support harness that runs on top of existing systems such as CRM, ticketing, knowledge bases, product docs, community, and telemetry, without model training, agent building, or knowledge migration. Agents are described as purpose-built for defined support jobs including L1 support, L2 troubleshooting, routing, escalation, knowledge, and case quality, and they share context across the support journey. The page states a 'no source, no action' rule: answers, drafts, routes, and scores are retrieved first, cited, and logged, and agents hand off to a person or the next agent when no reliable source is found. Governance features include permission-aware retrieval, topic-level guardrails, confidence thresholds, and an audit trail. The page cites SOC 2 Type II, ISO 27001, HIPAA, and GDPR support, and model-agnostic operation with GPT, Claude, Gemini, and open-weight models. Published customer case study figures reported on the page include 60% increase in case deflection, 45% reduction in escalations, 35% faster resolution, 40% higher CSAT, and 20% higher renewals.

Key features

  • Purpose-built AI agents for defined support jobs such as L1 support, L2 troubleshooting, routing, escalation, knowledge, and case quality
  • Agents retrieve from enterprise systems before acting and show cited sources
  • Hand-off to a person or the next agent when a reliable source is not found
  • Shared context across agents on the same case
  • Prebuilt connectors and MCP for 40+ systems including Salesforce, ServiceNow, Zendesk, Jira, Slack, Confluence, and ELK
  • Permission-aware retrieval that inherits existing entitlements
  • Topic-level guardrails and confidence thresholds for handoff
  • Full audit trail of what was retrieved, said, and why
  • Model-agnostic support for GPT, Claude, Gemini, and open-weight models
  • Knowledge creation from cases and gap detection
  • Quality scoring of closed cases

Best suited for

  • Enterprise customer support teams
  • Technical support organizations
  • Knowledge management teams using KCS
  • Support leaders seeking cited, auditable AI responses in regulated industries

Pricing

Not stated on the website

AI agentscustomer supportMCPcustomer serviceenterprise searchknowledge managementticket routingcase resolutionagentic RAG

Discussion

No comments yet. Start the conversation.