Enterprise Search Accelerator

Cut Support Ticket Volume 20-30%. Without Hiring More Agents.

Ticket Knowledge Base turns your Elasticsearch data into an intelligent self-service system. Semantic search that understands what customers mean, not just what they type. RAG-powered answers cited from your own documentation.

verified 28% ticket reduction in first quarter schedule 24-Hour Response SLA
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Your Help Center Search Is Broken. Your Team Pays the Price.

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Customers Can't Find Answers

Your help center has the answers. Customers can't find them. They type "payment failed" and get articles about setting up payments. So they open a ticket instead.

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Same 20 Questions. Every Day.

Your support team answers the same tier-1 questions daily while complex cases stack up in the queue. Hiring more agents treats the symptom, not the cause.

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Keyword Search Matches Words, Not Intent

Customers describe problems in natural language. Keyword search matches strings, not meaning. Different questions about the same issue return different results. Or no results.

From Customer Question to Cited Answer in Seconds

1

Index Your Knowledge Corpus

Ingest historical support tickets, help center articles, FAQs, and product documentation into Elasticsearch with semantic embeddings. Works with your existing documentation as-is.

2

Customers Search by Intent

Customers get intent-aware results. No exact keyword match required. "Why was I charged twice" and "double billing" return the same right answer.

3

RAG Generates Cited Answers

The RAG layer reads your documentation and generates direct answers with source citations. Not hallucinations. Not generic responses. Grounded in your actual knowledge corpus.

4

Agents Get AI-Assisted Replies

Tickets that do come in get auto-tagged, routed to the right team, and paired with AI-suggested replies pulling from the same knowledge base. Resolution time drops.

Six Capabilities That Reduce Your Ticket Queue

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RAG-Powered Answer Generation

LLM generates direct, cited answers from your knowledge corpus. Customers get the answer, not a list of documents. Every response includes the source article for verification.

Before: Keyword Search

Keyword search returns 12 articles. Customer reads 3, gives up, opens ticket.

After: RAG Answer

RAG returns one direct answer with citation. Customer resolves issue. No ticket.

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Semantic Search over Support Corpus

Finds answers based on customer intent, not exact keyword match. Powered by ELSER and Elasticsearch vector search.

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Ticketing System Integration

Native connectors for Zendesk, Intercom, Salesforce Service Cloud, and Jira Service Management. Your existing workflows stay intact.

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Auto-Tagging and Routing

Incoming tickets semantically classified and routed to the right team automatically. Based on similarity to known issue patterns, not rigid keyword rules.

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Agent Assist Mode

Support agents get AI-suggested replies with source citations for complex cases. Same knowledge base, different interface. Reduces resolution time.

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Deflection Metrics Dashboard

Built-in reporting on ticket deflection rate, search success rate, and knowledge gap identification. See which questions your docs don't answer yet.

Measurable Impact. First Quarter.

28%
Ticket volume reduction
3x
Faster customer resolution
20+
Agent hours reclaimed per week

Compare: hiring another support agent at $50-70K/year vs. deploying Ticket Knowledge Base. One scales. The other doesn't.

Ecosystem Fit

Built on the Elasticsearch Ecosystem You Already Trust

Ticket Knowledge Base is the support search accelerator within the Enterprise Search pillar. Pairs with Product Relevance Optimizer for organizations that need both support search and product discovery. Works within the AI Search Pilot engagement as the support use case implementation.

Why SquareShift Builds This

  • check_circle Elastic Select Reseller + SI Partner
  • check_circle Elastic Innovation Award 2023
  • check_circle 60+ production Elasticsearch implementations
  • check_circle Pre-engineered. Expert-deployed. Custom-fitted.
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chat Intercom
cloud Salesforce Service Cloud
bug_report Jira Service Management
Central search node connected to four integration endpoint nodes in topology diagram

Customer Testimonial

Reduced support ticket volume 28% in first quarter. Customers found answers 3x faster than previous search.

Head of Support
B2B SaaS Company
28%
Ticket volume reduction
3x
Faster customer resolution

See how AI Triage Assistant achieved 90% false positive reduction for AI-native credentials.

Frequently Asked Questions

Straight answers to the questions we get before the demo. If something isn't covered here, ask in the first five minutes.

No. It works with your existing documentation as-is, indexed into Elasticsearch with semantic embeddings. Better-structured content improves answer quality, but restructuring is not required at launch.
Regular search returns a list of documents. RAG reads those documents and generates a direct answer with citations. Like asking a knowledgeable colleague who has read every article in your help center, not a search engine that returns links.
OpenAI, Anthropic, and self-hosted open-source LLMs. No vendor lock-in. Choose the provider that fits your security and cost requirements.
Yes. Native Zendesk connector included. Salesforce Service Cloud, Intercom, and Jira Service Management also supported. Your existing ticketing workflows stay intact.
Available as SaaS subscription or standalone implementation. Pricing is based on your knowledge corpus size and integration requirements. Contact us for a custom quote based on your support volume.

Make Your Knowledge Base Work for Customers

Schedule a 15-minute demo to see Ticket Knowledge Base in action with your own support data. Or start a free trial and index your documentation today.

verified 24-Hour Response SLA. Demo scheduled within 72 hours.
Schedule 15-Minute Demo