Use Case Exploration
The Vectara Retrieval Augmented Generation as-a-Service (RAGaaS) platform enables enterprises to rapidly create GenAI experiences, from conversational AI agents to document generation and research applications. These agents reduce hallucinations and provide relevant results.
Build applications that understand natural language queries without requiring deep AI expertise. Vectara reduces hallucinations, supports 100+ languages, maintains enterprise-grade security, and never trains on customer content.
Conversational AI and virtual assistants
Build intelligent conversational experiences that understand context and provide accurate responses:
- Customer service virtual assistants: Deploy 24/7 self-service assistants, chat bots, or help desk agents.
- Engineering and operations support: Provide technical specifications, machine configurations, and troubleshooting guides through natural conversation.
- Department-specific agents: Create specialized conversational AI from
company data and knowledge for sales, HR, legal, or IT teams.
Document generation and analysis
Transform how your organization creates and analyzes documents:
- Scalable RFP generation: Automatically generate responses based on enterprise domain data.
- AI-driven loan underwriting: Increase accuracy with built-in guardrails and compliance checks.
- Contract analysis: Build AI agents that ensure compliance with pricing policies, vendor lists, and regulatory standards.
Research and knowledge discovery
Accelerate research and uncover insights from large document collections:
- Scientific research: Help R&D teams discover new materials and novel designs faster by searching through publications and research papers.
- Financial analysis: Analyze financial reports, market data, and regulatory filings to guide investment decisions.
- Legal research: Search through case law, statutes, and legal documents to find relevant precedents and insights.
Vectara acts as a global research assistant that reads and understands large volumes of documents instantly, providing recommendations and citations grounded in your data.
Question answering and knowledge management
Enable precise answers from your organization's knowledge base:
- Internal knowledge systems: Let employees quickly find information from company handbooks, policies, and training materials.
- Customer support: Embed FAQs and support documentation to provide instant, accurate responses.
- Product information: Help users find specifications, manuals, and troubleshooting guides.
Create a dynamic question and answer system that continuously improves user experience.
Semantic search for applications
Embed powerful search capabilities into your applications without becoming an LLM expert:
- E-commerce product search: Help customers find products using natural language descriptions.
- Document repositories: Enable users to search across large document collections by meaning, not just keywords.
- Support ticket analysis: Find similar cases and relevant solutions from historical support data.
Vectara bridges the gap between user queries and your data, delivering relevant results regardless of how questions are phrased.
Console quick start
The Vectara Console quick start tutorial shows you how to index and search your data quickly. Common data types that work well with Vectara include:
- Employee handbooks and training materials
- Product manuals and technical documentation
- Legal contracts and compliance documents
- Research papers and scientific publications
- Financial reports and regulatory filings
- Knowledge base articles and support content
These document types contain nuanced information where semantic search excels, helping users find specific details without knowing exact keywords or section titles.
Check out example Vectara applications, demos, and tutorials to explore platform capabilities across various use cases and datasets.