Make AI Factually Accurate with Retrieval-Augmented Generation
increased deflection rates
factual accuracy
Customer Support Teams, Generate Contextual Responses
Automated Chatbot Enhancement
Power Einstein Chatbots with unified knowledge bases including articles, manuals, PDFs, and website content. Retrieve the right answers on the fly, improving deflection rates and customer satisfaction.
Intelligent Case Routing
Automatically classify and route complex cases to the correct queue based on semantic understanding of case details and relevant knowledge articles.
Business Analysts, Discover Hidden Insights
Document & Knowledge Mining
Run semantic search over indexed content—PDFs, KB articles, historical cases—to generate on-demand insights, trend analyses, and executive summaries.
Reduced Time-to-Insight
Slash the time spent manually searching disparate systems by leveraging intelligent retrieval of relevant information across your knowledge bases.
Enterprise Architects, Integrate Across Clouds
Multi-Cloud Vector Store Integration
Connect natively to major RAG providers—Google Vertex AI Matching Engine on GCP, Amazon Pinecone (via AWS), Azure Cognitive Search, and others—using your preferred vector store.
100% Salesforce-Native Execution
Pull content directly from inside your Salesforce org with no external agent or middleware required, preserving data residency and simplifying governance.
Why Teams Choose GPTfy RAG
Hybrid Semantic Retrieval
Balance recall and precision with support for both pure vector search and hybrid search (vector + keyword), reducing hallucinations while ensuring consistent, context-aware results.
Flexible Data Ingestion
Identify and pull in content from Salesforce Knowledge articles, custom objects, attached files (PDFs, docs), external objects, or websites—all through a declarative interface.
Enterprise-Grade Security
Apply PII-masking rules before content is embedded, enforce field-level access via Salesforce permissions, and log every retrieval and AI call in an immutable audit trail.
Real-World Use Cases
Self-Service Deflection
Improve Einstein Chatbot deflection rates by 70% with RAG-powered responses that pull from unified knowledge sources.
Agent Productivity
Enable support agents to find relevant case resolution paths 5X faster with context-aware recommendations from similar past cases.
Knowledge Extraction
Automatically extract insights from disorganized document libraries and generate summaries, trend reports, and business intelligence.
Legacy System Integration
Connect AI to historical record systems using RAG to bridge knowledge gaps without complex data migrations.
Technical Capabilities
Multi-Cloud Vector Stores
Native integration with Google Vertex, Pinecone, Azure Cognitive Search, and more, so you can choose the vector store that fits your architecture.
Context-Aware Prompt Orchestration
Retrieve and present the most relevant content chunks from your vector store based on user queries or record context, injecting them into AI prompts.
Declarative Configuration
Set up and maintain vector databases entirely within Salesforce using point-and-click tools, with no external infrastructure to maintain.
Vector Processing Security
Only vector embeddings (not raw PII) leave Salesforce for your vector store, with sensitive data anonymized pre-embedding and re-identified only in-org.
AI with Context. Answers You Can Trust.
See how GPTfy's RAG capabilities can enhance your Salesforce AI experience with contextual, factual information in just 30 minutes. We'll demonstrate implementation tailored to your business needs.
Book 30 mins. See RAG in action.100% Salesforce Native. AppExchange Security Approved.
GPTfy's RAG implementation operates within your Salesforce security model. Only vector embeddings—not raw data—leave your org when using external vector stores, ensuring compliance with data protection requirements while delivering enhanced AI capabilities.