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.
Powerful Capabilities
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.
Frequently Asked Questions
GPTfy's RAG system maintains enterprise-grade security by processing data entirely within your Salesforce environment. It applies PII-masking rules before content embedding, enforces field-level access via Salesforce permissions, and maintains an immutable audit trail of all retrievals and AI calls. This ensures compliance with data residency requirements and security protocols.
The RAG system supports multiple data sources including Salesforce Knowledge articles, custom objects, attached files (PDFs, documents), external objects, and website content. All integrations are managed through a declarative interface, making it easy to set up and maintain without requiring complex coding or external infrastructure.
Our hybrid semantic retrieval combines vector search with keyword matching to achieve optimal balance between recall and precision. This approach reduces AI hallucinations while ensuring consistent, context-aware results. The system achieves 85% factual accuracy by intelligently retrieving and presenting the most relevant content chunks based on user queries or record context.
Why Choose Retrieval-Augmented Generation
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.
Transform AI Accuracy: Contextual Knowledge, Factual Responses
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 and show how to achieve 85% factual accuracy with hybrid semantic retrieval.