The Core of Our Intelligence Platform
RAG TECHNOLOGYRetrieval-Augmented Generation combines the power of large language models with real-time access to your business data, creating contextually aware AI that understands your specific domain.
DEMO →How RAG Powers Our AI Builder
Every answer is built from your own data in three steps: ingest, retrieve, then generate.
Document Ingestion & Vectorization
Your business documents, policies, and data are processed with state-of-the-art embedding models, turning the information into vector representations.
Semantic Search & Retrieval
When a query arrives, the RAG architecture searches your data semantically with Pinecone, Weaviate, or ChromaDB, retrieving the most relevant content with sub-100ms latency.
Context-Aware Generation
Retrieved content is injected into prompts for GPT-4, Claude, or custom models, so responses are grounded in your business knowledge and policies.
RAG Architecture Components
Vector Databases
Pinecone, Weaviate, and ChromaDB for scalable similarity search.
Embedding Models
OpenAI Ada-002, Sentence-BERT, and E5 for accurate text embeddings.
Retrieval Engine
Hybrid search combining semantic and keyword matching.
Generation Models
GPT-4, Claude 3, and Llama 2 with secure compute pipelines.
Reduced Hallucinations
RAG grounds AI responses in factual data, reducing false information by up to 90% compared to pure generative models.
Real-time Knowledge
Access live business data without retraining models, so responses are based on the latest information.
Domain Expertise
Specialized knowledge for your industry without expensive model fine-tuning or extensive retraining.
Intelligent Features
Advanced AI capabilities that transform how businesses operate and make decisions.
Smart API Discovery & Chaos Integration
Scans your applications to find integration points with databases and services, then handles mapping and configuration automatically.
Automated Workflow Orchestration
Smart automation of complex business processes, with adaptive decision-making and error handling.
Deep Learning Search
Searches across chats, forms, logs, and business data with role-based access and contextual understanding.
Anomaly Detection
Machine learning-based monitoring that flags unusual patterns in business processes and data flows.
Core Capabilities
The AI Builder serves as the central nervous system, orchestrating intelligent automation across your entire business ecosystem.
Intelligent Processing Hub
Central orchestration powered by advanced LLMs including GPT-4, Claude 3, and Llama 2, enabling seamless communication across all integrated systems.
Multi-Channel Processing (MCP)
A unified processing engine for appointment booking, time tracking, reminders, and employee management through one intelligent interface.
Universal Integration
Native connectors for Salesforce, HubSpot, QuickBooks, HR systems, and legal platforms, with real-time data synchronization.
Enterprise Security
SOC 2 compliant infrastructure with end-to-end encryption, role-based access control, and audit trails.
Technical Architecture
Built on enterprise-grade infrastructure with state-of-the-art AI models and frameworks.
Large Language Models
- GPT-4 with custom injection
- Claude 3.5 Sonnet & Haiku
- Llama 3 with custom injection
- Mistral 7B for domain fine-tuning
Infrastructure
- Microservices & API-first
- Docker containerization
- Auto-scaling architecture
- Multi-region deployment
Frameworks & APIs
- LangChain & LangSmith
- Haystack for RAG
- REST & GraphQL APIs
- Real-time webhooks
Data Processing
- Custom data integration
- Apache Kafka streaming
- Complex knowledge bases
- Real-time data models
Frequently Asked Questions
Get answers to common questions about AI Builder.
AI Builder is LLM Software's platform for creating AI applications grounded in your own business data. It combines retrieval-augmented generation with ready-made connectors and workflows, so teams can build assistants, search tools, and automations that answer from their real documents and systems.
Yes. AI Builder offers visual configuration for data sources, prompts, and workflows, so business users can set up working AI applications without programming. Developers can still extend them through APIs and webhooks when more advanced logic is needed.
AI Builder handles the hard parts of the stack for you: data ingestion, vector search, model selection, and security come built in. Teams connect their systems, choose a model, and configure the workflow, instead of building and maintaining each layer separately.
After launch, AI Builder provides dashboards for usage, response quality, latency, and cost, along with conversation logs and audit trails. Anomaly detection flags unusual behavior, so teams can spot issues early and keep improving their applications.