Data Vectorization and Ingestion 

Convert unstructured files into AI-ready formats, syncing to vector databases

Data Connection & Curation

Connect and curate diverse data sources

• Securely integrate data from on-premise, cloud, and SaaS platforms
• Define data scope at ingestion, excluding content for quality, legal and ethical compliance
• Use advanced document classifiers and user entitlements to direct data to appropriate AI pipelines

Data Extraction & Normalization

Extract and parse information from complex files

• Process hundreds of file formats, including Word, PDF, and multimedia
• Convert unstructured data into coherent datasets
• Maintain context and relationships within complex documents to enhance vector DB comprehension of extracted data

Data Sanitization

Auto-clean data to comply with enterprise policies

• Apply dynamic masking, redaction, or anonymization to sensitive information on the fly
• Customize data sanitization based on enterprise-specific policies
• Transform data into a clean and compliant format suitable for AI pipeline use

Data Vectorization

Generate and load custom embeddings

• Create embeddings using various models for AI pipeline applications
• Load embeddings into preferred vector databases
• Preserve permissions and associated metadata during ingestion

Retrieval Firewall

Monitor and control data retrieval in real-time

• Safeguard sensitive information during the RAG process
• Ensure retrieved data is relevant and topical
• Customize firewall rules based on specific security requirements