Transform Your Data into Expert Enterprise AI Agents
Advanced Ingestion & Retrieval
built for Enterprises that need scale and value privacy
Enterprise-grade support for integrating over 100 data sources such as S3, Snowflake, SharePoint, and Slack. Scale seamlessly with robust connector customization- including metadata extraction, file handling, and
post-processing tailored for enterprise needs.
Achieve precise parsing for complex enterprise documents, including tables, images, formulas, and slides. Use multi-modal pipelines to extract visual data, OCR readers for text recognition, and LLMs for validation. Customize parsers for specific file types to meet unique needs.
Ensure full data privacy with locally deployed models and native support for vector stores. Configure pipelines for chunking, transforming, and embedding data. Gain real-time insights into the ingestion process with comprehensive tracing and observability tools.
Leverage advanced retrieval mechanisms such as re-ranking, query reconstruction, and custom post-processing for precise results. Use privately deployed LLMs to synthesize responses and customize user prompts for improved relevance.
Custom Pipelines
Experiment, design, and manage tailored pipelines for parsing, ingestion, and retrieval to meet diverse enterprise use case requirements.
Parallel Processing
Accelerate ingestion and retrieval with parallel processing across thousands of files and multiple sources, reducing latency significantly.
Compute Optimization
Optimize resource usage with GPU-powered ingestion for large datasets. Automatically scale down workers during idle periods to ensure efficiency.
Semantic Cache
Boost response speed and user confidence by caching frequently asked similar questions for immediate, contextually relevant responses.
Tracing
Ensure data integrity and system auditability with end-to-end tracing for both ingestion and retrieval workflows.
Auto Sync
Keep RAG applications current by scheduling automated data synchronization, ensuring your AI solutions always deliver the most relevant information.
RAG enhances AI systems by combining retrieval mechanisms with generative capabilities. It delivers accurate, context-rich responses by integrating enterprise data directly into the AI pipeline.
The DkubeX Advanced RAG module supports parallel processing and customizable pipelines for ingesting large datasets efficiently while ensuring full data privacy and traceability.
Yes, it integrates seamlessly with CRMs, ERPs, and other systems using configurable APIs, ensuring smooth deployment into your workflows.
Data is processed within your on-premises or private cloud environment using locally deployed models, guaranteeing that sensitive information remains secure.
The module includes re-ranking, query reconstruction, and custom post-processing, combined with private LLMs for response synthesis tailored to enterprise needs.
Automated sync schedules and periodic data refresh pipelines ensure your applications always work with the most current information.
Yes, it supports multi-modal pipelines, advanced OCR readers, and customizable parsers to handle diverse and complex data formats effectively.
It employs GPU-powered ingestion, automatic scaling, and parallel processing to ensure efficiency without compromising performance, even during peak usage.
Yes, semantic caching reduces latency by storing frequently asked questions, ensuring quick and accurate responses for end-users.
The module provides complete tracing and auditability for ingestion and retrieval workflows, enabling full transparency and system integrity.