Gencore AI for Azure Blob Storage

Gencore AI enables businesses to easily and quickly build safe, enterprise-grade generative AI (GenAI) systems, copilots and AI agents. It accelerates GenAI adoption in the enterprise by making it easy to build unstructured and structured data + AI pipelines utilizing proprietary enterprise data across hundreds of diverse data systems and applications.

You can utilize any foundation model available in Google Cloud such as Vertex AI, Gemini, and PaLM 2, including third-party models such as Anthropic, Claude, Meta Llama 2, Mistral etc.

Key capabilities include:

1. Build Safe Enterprise AI Copilots: Create AI copilots and knowledge systems by combining data from multiple systems in minutes. Automatic enterprise controls, AI usage monitoring, and full provenance tracking.

2. Safely Sync Data to Vector Databases: Securely ingest and sync data at scale from various systems. Create custom embeddings with metadata for vector databases, preparing enterprise data for LLM usage.

3. Curate and Sanitize Data for Model Training: Easily assemble, cleanse, and sanitize high-quality datasets for AI model training and tuning.

4. Protect AI Interactions: The natural language conversation-aware LLM Firewall, protects user prompts, responses and data retrievals in AI systems.

Key Features:

1. Seamless Data Connectivity Across Your Enterprise: Safely ingest data through hundreds of native connectors while enabling diverse enterprise AI applications that leverage both unstructured and structured data across multiple environments - SaaS, on-premise, public and data clouds.

2. Inline Controls Across AI Pipeline: Protect AI operations through comprehensive security layers, including data sanitization before AI model consumption, LLM firewalls to ensure policy-compliant interactions, and continuous compliance monitoring (NIST AI RMF, EU AI Act etc.).

3. Complete AI System Provenance: Gain full visibility into the entire AI system, including data and AI usage — down to the level of each file, individual user, and all AI models and usage endpoints.

For Support please reach out to https://securiti.ai/contact-us/

How do you load your Azure Blob Storage data in minutes to build your GenAI pipeline?

      1.SelectAzure Blob Storageas the Source.
      2.Select the data system, bucket, or other attribute forAzure Blob Storage.
      3.Define the scope relevant toAzure Blob Storage.
      4.Select optional conditions:
            - Object Prefix: Enter a text or a regex prefix to match.
            - Object Name: The object name based on a regular expression.
            - Object Tags: The object name based on tags as a key:value pair.
            - Object Extension Category: The object based on extension category.
            - Object Extensions: Match the object based on the extension text.
            - Object Size: Match the object based on size.
            - Last Modified: Match the object based on when it was last updated.
      5.When ready, clickSave and Continueto enter the Data Sanitizer stage.