Gencore AI for Azure Data Lake Storage (ADLS) Gen2

Gencore AI allows organizations to rapidly and securely develop enterprise-grade generative AI (GenAI) systems, AI copilots, and intelligent agents. It streamlines GenAI adoption by enabling the creation of pipelines that integrate both structured and unstructured enterprise data from hundreds of diverse systems and applications.

You can leverage any foundational model on Google Cloud, including Vertex AI, Gemini, and PaLM 2, as well as third-party models such as Anthropic, Claude, Meta Llama 2, and Mistral.

Core Capabilities:

1. Develop Secure Enterprise AI Copilots: Build AI copilots and knowledge systems by consolidating data from multiple sources within minutes. Features include automatic enterprise controls, AI usage monitoring, and full system provenance tracking.

2. Safely Sync Data to Vector Databases: Ingest and synchronize data securely at scale. Generate custom embeddings with metadata for vector databases, making enterprise data ready for LLM applications.

3. Prepare and Clean Data for Model Training: Assemble, sanitize, and curate high-quality datasets efficiently for AI training and tuning.

4. Protect AI Interactions: The conversation-aware LLM Firewall safeguards user prompts, AI responses, and data retrievals, ensuring compliance and mitigating risks like prompt injections or data leaks.

Key Features:

1. Enterprise-Wide Data Connectivity: Connect safely to hundreds of native data sources, supporting applications across SaaS, on-premises, and cloud environments with both structured and unstructured data.

2. Inline AI Pipeline Controls: Ensure secure AI operations with pre-model data sanitization, LLM firewalls for policy-compliant interactions, and continuous compliance monitoring (NIST AI RMF, EU AI Act, etc.).

3. Complete AI System Visibility: Gain full insights into AI operations, data usage, and model interactions at the level of individual files, users, and models.

For assistance, visit: Securiti Support

Loading ADLS Gen2 Data into Your GenAI Pipeline in Minutes:

1. Choose ADLS Gen2 as your data source.

2. Select the relevant data system, bucket, or other ADLS Gen2 attributes.

3. Define the scope for your ADLS Gen2 data.

4. (Optional) Set conditions such as:

   • Object Prefix (text or regex)

   • Object Name (regex)

   • Object Tags (key:value)

   • Extension Category or specific Extensions

   • Object Size

   • Last Modified date

5. Click Save and Continue to move to the Data Sanitizer stage.