Gencore AI for G Suite Gmail

Gencore AI allows organizations to quickly and safely build enterprise-grade generative AI (GenAI) systems, AI copilots, and intelligent agents. It speeds up GenAI adoption by simplifying the creation of AI pipelines that combine both unstructured and structured data from proprietary enterprise sources across hundreds of different systems and applications.

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

Core Capabilities:

1. Build Secure Enterprise AI Copilots: Assemble AI copilots and knowledge systems from multiple data sources in minutes, with built-in enterprise controls, usage monitoring, and full provenance tracking.

2. Safely Sync Data to Vector Databases: Ingest and synchronize enterprise data at scale. Generate custom embeddings with metadata for vector databases to prepare data for LLM use.

3. Curate and Sanitize Training Data: Collect, clean, and sanitize high-quality datasets for AI model training and fine-tuning.

4. Protect AI Interactions: The LLM Firewall monitors natural language interactions, safeguarding prompts, responses, and data retrievals.

Key Features:

1. Enterprise-Wide Data Connectivity: Safely connect to hundreds of native data sources, supporting both unstructured and structured data across SaaS, on-premises, public, and cloud environments.

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

3. Full AI System Provenance: Track all AI system activities, including data usage, individual files, users, models, and endpoints.

Loading Your G Suite Gmail Data for GenAI Pipelines:

1. Choose G Suite Gmail as your source.

2. Select the data system, bucket, or relevant attribute.

3. Define the scope for Gmail data.

4. Optionally, apply filters such as:

   • Object Prefix (text or regex)

   • Object Name (regex)

   • Object Tags (key:value)

   • Extension Category

   • Extensions

   • Object Size

   • Last Modified date

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