Gencore AI for Microsoft Teams

Gencore AI helps organizations quickly and safely build enterprise-grade generative AI (GenAI) systems, AI copilots, and intelligent agents. It simplifies GenAI adoption by enabling fast creation of AI pipelines that combine unstructured and structured data from proprietary enterprise sources across hundreds of systems and applications.

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

Core Capabilities:

1. Build Secure Enterprise AI Copilots: Combine data from multiple sources to create AI copilots and knowledge systems in minutes, with automatic enterprise controls, usage monitoring, and full provenance tracking.

2. Sync Data Safely to Vector Databases: Ingest and sync enterprise data at scale, creating custom embeddings with metadata for LLM usage.

3. Curate & Sanitize Data for Model Training: Easily assemble, clean, and prepare high-quality datasets for AI training and tuning.

4. Protect AI Interactions: The conversation-aware LLM Firewall secures prompts, responses, and data retrievals.

Key Features:

• Seamless Enterprise Data Connectivity: Connect to hundreds of native data sources across SaaS, on-premise, and cloud environments, supporting both structured and unstructured data.

• Inline AI Pipeline Controls: Ensure compliance with data sanitization, LLM firewalls, and continuous monitoring aligned with standards like NIST AI RMF and EU AI Act.

• Full AI System Provenance: Track every file, user, model, and endpoint usage for complete visibility into AI operations.

Load Microsoft Teams Data for GenAI Pipelines:

1. Choose Microsoft Teams as the Source.

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

3. Define the scope relevant to Teams data.

4. Apply optional filters such as object prefix, name, tags, extensions, size, or last modified date.

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