Gencore AI for Asana Enterprise

Gencore AI allows businesses to quickly and securely create enterprise-grade generative AI (GenAI) systems, AI copilots, and agents. It streamlines GenAI adoption by enabling the construction of pipelines that combine structured and unstructured data from proprietary enterprise sources across hundreds of systems and applications.

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

Core Capabilities:

1. Create Secure Enterprise AI Copilots: Build AI copilots and knowledge systems by integrating data from multiple sources in minutes. Includes automatic enterprise controls, AI usage monitoring, and full data provenance.

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

3. Prepare and Sanitize Data for Training: Easily collect, cleanse, and refine high-quality datasets for AI model training and fine-tuning.

4. Protect AI Interactions: The LLM Firewall monitors conversations, safeguarding prompts, responses, and data retrievals, preventing sensitive data leaks and malicious instructions.

Key Features:

• Enterprise-Wide Data Connectivity: Ingest data securely via hundreds of native connectors across SaaS, on-premises, public, and hybrid clouds, enabling a wide range of AI applications.

• Inline Pipeline Controls: Protect AI operations with layers like data sanitization before model use, LLM firewalls for policy-compliant interactions, and continuous compliance monitoring (NIST AI RMF, EU AI Act, etc.).

• Full AI System Visibility: Track complete AI system usage, from every file and user to all AI models and endpoints.

Loading Your Asana Enterprise Data for GenAI Pipelines:

1. Choose Asana Enterprise as the data source.

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

3. Define the scope of Asana Enterprise data.

4. Optionally filter by:

   • Object Prefix or Regex

   • Object Name or Tags

   • Extension Category or Text

   • Object Size

   • Last Modified Date

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