Gencore AI for Slack Pro

Gencore AI helps organizations rapidly build secure, enterprise-ready generative AI (GenAI) systems, copilots, and AI agents. It accelerates enterprise GenAI adoption by simplifying the creation of AI pipelines that combine both unstructured and structured data, powered by proprietary enterprise data from hundreds of diverse systems and applications.

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

Key Capabilities

1. Build Secure Enterprise AI Copilots
Quickly create AI copilots and knowledge systems by unifying data from multiple sources. Built-in enterprise controls provide AI usage monitoring and complete end-to-end provenance tracking.

2. Securely Sync Data to Vector Databases
Ingest and synchronize data at scale from a wide range of systems. Generate custom embeddings enriched with metadata to prepare enterprise data for LLM-powered applications.

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

4. Protect AI Interactions
A natural language–aware LLM Firewall safeguards user prompts, model responses, and data retrieval across AI systems.

Key Features

1. Seamless Enterprise Data Connectivity
Safely ingest data through hundreds of native connectors, enabling AI applications that span unstructured and structured data across SaaS, on-premises, public cloud, and data cloud environments.

2. Inline Security and Compliance Controls
Protect AI workflows with layered security, including pre-model data sanitization, LLM firewalls for policy enforcement, and continuous compliance monitoring aligned with frameworks such as NIST AI RMF and the EU AI Act.

3. End-to-End AI System Visibility
Gain comprehensive visibility into data usage and AI operations—down to individual files, users, models, and inference endpoints.

For support, please contact: https://securiti.ai/contact-us/

How to Load Your Slack Pro Data in Minutes

1. Select Slack Pro as the data source.

2. Choose the relevant data system, workspace, or attributes.

3. Define the desired data scope for Slack Pro.

4. Apply optional filters:

   • Object prefix (text or regex)

   • Object name (regex-based)

   • Object tags (key:value)

   • Object extension category

   • Object extensions

   • Object size

   • Last modified date

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