Gencore AI for ServiceNow Files

Gencore AI helps organizations rapidly build secure, enterprise-ready generative AI systems, copilots, and AI agents. It accelerates GenAI adoption by simplifying the creation of structured and unstructured data pipelines that leverage proprietary enterprise data across hundreds of data sources and applications.

The platform supports 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 combining data from multiple sources. Built-in enterprise controls, usage monitoring, and end-to-end provenance tracking are included by default.

2. Secure Data Synchronization to Vector Databases
   Ingest and synchronize data at scale from diverse systems. Generate custom embeddings with rich metadata to prepare enterprise data for LLM-based applications.

3. Data Curation and Sanitization for Model Training
   Easily assemble, clean, and sanitize high-quality datasets for training and fine-tuning AI models.

4. Protection for AI Interactions
   A conversation-aware LLM Firewall safeguards user prompts, model responses, and data retrievals throughout AI workflows.

Key Features

1. Enterprise-Wide Data Connectivity
   Securely ingest data using 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 every stage of the AI pipeline with data sanitization before model access, policy-enforcing LLM firewalls, and continuous compliance monitoring aligned with standards such as NIST AI RMF and the EU AI Act.

3. End-to-End AI System Provenance
   Gain complete visibility into data and AI usage—down to individual files, users, models, and endpoints—for transparency, governance, and auditability.

Support
For assistance, visit: https://securiti.ai/contact-us/

How to Load ServiceNow Files Data in Minutes for Your GenAI Pipeline

1. Choose ServiceNow Files as the data source.

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

3. Define the appropriate scope for ServiceNow Files.

4. Apply optional filters such as:

   • Object prefix (text or regex)

   • Object name (regex-based)

   • Object tags (key:value pairs)

   • Extension category or specific extensions

   • Object size

   • Last modified date

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