Gencore AI for Dropbox

Gencore AI helps organizations quickly and safely develop enterprise-grade generative AI (GenAI) systems, copilots, and AI agents. It streamlines GenAI adoption by enabling the creation of AI pipelines that integrate both structured and unstructured proprietary data across hundreds of systems and applications.

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

Core Capabilities:

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

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

3. Curate and Clean Data for Model Training: Quickly assemble, sanitize, and refine high-quality datasets for AI training and tuning.

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

Key Features:

1. Enterprise-Wide Data Connectivity: Securely ingest data via hundreds of native connectors, enabling AI applications across SaaS, on-premises, public, and hybrid cloud environments.

2. Inline Security Controls: Ensure AI operations remain policy-compliant with data sanitization, LLM firewalls, and continuous compliance monitoring (e.g., NIST AI RMF, EU AI Act).

3. Complete AI System Visibility: Track every data file, user, AI model, and usage endpoint for full transparency.

How to Load Dropbox Data Quickly for GenAI Pipelines:

1. Choose Dropbox as the source.

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

3. Define the scope for Dropbox data.

4. Apply optional filters: object prefix, name, tags, extension category, specific extensions, size, or last modified date.

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