SAFE AI Agents for Enterprise Data
Build domain-specific AI applications by safely integrating proprietary data with any AI model. Customize and deploy agents right on your data with instant access to organizational context.
Agent Development Platform
VectorCat offers a powerful AI development environment while supporting familiar tools like Python and its libraries. All agents inherit the user's SAFE workspace — ensuring security, auditability and governance are part of the architecture. Our fleet of data management assistants was built on top of it.
Agents as Code
Define agents entirely in code for easy versioning, change management and collaboration. Includes a built-in testing framework supporting unit, integration and regression tests — ensuring agent quality at every stage of development.
Workflow Visualization
Automatically visualizes complex DAG-based flows for both developers and business users, making it easy to test, validate and ensure the quality of each step — enabling enterprise-grade agent implementations.
Distributed Execution
Leverages a distributed execution mechanism where client machines control the flow, reducing server infrastructure costs and complexity while improving responsiveness and interactivity in agentic workflows. It's a "write once — run everywhere" framework, which runs both in backend sandboxes and in the browser via WebAssembly.
Model-Agnostic Approach
Supports seamless integration with any model from any provider, enabling rapid performance testing and effortless upgrades when better models become available.
Data Governance Agents
These agents work continuously in the background to protect, organize and enrich your data as it flows through the platform.
Data Protection Agent
Automated compliance enforcement
Automatically enforces data protection policies across your entire data landscape.
- Scan — Multi-stage SPI detection: Safe Harbor, GDPR, GxP, quasi-identifiers, composite identifiers and custom policies
- Quarantine — Immediately block any detected SPI or confidential data from unauthorized access
- Govern — Review with stewards from DPO/Compliance to accept policy and quarantine decisions
Data Stewardship Agent
Domain understanding & organization
Helps governance teams discover structure, create ontologies and organize data assets semantically.
- Discover — Assist your governance team in discovering structure and creating an ontology
- Map — Map ontologies to ground truth. Work with semantic assets, not files
- Describe — Generate descriptions for discovered assets. Collaborate and validate with domain stewards
Data Annotation Agent
Metadata enrichment & transformation
Automatically enriches data with business metadata and transforms between structured and unstructured formats.
- Enrich — Assign business metadata automatically at any level of granularity
- Transform — Convert unstructured data to structured and vice-versa
- Compose — Prepare domain-specific knowledge graphs for downstream consumption
User-Facing Agents
Once data is governed and enriched, these agents provide direct value to scientists, analysts and domain experts.
AI Research Assistant
Searches organizational knowledge to answer domain-specific questions
- Search — Runs autonomous searches across organizational resources to find relevant documents and data assets
- Summarize — Provides summaries with references to all findings, grounded in source material
- Reason — Answers questions like "what experiments have we performed with compound N?"
Data Extraction Agent
Extracts and harmonizes data from unstructured sources into consistent formats
- Extract — Pulls data from structured or unstructured documents (lab notes, protocols, log files) into user-defined formats
- Normalize — Converts languages, units (2 mL → 2000 µL), and infers information from context
- Validate — Outputs can be manually corrected by the user before validation. Reduces curation time from hours to minutes
Documentation Agent
Generates and maintains documentation from data asset context
- Generate — Creates comprehensive documentation for data pipelines, experimental protocols and analytical workflows
- Contextualize — Understands relationships between assets within the same project or workflow
- Maintain — Keeps documentation consistent across teams, for both wet lab scientists and computational teams
Ready to try our agents or develop yours?
See how VectorCat's agent framework can accelerate your data workflows.