AI-powered automation for your data platform. Three modules, each solving a different challenge. Add what you need.
Each module is a separate add-on. Start with what you need, add more as you grow.
Automate data documentation. Describe tables, detect PII, classify domains.
Find and query data with natural language. No SQL required.
Understand quality issues. Create rules in plain English.
Automate 90% of catalog documentation
Generate business-friendly descriptions by analyzing table names, schema context, and column structure.
Intelligent descriptions using context, naming patterns, and data type inference.
Detect 15+ PII types and PHI for healthcare. Confidence scores with reasoning.
Auto-classify into business domains with subdomain categorization.
Semantic matching to existing glossary terms and new term suggestions.
AI-generated tags for automatic data organization and discovery.
Enrich entire schemas in background with progress monitoring.
Auto-approve high-confidence suggestions. Bulk operations with filtering.
Natural language data discovery
Find data assets using natural language. Search by meaning, not just keywords.
Query your data in plain English. Get SQL generated automatically with explanations.
"Show me all customers who signed up last month and haven't made a purchase"
Generated SQL:
SELECT * FROM customers c
WHERE c.created_at >= DATE_TRUNC('month', CURRENT_DATE - INTERVAL '1 month')
AND c.id NOT IN (SELECT customer_id FROM orders)Two products for different needs
When issues arise, understand why. AI-powered explanations and root cause analysis.
Understand why data quality checks failed with AI-generated explanations.
5-Whys root cause analysis with Bayesian reasoning to trace failures.
Executive-ready summaries of data quality issues prioritized by impact.
Create quality checks in plain English. AI-powered recommendations from profiling.
Create data quality rules in plain English. AI converts to executable checks.
Get AI suggestions for new quality rules based on profiling statistics.
Quality Pro includes both Diagnostics and Copilot at a bundled rate.
You write:
"Email addresses must be valid and unique. Customer age should be between 18 and 120."
NexionMind creates:
email ~ '^[^@]+@[^@]+\.[^@]+$'email IS UNIQUEage BETWEEN 18 AND 120Use models from your own cloud subscription or run locally. Your data never leaves your infrastructure.
GPT-4, Azure OpenAI models in your Azure subscription
Claude, Llama, and other models in your AWS account
Direct access to GPT-4, GPT-3.5, and embedding models
Run models locally in your datacenter. Full privacy control.
Built for regulated industries. Your sensitive data never reaches the AI.
Sample data is automatically masked before LLM analysis. Your sensitive data never reaches the AI.
Use Azure OpenAI, AWS Bedrock, OpenAI, or Ollama. No cloud dependency required.
Every LLM call logged with token usage, cost tracking, and user attribution.
Each module is priced separately. Start with Catalog AI, add more as you need.