As AI-driven reports and summaries become standard in enterprise software, we ve noticed a massive bottleneck that dev teams face: accuracy auditing.
When an LLM summarizes a business report containing financial metrics, user stats, or KPI numbers, verifying that those numbers match your structured databases is a tedious, manual process.
We built Datamagics.ai to automate this using isolated query sandboxes that compare unstructured report claims against live SQL connections and CSVs simultaneously.
Datamagics.ai is a unified visual workspace to clean, ingest, and validate data for AI applications. Build node-based RAG pipelines into Pinecone and Qdrant in a drag-and-drop canvas. Automatically audit unstructured report claims against live SQL databases and datasets simultaneously in secure, isolated sandboxes. Create repeatable data-cleaning recipes to auto-fix formatting anomalies, and monitor real-time ML observability drift metrics. Zero code required.
Datamagics: High-performance data infrastructure for the AI age. Process 20GB+ datasets via an intelligent streaming engine—the bridge between raw data and production intelligence.
Core Capabilities: ⚡ Neural AI: Audits & transforms inconsistent data with extreme accuracy. 🔄 Logic Cloning: Define complex logic once & replay across streams instantly. 🛡️ Secure Sandbox: AI logic executes in isolated VM environments. 📊 Interactive Intelligence: Natural language queries for live KPIs.
