Hanalyzer.ai

Hanalyzer.ai is a governed data analysis platform that connects files or warehouses, runs in-browser machine learning and statistical tests, and routes queries across frontier models. Its trust layer masks sensitive fields, scopes rows, audits access and issues verification certificates for every number.

Hanalyzer.ai is a data analysis platform built around a simple premise: AI should not touch enterprise data without guardrails, and every figure it produces should be provable. The product connects to files or warehouses, runs statistical and machine learning work inside the browser where possible, and wraps the output in policy enforcement and verification. The Hanalyzer Agent acts as the orchestration layer, routing questions to GPT-4o, Claude, Gemini or other frontier models depending on the task, while a separate trust layer masks protected health information, scopes rows, caps queries and issues a tamper-evident certificate for each result. Practically, the platform covers three jobs. Ingestion handles CSV, Excel, PDF, JSON, SQL dumps and API feeds with automatic schema inference. The ML Lab and Data Engineering Lab then run clustering, classification, time series and regression work (k-means++, Random Forest, PCA, ARIMA, Prophet-style models, LSTM forecasting with confidence bands) through TensorFlow.js and WebAssembly, so those computations stay client-side. A SQL workbench, schema profiler, transform pipeline and deduplication tools round out the cleaning side without requiring infrastructure. The natural audience is analysts and data teams in regulated environments: healthcare, finance, public sector, or any group whose IT department has blocked consumer AI tools. Hanalyzer positions itself as the middle layer between a warehouse and whichever AI model a team wants to use, including through an MCP server that exposes data as a live endpoint. White-label branding and client portals suggest agencies and resellers are also in scope. Among general analytics chatbots, Hanalyzer's differentiator is the governance and verification story rather than raw model access. It also pushes heavy compute to the browser, which helps with privacy but shapes what the product can realistically do at very large scale. Teams that mainly want quick chart generation will find more than they need here. Teams that need an auditable record of what an AI did to sensitive data will find the feature set pointed directly at that problem.