I built Acutize around a problem I kept seeing: working with business data often means jumping between spreadsheets, notebooks, scripts, visualization tools, and reporting software. For people who don’t write code every day, even getting from a messy file to a useful answer can become a slow, technical process. Acutize brings that workflow into one browser-based workspace. You can upload CSV, Excel, JSON, or Parquet files, inspect data quality, clean common issues, generate business insights, forecast metrics, compare ML models, and export datasets, reports, or training scripts without building the pipeline yourself. The product initially focused on data cleaning and analysis. As it evolved, I realized that cleaning was only the beginning. Users also needed help understanding what the data meant, deciding what to do next, exploring predictive models, and producing something they could share or continue working with. That led to the guided, end-to-end workflow Acutize offers today. There’s a free plan with enough starter credits to explore the main workflow, no credit card required. I’d especially love your feedback on: - Which part of your data workflow consumes the most time? - What would make Acutize useful enough to become part of your regular workflow? - Which file formats, analyses, or exports should I prioritize next? Thanks for checking out Acutize. I’ll be here throughout the launch to answer questions and learn from your feedback!

Acutize

Clean, analyze, forecast, and model data—without code

Clean, analyze, forecast, and model data—without code