A clearer picture.
Before you begin.

Opscien is an AI analyst and data scientist for business leaders, built by Good at Numbers. Bring your data, ask a question in plain language, and inspect the analysis behind the answer. You can explore forecasts and what-if scenarios, create reports and small applications, and review proposed decisions with your team. Explore the demo.

Business owners, executives, finance leaders, and operations teams who need to understand what is changing and decide what to do next. Opscien is built for businesses across industries. Your data and the definitions you approve give it the context for your organization.

Opscien connects a question to analytical tools and your reviewed data. It plans the work, runs the analysis, and checks the figures in its answer against the results. Definitions, reports, and decision records stay in the workspace so your team can inspect and reuse the work.

People set the goals and remain responsible for business decisions. Opscien helps investigate a question and compare options. An administrator or workspace owner can approve, reject, or defer a proposed decision; approving it and recording that an action happened are separate steps.

You can upload CSV, Excel, and Parquet files, as well as PDFs and scanned images. Database connections support PostgreSQL, MySQL, and SQL Server. Opscien prepares the data for review; your team checks its meaning before publishing it for analysis.

“Revenue” might mean money invoiced, money received, or sales after refunds. Opscien proposes descriptions of your tables and columns; you can correct and approve them. Shared definitions help a question, a forecast, and a report use the same measure.

You can ask questions and describe reports or small applications in plain language. You do not need to write a query to ask a question. Your team still needs to review the data and definitions, and a database connection may need help from whoever manages that system.

You can forecast a measure across your workspace, such as total revenue or demand, when enough suitable history is available. Opscien compares forecasting methods and shows uncertainty ranges when the selected model supports them. Store-by-store or item-by-item forecasts are not currently supported. A forecast is an estimate, not a guarantee.

Yes, where the workspace has evidence for how the relevant factors relate. For example, estimating the effect of a price change needs evidence about how demand responds. Opscien can refuse a study when that evidence is missing. A scenario describes what follows under its assumptions; it does not prove that an action will cause that outcome.

Start with the source data, the definitions, and the calculation. Opscien checks figures against results from the analysis and marks figures it cannot support as withheld. Those checks do not make every answer correct: the input data, assumptions, or chosen method may still need correction. Review the evidence before acting. See the controls behind an answer.

You can create reports to review and publish in the workspace, or describe a small application built around your published data. These give your team a reusable way to read a finding, inspect a chart, or work with the data.

The demo opens Business workspace. Start at Home, ask prepared questions, compare stores, filter the Daily store performance application, and read its complete report. The same figures are shared across the screens. It starts in light mode, with a dark theme available. An optional guided tour helps you explore the application, report, scenarios and external intelligence. All interactions run locally without live AI analysis or business actions. Inspect the dataset.

Workspace roles determine who can review decisions and change spending limits. The product records decision reviews in an audit log and checks requests to the AI against the workspace budget. Before an evaluation, we will discuss your access, deployment, and data-handling requirements with you.

We do not publish a price list on this website. Tell us what you want to evaluate, the data involved, and who would use it. We can discuss the scope and commercial terms with you before you make a commitment.

Bring one question you want to answer and an outline of the data you would use. Customers, pilot partners, early adopters, and investors can all use the same contact form and tell us what brings them here. Talk to the team to discuss fit, a sample-data evaluation, or a partnership.