A fully automated analysis and reporting system. Upload your data, get interactive reports with charts, correlations, and AI-generated insights — built on validated R statistical software, not AI-generated code.
Every analysis runs on validated R scripts — the same statistical language used in academia, pharma, and finance. Results are deterministic and reproducible. AI provides the insights and interpretation, not the methodology.
Save reports over time. Search across analyses. Cross-check findings. Use AI assistance for deeper exploration — or connect your data sources for automated recurring reports.
Every analysis produces a full report — not a JSON blob. Choose how you want to explore, share, or present your findings.
1 MCP report = 10 Julius prompts. Every report includes 6-16 interactive cards, AI insights, diagnostics, and exportable PDF.
Other tools make you prompt for each chart. We deliver the whole analysis in one click.
Upload your CSV. Get a real statistical report with interactive charts and AI insights.
Each card in your report gets its own AI interpretation. Not generic summaries — specific observations about your data, statistical significance calls, and actionable recommendations.
AI reads each chart and table, explains what matters and what to act on.
One-page TLDR for stakeholders who won't read the full report.
Citable R code, assumption checks, what the test actually proves.
TV spend shows the strongest ROI at $4.20 per dollar, significantly outperforming Radio ($2.15) and Newspaper ($0.87). The model explains 89.7% of variance (R² = 0.897), suggesting marketing budget reallocation from Newspaper to TV could increase revenue by approximately 12-18%.
Every result gets embedded into a high-dimensional vector space. Related insights cluster together automatically.
Search by meaning, not keywords. The more you analyze, the more connections you find.
Ask a question, pick a tool, or let the agent decide. The result is a full report with charts, tables, and AI insights.
The result is converted to a 768-dimension vector and placed in a shared semantic space alongside every other analysis.
Ask “What do we know about churn?” and the system retrieves the most semantically relevant results — across all datasets, tools, and time.
Each dot is a past analysis. Proximity = similarity in meaning.
A query finds the nearest neighbors — regardless of when they ran or what tool was used.
The more you analyze, the more connections you find.
Every report has feedback buttons on each slide. Flag an issue and we'll send you an updated version. Still not satisfied? Credits back, no questions asked.
Every analysis you run becomes searchable knowledge. The more you use it, the smarter your organization gets.