Innovative AI Agents

The first fully autonomous Enterprise Data Scientist

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Time Series Analysis

Our AI Agent autonomously uncovers trends, patterns, and seasonality in data, delivering natural-language forecasts, performance monitoring, and anomaly detection – fully automated and future-ready.

Distribution Analysis

The AI Agent instantly reveals frequencies, variability, and outliers, translating raw distributions into clear, expert-level insights. Patterns emerge automatically, empowering faster, smarter decisions.

Correlation Analysis

By analyzing correlations and associations between variables, the AI Agent uncovers hidden drivers and connections. Everything is explained in natural language – automatic, actionable, and transformative.

Meet our Experts

Thomas Koss, Snowflake Inc.

Mag. Magdalena Eder

Christoph Spöck MEd MA MA

Business Insights with AAAxAgents

Detailed EDA Interpretation

  • Only the POSTAL_CODE column contains missing values (41,296 entries)

  • This represents approximately 80.5% of all records, which is significant

  • For classification tasks, this feature may need to be dropped or imputed

  • Sales range: 0.44 – 22,638.48
  • Mean sales: 246.49 (high standard deviation: 487.57)

  • Highly skewed distribution (75% of sales below $251.05)

  • Potential outliers in upper range require investigation

  • Quantity: 1 – 14 units per order

  • Average quantity: 3.48 items (std: 2.28)

  • Discounts: 0% – 85%

  • Median discount: 0%, indicating many orders have no discount

  • Negative profits observed (min: -6,599.98)

  • Maximum profit: 8,399.98

  • Shipping cost range: 1.00 – 933.57

  • Mean shipping cost: 26.48

Strong Positive Correlations

  1. Sales & Shipping Cost (ρ=0.909, r=0.768)

    • Higher value orders incur higher shipping costs

  2. Profit & Sales (ρ=0.490, r=0.485)

    • Higher sales generally lead to higher profits

Notable Negative Correlations

  1. Discount & Profit (ρ=-0.596, r=-0.316)

    • Higher discounts reduce profitability

  2. Discount & Sales (ρ=-0.100, r=-0.087)

    • Minimal impact of discounts on sales volume

Order Priority

  • Medium priority: 57.39%

  • High priority: 30.22%

  • Critical: 7.67%, Low: 4.73%

Product Categories

  • Office Supplies: 61%

  • Technology: ~19%

  • Furniture: ~20%

Sub-Categories

  • Top 5 sub-categories = ~45% of orders

  • Binders: 11.98%, Storage: 9.84%

  • Other sub-categories evenly distributed

  • Address missing POSTAL_CODE values

  • Feature engineer based on strong correlations

  • Manage class imbalance in categorical variables

  • Handle outliers in sales and profit

  • Normalize numerical features due to varying scales

Our Solutions

We optimize AI models tailored to your domain, ensuring solutions that align perfectly with your business needs and drive measurable impact.

“What is cool actually is startups - like Benjamin's startup can really scale actually, so the good thing is if you have an idea, you just take ecosystems like Snowflake and there's no concern about scaling servers and hardware anymore.”

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