FINANCIAL INTELLIGENCE ENGINE

    See What Reported Numbers
    Won't Tell You

    Machine-driven accounting adjustment analysis. Screen thousands of companies, trace every figure to its source, and uncover the gaps between reported and adjusted reality.

    4.000+
    Data Points per Filing
    250+
    Risk and Adjustment Factors
    4+
    Output Formats
    100%
    Source Traceable

    THE ARCHITECTURE

    Not Just AI. A Machine.

    We didn't bolt AI onto a spreadsheet. We designed a systematic analysis engine where every step is conditional, validated, and traceable.

    01

    Conditional Factor Validation

    Every data point passes through multi-layered conditional checks. If revenue recognition changes, the machine flags dependent adjustments across the entire statement.

    02

    Narrow Search Frameworks

    Purpose-built analysis frameworks for specific risks — related party exposure, lease adjustments, IFRS reconciliations, and 250+ more risk vectors.

    03

    Source Traceability

    Every adjusted figure links directly back to its source filing. No black boxes — every calculation is transparent, auditable, and reproducible.

    04

    Pre-Analyzed Output

    Figures arrive pre-calculated with comparability adjustments applied. Peer groups normalized. Ratios computed. Ready for your decision.

    CAPABILITIES

    Everything You Need to Decode Financials

    Deep Screening

    Deterministic screening on any combination of 4,000+ data points across the universe of public companies.

    Peer Analysis

    Comparability layer normalizes accounting policies across peers. See how numbers stack up when everyone plays by the same rules.

    4,000+ Data Points

    Per company, per period — stored in structured JSON, human-readable format & excel.

    Full REST API

    Documents, screening, analysis, and reports. Pull any data point, any adjustment, any company — programmatically.

    Data Architecture

    Structured Down to Every Field

    Every analysis produces a fully structured JSON output — 4,000+ data points per company, per period. This allows deterministic data extraction, computation, and more.

    pension_funded_status_output.json
    47 fields
    {
    "current_period":"FY 2025"
    "current_period_minus_1":"FY 2024"
    "current_period_minus_2":"FY 2023"
    "current_period_minus_3":"FY 2022"
    }
    "units":"millions"
    }
    "reasoning":"Plan assets declined 5.3% while PBO grew 6.5%, widening the funding gap by $109.3M..."
    }
    Output format: JSON → MD / HTML / PDF / ExcelClick any node to expand ↕

    Ready to See Behind the Numbers?

    Submit a Company for a trial analysis or schedule a call to see our platform in action.