{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_numra","slug":"numra","name":"Numra","type":"product","url":"https://numrahq.com","page_url":"https://unfragile.ai/numra","categories":["automation"],"tags":[],"pricing":{"model":"paid","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_numra__cap_0","uri":"capability://data.processing.analysis.ai.driven.expense.categorization.and.classification","name":"ai-driven expense categorization and classification","description":"Automatically analyzes transaction descriptions, vendor names, and metadata to classify expenses into appropriate accounting categories using machine learning models trained on historical financial data. The system learns from user corrections to improve classification accuracy over time, reducing manual categorization overhead. Integration with accounting systems enables real-time category assignment as transactions are imported.","intents":["Reduce manual time spent categorizing hundreds of monthly transactions across multiple expense types","Ensure consistent expense classification across teams to improve financial reporting accuracy","Automatically route expenses to correct cost centers or departments without manual intervention"],"best_for":["Mid-market accounting teams processing 500+ monthly transactions","Accounting firms managing multiple client expense streams","Finance operations teams seeking to reduce data entry FTEs"],"limitations":["Classification accuracy depends on transaction metadata quality — sparse or non-standard vendor names reduce precision","Requires training period with historical data to establish baseline categorization patterns","May struggle with novel or emerging vendor types not represented in training data","Custom category hierarchies require manual configuration per accounting system"],"requires":["Active accounting system integration (QuickBooks, Xero, NetSuite, or similar)","Minimum 3-6 months of historical transaction data for model training","API credentials for connected accounting platform"],"input_types":["transaction descriptions (text)","vendor names (text)","transaction amounts (numeric)","transaction dates (datetime)","historical categorization labels (structured)"],"output_types":["category assignments (structured)","confidence scores (numeric 0-1)","alternative category suggestions (ranked list)","categorization audit logs (structured)"],"categories":["data-processing-analysis","machine-learning-classification"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_numra__cap_1","uri":"capability://data.processing.analysis.automated.financial.reconciliation.with.anomaly.detection","name":"automated financial reconciliation with anomaly detection","description":"Matches transactions across multiple data sources (bank feeds, credit card statements, accounting ledgers) using fuzzy matching algorithms and transaction fingerprinting to identify discrepancies and reconciliation gaps. The system flags unusual patterns (duplicate transactions, amount mismatches, timing anomalies) using statistical anomaly detection, reducing manual reconciliation review time. Integration with accounting platforms enables automatic posting of reconciled transactions.","intents":["Eliminate manual bank reconciliation processes that consume 10+ hours monthly for mid-size companies","Detect duplicate or fraudulent transactions before they impact financial statements","Identify timing differences and outstanding items without manual line-by-line review"],"best_for":["Finance teams managing 5+ bank accounts or credit cards","Accounting firms reconciling client accounts monthly","Companies with high transaction volume (1000+ monthly transactions)"],"limitations":["Fuzzy matching accuracy degrades with non-standard transaction descriptions or international characters","Requires clean bank feed data — corrupted or incomplete feeds reduce matching confidence","Cannot reconcile transactions with significant time delays (>30 days) without manual intervention","Anomaly detection thresholds require tuning per client to avoid false positives"],"requires":["Active bank feed integration (OFX, API, or CSV import capability)","Accounting system with transaction posting API","Minimum 2-3 months of historical transaction data for baseline establishment"],"input_types":["bank transaction feeds (OFX, CSV, API)","accounting ledger transactions (structured)","transaction metadata (dates, amounts, descriptions)","reconciliation rules (configuration)"],"output_types":["reconciliation matches (structured pairs)","unmatched transaction lists (structured)","anomaly flags with severity scores (structured)","reconciliation reports (PDF, CSV)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_numra__cap_2","uri":"capability://tool.use.integration.seamless.multi.system.accounting.integration.with.data.normalization","name":"seamless multi-system accounting integration with data normalization","description":"Provides standardized API connectors and data transformation pipelines that map disparate accounting systems (QuickBooks, Xero, NetSuite, SAP) to a unified data model, enabling bidirectional sync without custom ETL development. Uses schema-based transformation rules to normalize chart of accounts, transaction formats, and reporting structures across platforms. Handles authentication, rate limiting, and error recovery automatically.","intents":["Connect multiple accounting systems without building custom integration code or hiring integration engineers","Maintain data consistency across legacy and modern accounting platforms during system migrations","Enable real-time data flow between accounting system and downstream analytics or reporting tools"],"best_for":["Companies using multiple accounting systems (e.g., QuickBooks for operations, NetSuite for consolidation)","Accounting firms managing diverse client accounting platforms","Organizations migrating from legacy to modern accounting systems"],"limitations":["Connector availability limited to supported platforms — custom or niche accounting systems require manual API integration","Data normalization rules must be configured per client accounting structure — no one-size-fits-all mapping","Rate limiting on accounting system APIs can cause sync delays during high-volume periods","Bidirectional sync requires careful conflict resolution logic to prevent data corruption"],"requires":["API credentials for each connected accounting system","Network connectivity and firewall rules allowing outbound API calls","Admin access to accounting systems for connector setup and testing"],"input_types":["accounting system API responses (JSON, XML)","chart of accounts mappings (structured)","transaction data (structured)","custom field mappings (configuration)"],"output_types":["normalized transaction data (standardized JSON schema)","sync status reports (structured)","error logs with remediation steps (structured)","data reconciliation reports (CSV, PDF)"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_numra__cap_3","uri":"capability://data.processing.analysis.intelligent.financial.reporting.and.consolidation.automation","name":"intelligent financial reporting and consolidation automation","description":"Automatically aggregates transaction data from multiple sources and generates standardized financial reports (P&L, balance sheet, cash flow) using configurable reporting templates and GAAP/IFRS compliance rules. The system handles multi-entity consolidation, intercompany eliminations, and currency conversions using real-time exchange rates. Reports are generated on-demand or on a scheduled basis with version control and audit trails.","intents":["Generate monthly financial statements without manual data compilation from multiple accounting systems","Consolidate financial data across subsidiaries or business units with automatic intercompany elimination","Ensure financial reports comply with accounting standards (GAAP, IFRS) without manual compliance review"],"best_for":["Multi-entity organizations requiring consolidated financial statements","Accounting firms preparing client financial statements monthly","Companies needing rapid financial close processes (weekly or daily reporting)"],"limitations":["Consolidation logic requires manual configuration for complex intercompany transactions or eliminations","Currency conversion relies on external exchange rate feeds — timing mismatches can cause reconciliation issues","Custom reporting requirements beyond standard templates require manual report design","Audit trail completeness depends on source system transaction logging quality"],"requires":["Integrated accounting systems with complete transaction data","Chart of accounts mapping across all entities","Reporting template configuration (GAAP or IFRS rules)","Exchange rate data feed (manual or API-based)"],"input_types":["transaction data from multiple accounting systems (structured)","chart of accounts (structured)","intercompany transaction mappings (structured)","reporting template definitions (configuration)","exchange rate data (numeric)"],"output_types":["financial statements (PDF, Excel, JSON)","consolidation schedules (structured)","audit trail logs (structured)","variance analysis reports (structured)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_numra__cap_4","uri":"capability://data.processing.analysis.real.time.financial.data.pipeline.with.streaming.ingestion","name":"real-time financial data pipeline with streaming ingestion","description":"Ingests financial transactions from multiple sources (bank feeds, credit cards, accounting systems, payment processors) in real-time or near-real-time using event-driven architecture and message queues. Data is validated, enriched with metadata, and routed to appropriate downstream systems (analytics, reporting, compliance) without manual intervention. Handles backpressure and retry logic automatically.","intents":["Enable real-time visibility into cash position and transaction activity without waiting for daily batch imports","Automatically trigger downstream workflows (alerts, approvals, reconciliation) based on transaction events","Reduce latency between transaction occurrence and financial reporting from hours to minutes"],"best_for":["Organizations requiring real-time cash visibility (treasury, working capital management)","Companies with high-frequency transaction volumes needing immediate processing","Finance teams implementing event-driven automation workflows"],"limitations":["Real-time ingestion requires stable API connectivity — network outages cause data gaps that must be reconciled","Message queue infrastructure adds operational complexity and requires monitoring","Data enrichment latency can introduce delays if external data sources are slow","Streaming architecture requires careful handling of duplicate transactions and out-of-order events"],"requires":["Real-time data source APIs (bank feeds, payment processors with webhooks)","Message queue infrastructure (Kafka, RabbitMQ, or cloud equivalent)","Data validation and enrichment service","Monitoring and alerting for pipeline health"],"input_types":["webhook events (JSON)","API transaction feeds (JSON, XML)","batch imports (CSV, OFX)","enrichment data (structured)"],"output_types":["normalized transaction events (JSON)","enriched transaction data (structured)","pipeline status metrics (numeric)","error and retry logs (structured)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_numra__cap_5","uri":"capability://safety.moderation.compliance.and.audit.trail.management.with.regulatory.reporting","name":"compliance and audit trail management with regulatory reporting","description":"Maintains immutable audit logs of all financial transactions, system changes, and user actions with timestamps, user identification, and change details. Generates compliance reports for regulatory requirements (tax reporting, SOX, GDPR) and enables forensic analysis of financial data changes. Integrates with external compliance frameworks and provides evidence for audits.","intents":["Maintain audit-ready documentation of all financial data changes for external auditors","Generate tax compliance reports (1099, W2, sales tax) automatically without manual compilation","Demonstrate data governance and access controls for regulatory inspections"],"best_for":["Public companies subject to SOX or equivalent audit requirements","Organizations in regulated industries (banking, insurance, healthcare)","Companies undergoing external audits or regulatory inspections"],"limitations":["Audit log storage grows rapidly with transaction volume — requires robust data retention policies","Compliance report generation requires manual configuration per regulatory jurisdiction","Immutable audit logs cannot be modified — errors require compensating transactions","Integration with external compliance frameworks (tax, regulatory) requires ongoing maintenance"],"requires":["Secure audit log storage with encryption and access controls","User authentication and authorization system","Compliance framework definitions (tax rules, regulatory requirements)","External audit and compliance tool integrations"],"input_types":["transaction data (structured)","user actions (events)","system changes (events)","compliance rule definitions (configuration)"],"output_types":["audit logs (immutable structured records)","compliance reports (PDF, CSV)","regulatory filings (structured)","access control reports (structured)"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_numra__cap_6","uri":"capability://planning.reasoning.predictive.cash.flow.forecasting.with.scenario.modeling","name":"predictive cash flow forecasting with scenario modeling","description":"Analyzes historical transaction patterns and applies machine learning models to forecast future cash flows with configurable time horizons (weekly, monthly, quarterly). Enables scenario modeling by adjusting input parameters (revenue growth, expense changes, payment terms) to simulate different business outcomes. Integrates with accounting data to ground forecasts in actual financial position.","intents":["Forecast cash position 3-12 months ahead to plan working capital and financing needs","Model impact of business decisions (pricing changes, expense cuts, expansion) on cash flow","Identify potential cash shortfalls early enough to take corrective action"],"best_for":["Finance teams managing working capital and liquidity planning","Startups and growth companies with volatile cash flows","CFOs presenting financial projections to boards or investors"],"limitations":["Forecast accuracy degrades with limited historical data — requires minimum 12-24 months of transaction history","Seasonal patterns and business cycles require manual adjustment to model parameters","External factors (market conditions, regulatory changes) cannot be automatically incorporated","Scenario modeling requires domain expertise to set realistic parameter ranges"],"requires":["Minimum 12-24 months of historical transaction data","Accounting system integration for real-time cash position","User-configurable forecast parameters (growth rates, payment terms, seasonality)"],"input_types":["historical transaction data (structured)","current cash position (numeric)","forecast parameters (numeric, configuration)","scenario definitions (structured)"],"output_types":["cash flow forecasts (time series)","confidence intervals (numeric ranges)","scenario comparison reports (structured)","variance analysis (structured)"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_numra__cap_7","uri":"capability://automation.workflow.vendor.and.supplier.payment.automation.with.approval.workflows","name":"vendor and supplier payment automation with approval workflows","description":"Automates accounts payable processes by matching invoices to purchase orders and receipts, calculating payment amounts and due dates, and routing payments through configurable approval workflows based on amount thresholds and vendor risk profiles. Integrates with payment processors to execute ACH, wire, or check payments automatically. Tracks payment status and reconciles against bank feeds.","intents":["Reduce manual invoice processing and approval time from days to hours","Ensure vendors are paid on time while maintaining control through approval workflows","Optimize payment timing to improve cash flow without damaging vendor relationships"],"best_for":["Companies processing 100+ invoices monthly","Organizations with complex approval hierarchies or vendor risk management","Finance teams seeking to reduce AP processing costs"],"limitations":["Three-way matching (PO, receipt, invoice) requires clean data — missing or mismatched documents require manual intervention","Approval workflow configuration is client-specific — no standard workflow fits all organizations","Payment processor integration requires separate setup and testing per payment method","Vendor master data quality directly impacts automation success — duplicate or incomplete vendor records cause issues"],"requires":["Integration with accounting system (invoice data)","Integration with procurement system (purchase orders, receipts)","Payment processor API credentials (ACH, wire, check)","Approval workflow configuration and user role definitions"],"input_types":["invoices (PDF, structured data)","purchase orders (structured)","receipts/goods received records (structured)","vendor master data (structured)","approval rules (configuration)"],"output_types":["payment instructions (structured)","approval requests (notifications)","payment confirmations (structured)","reconciliation data (structured)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Active accounting system integration (QuickBooks, Xero, NetSuite, or similar)","Minimum 3-6 months of historical transaction data for model training","API credentials for connected accounting platform","Active bank feed integration (OFX, API, or CSV import capability)","Accounting system with transaction posting API","Minimum 2-3 months of historical transaction data for baseline establishment","API credentials for each connected accounting system","Network connectivity and firewall rules allowing outbound API calls","Admin access to accounting systems for connector setup and testing","Integrated accounting systems with complete transaction data"],"failure_modes":["Classification accuracy depends on transaction metadata quality — sparse or non-standard vendor names reduce precision","Requires training period with historical data to establish baseline categorization patterns","May struggle with novel or emerging vendor types not represented in training data","Custom category hierarchies require manual configuration per accounting system","Fuzzy matching accuracy degrades with non-standard transaction descriptions or international characters","Requires clean bank feed data — corrupted or incomplete feeds reduce matching confidence","Cannot reconcile transactions with significant time delays (>30 days) without manual intervention","Anomaly detection thresholds require tuning per client to avoid false positives","Connector availability limited to supported platforms — custom or niche accounting systems require manual API integration","Data normalization rules must be configured per client accounting structure — no one-size-fits-all mapping","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"ecosystem":0.25,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:31.859Z","last_scraped_at":"2026-04-05T13:23:42.560Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=numra","compare_url":"https://unfragile.ai/compare?artifact=numra"}},"signature":"byEAOCib2keGUSs96vw3EutZwkojyTiiP3s8fFRWjZWSIqa6Tzj4pvNZa/c6uAfRsO4SfMpOOe3bom9qyxufBA==","signedAt":"2026-06-20T15:56:09.081Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/numra","artifact":"https://unfragile.ai/numra","verify":"https://unfragile.ai/api/v1/verify?slug=numra","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}