Spade

What Spade does

Spade is a data and AI platform for modern finance that transforms messy transaction data into structured, verified records. It enriches transaction data in real time, adding structure, accuracy, and intelligence for various financial applications. Spade's platform supports fintechs, banks, and AI companies by providing clean, enriched data for authorization decisions, rewards programs, analytics, AI model training, and improved user experiences. The company focuses on providing a unified data layer that connects payments to their real-world context with high accuracy and speed, ensuring data integrity across different payment types like cards, ACH, and wires.

Products

• Spade EnrichmentProvides factual transaction details and enhanced data features about the merchant on the other side of a transaction, including card data, transfer data, and universal data.
• Spade ToolingTools to help users easily use enriched data to power product features and workflows, including merchant search and category personalization.
• Attribution AgentAn agentic workflow built on enriched transaction data that applies automated logic to validate transactions against partner lists and Spade’s merchant graph in real time for rewards programs.

Key capabilities

• Real-time transaction enrichment
• Verified merchant and location data
• Sub-50 millisecond P99 enrichment latency
• High accuracy (99% enrichment accuracy, 99.9% accuracy across payment types)
• Coverage of US & Canadian merchants
• API integration
• Standardized merchant descriptors
• Agentic commerce support
• Unified data layer across cards, ACH, wires, and third-party sources
• Data encryption at rest and in transit
• SOC 2 certified
• Continuous testing and validation (penetration testing, automated vulnerability scanning)
• Least-privilege access controls

Use cases

• Risk & Authorization: Make authorization decisions smarter, reduce false declines, drive down fraud losses, support vendor-locked cards, power agentic commerce.
• Rewards & Attribution: Connect purchases to the right reward, enable targeted marketing programs, eliminate attribution errors, personalize offers, automate attribution.
• Analytics & AI: Build intelligence on solid data, provide consistent merchant context, power personalized offers, new product features, and cross-sell opportunities, feed clean data into models, uncover customer insights, accelerate insight generation, unify analytics and operations.
• User Experience: Move disputes to the merchant, provide clarity to customers to recognize charges, reduce customer confusion and disputes, make transactions readable, reduce support costs, speed up disputes.
• Financial Workflows: Support accounting, categorization, and other downstream financial workflows, minimize manual cleanup, provide reliable inputs for financial automation.
• Spend Controls: Enforce real-time spend controls for fleet cards, approve legitimate purchases while blocking misuse, location-based authorization, merchant- and category-locked cards.

AI approach

Spade uses AI agents and machine learning models to enrich messy transaction data, turning it into structured, verified records. This includes standardizing merchant descriptors, categorizing transactions, and providing real-time merchant and location context. The platform feeds clean, enriched data to customer's AI models for improved intelligence and decision-making, and also uses AI agents for automated attribution and risk decisioning.

Tech named: AI agents, machine learning models

Industries served

• Fintechs
• Banks
• AI companies
• Payments
• Hedge funds
• Analytics providers

What it says sets it apart

• Transforms messy transaction data into structured, verified records with AI agents.
• Real-time enrichment with sub-50ms latency and high accuracy.
• Unified data layer for consistent merchant context across various payment types and sources.
• Built for agentic commerce, providing trusted data for autonomous risk decisioning and AI agents.
• Consolidates multiple data sources and tools (merchant databases, enrichment feeds, internal builds) into one API.
• Focus on security with SOC 2 certification, encryption, and robust data protection measures.
• Enables precise, hyper-local attribution for rewards programs.
• Reduces operational overhead and manual reconciliation for financial institutions.
• Provides ground truth data for training AI models, reducing false positives and amplifying precision.

Funding rounds we track

From the AI funding tracker — rounds as reported by the linked publications.