Side-by-side comparison of AI visibility scores, market position, and capabilities
Modern financial modeling and business planning tool built for spreadsheet-style flexibility with model transparency. London UK, raised $30M+.
Causal is a financial modeling and business planning tool that reimagines the spreadsheet as a more powerful, transparent, and shareable medium for financial and operational analysis. Founded in 2019 and headquartered in London, United Kingdom, Causal has raised more than $30 million from investors including Coatue Management. The company was built by former McKinsey consultants and software engineers who believed that spreadsheets could be fundamentally improved without abandoning the formula-based modeling approach that makes them so versatile for financial planning.\n\nCausal's interface introduces a formula-based modeling system that maintains the flexibility of spreadsheets while adding features that traditional spreadsheets lack: visible model structure, automatic scenario management, live data connections, and presentation-quality output. Users write formulas to define business logic, and Causal automatically organizes those formulas into a readable, auditable model structure rather than hiding logic in individual cells. This makes Causal models easier to review, share, and hand off than traditional spreadsheet models, addressing a key failure mode of spreadsheet FP&A.\n\nCausal targets early-stage startups, growth companies, and financial consultants who build financial models for clients, as well as finance teams at mid-market companies who want more powerful modeling tools without moving to full CPM platforms. The tool has found particular traction for startup fundraising models, unit economics analysis, and scenario planning use cases. Causal competes with Runway Financial, Cube, and more broadly with Excel and Google Sheets themselves, positioning itself as a modern replacement for the spreadsheet in the financial modeling workflow.
a2z Radiology AI raised $20M in 2025 for its whole-body AI that simultaneously screens for 24+ conditions across CT scans — from incidental cancers to cardiovascular risk — in a single automated read.
a2z Radiology AI has developed a whole-body CT analysis platform that simultaneously screens for over 24 medical conditions across a single CT scan, including incidental cancers, coronary artery disease, aortic aneurysm, bone density loss, and organ abnormalities. The AI acts as a second reader that radiologists can use to catch incidental findings that fall outside the primary reason for a scan — a major source of missed diagnoses.
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