ValueEQ is an AI-powered business valuation and M&A intelligence platform that gives investment professionals access to 60,000+ public company comparables, 60,000+ M&A deals, and a full valuation suite — at 90% of the cost of legacy financial terminals. We were brought in to architect and build the product from the ground up, delivering a platform now trusted by 500+ teams worldwide, including institutions like Barclays, Eurazeo, and Crédit Agricole.

The Challenge

Investment professionals were spending hours manually compiling peer sets and benchmarking data across fragmented sources. Legacy terminals like Bloomberg charged tens of thousands of dollars annually, putting institutional-grade data out of reach for most firms. ValueEQ needed a platform that was fast, global in scope, and intelligent enough to let users find what they needed in plain English — without the complexity of traditional financial software.

Financial Dashboards at Global Scale

We built the core data platform using React.js, Next.js, D3.js, TailwindCSS, and TanStack Query — a stack chosen specifically for its ability to handle high-frequency data updates without UI jank.

The dashboards pull live financial metrics from 120+ countries and 70+ stock exchanges, surfacing company fundamentals, valuation multiples, M&A deal details, and sector benchmarks in a single workspace. TanStack Query manages the caching and background refetching layer, ensuring data stays fresh without hammering the API. D3.js powers the interactive charting — trend lines, multiple comparisons, and peer benchmarking visualizations — all of which needed to perform smoothly across large datasets.

Every dashboard was designed to be export-ready, with one-click Excel export so analysts could pull clean, AI-normalized data directly into their models.

AI-Powered Natural Language Screening

One of the most technically interesting problems was making 60,000+ companies actually searchable in a meaningful way. Traditional filters — dropdowns, range sliders, multi-select menus — don't match how analysts think. They think in sentences: "European SaaS firms with EV/Revenue below 8×" or "US healthcare companies growing revenue above 20% with positive EBITDA."

We built a natural language filtering system that parses queries like these, maps them to structured financial criteria, and executes them against the full company database in real time. The result: 50% reduction in search time for users versus traditional filter-based approaches. Analysts can iterate on their screens conversationally, refining peer sets the same way they'd describe them to a colleague.

Secure Payments & Authentication

We integrated Stripe for subscription billing, supporting the tiered access model that lets ValueEQ serve everyone from independent advisors to large institutional teams. The implementation handles subscription lifecycle events — upgrades, downgrades, cancellations, and renewals — through Stripe webhooks, keeping billing state synchronized with user access in real time.

Authentication is handled via Firebase Auth, providing institutional-grade security with support for SSO and multi-factor authentication. Access control is enforced at the API layer, ensuring each tier of subscription unlocks the appropriate depth of data — from basic screening to full valuation suite access with M&A deal analytics.

Results

• 500+ investment firms onboarded, including Barclays, Eurazeo, L Catterton, and Crédit Agricole
• 120+ countries and 70+ stock exchanges covered with real-time data
• 60,000+ companies screenable via natural language queries
• 50% reduction in company search and peer set assembly time
• 90% cost reduction compared to legacy financial terminals like Bloomberg

Tech Stack

• Frontend: React.js, Next.js, TailwindCSS
• Data Visualization: D3.js
• Data Fetching: TanStack Query
• Payments: Stripe (subscription billing, webhooks)
• Authentication: Firebase Auth
• AI: Natural language query parsing for financial screening