A venture investment in a fast-growing AI platform that addresses the key reasons why artificial intelligence fails in financial institutions — inconsistent outputs, lack of institutional memory, and the inability to scale complex workflows without errors.
Regional focus of the project: United States, United Kingdom — global expansion.
Problem
Artificial intelligence in finance and insurance is being adopted faster than governance systems are being developed, and the cost of errors is already measured in billions. This means:
- $2.3 billion in losses from AI-related errors in trading alone in the first quarter of 2026.
- One in five commercial insurers reported losses caused by artificial intelligence in 2025.
- Every senior partner or underwriter who leaves takes years of accumulated institutional knowledge with them — no existing tool captures this automatically.
- 24 U.S. states have adopted the NAIC regulatory bulletin on the use of AI in insurance — governance is no longer optional.
- Leading language models generate brilliant answers to isolated queries, but remain inconsistent, non-standardized and temporary at the scale of real operations.
Solution and Product
A unified platform consisting of three components:
- V7 Go: connects leading language models with finance and insurance teams — launching deal reviews, analytical briefs and screening as repeatable automated workflows; every result is linked to its primary source; over 100,000 tasks per day.
- Knowledge Base: every processed document enriches the client company’s permanent structured knowledge repository — growing in value over time and unable to be copied by competitors.
- V7 Darwin: data annotation and training datasets for computer vision; $7.3 million in annual revenue, 418 clients — GE, Siemens, Medtronic, Roche, Walmart, Helsing; independently profitable.
All three components form a single platform. The institutional knowledge base deepens with every processed document and cannot be replicated by competitors.
Brief Market Analysis
Enterprise artificial intelligence for finance and insurance is one of the most structurally growing segments in enterprise software:
- $155 billion+ global enterprise AI software market by 2030.
- $25.7 million in open contracts in the pipeline; $1 million+ in new deals added weekly.
- 97 active clients with near-zero penetration in the target verticals — a massive gap.
- Finance — 43 clients, $3.2 million in annual revenue — and insurance are the deepest verticals with the highest conversion rates.
V7 is a unified platform that works with any language model, accumulates company knowledge and controls the quality of every result — without dependence on a single provider.
Tangible and Intangible Assets
- The strongest competitive position in the category: 12 wins out of 13 against Hebbia and 10 out of 10 against Rogo in direct benchmark comparisons; 38% of annual revenue came from displacing competitors.
- Key clients: Hamilton Lane — $1 trillion in assets under management, Yale Investments — $49 billion, Capital Dynamics — $14 billion, Grant Thornton — growth from $85,000 to $390,000 over 12 months, 459% net revenue retention, Aegis Lloyd’s — $1.4 million total contract value.
- A unified platform with a proven accumulated knowledge advantage: client data is structured according to V7’s proprietary logic — migrating it to another system takes months and always produces an inferior result.
- Technological advantage: more than 90% of production workflows use more than one class of models; V7 is not dependent on any single provider and automatically selects the best model for each task.
- Partnerships: direct research partnership with Anthropic — early access to models before public release; $4 million deal with a leading AI lab; Deloitte Fast 50 UK — November 2025.
Current Development Status and Achievements
The company demonstrates an exceptional growth trajectory: $15 million in total annual revenue, $7.8 million in V7 Go revenue as of April 2026, 97 active clients, and 44× growth over approximately 24 months.
- V7 Go revenue: $3 million → $6 million in one quarter at the beginning of 2026; April closed at $7.8 million — 21% month-on-month growth.
- 160% net revenue retention — month 12; top 20 clients — 250%.
- 95% customer retention by logo count; no churn above $100,000; no unwanted churn.
- Approximately 80% gross margin — stable during scaling.
- Grant Thornton: $85,000 → $390,000 — 459% net revenue retention on a single client over 12 months.
- A $4 million deal signed with a leading AI lab confirms V7 as infrastructure trusted by the world’s most demanding artificial intelligence developers.
Team and Personnel
The company was founded by entrepreneurs and engineers with experience in artificial intelligence, enterprise software and finance.
Key team members:
- Alberto Rizzoli, CEO — co-founder of Aipoly, former Sequoia Capital scout, serial entrepreneur in computer vision and enterprise AI.
- Simon Edwardsson, CTO — co-founder of Aipoly, founder of Tower Defence, architect of the V7 technology platform.
- Jason Miller, Head of Growth — former Berkeley, Tyk and Jigsaw.
- Institutional investors: Amadeus Capital Partners — lead Series A investor, Temasek, Radical Ventures, Air Street Capital — Nathan Benaich, Partech, Miele Ventures.
- Strategic angels: Christian Szegedy — xAI, Max Jaderberg — Isomorphic Labs, Oriol Vinyals — Google DeepMind, Alex Kendall — Wayve, François Chollet — Keras, Miles Brundage — former OpenAI.
Key Current and Target Project Metrics
Current metrics: $7.8 million in V7 Go revenue — April 2026, $15 million in total annual revenue, 97 active clients.
- 44× growth over approximately 24 months.
- 160% net revenue retention — month 12; top 20 clients — 250%.
- Approximately 80% gross margin; 95% customer retention by logo count.
- $25.7 million in open contracts in the pipeline.
Unit Economics
- Average annual contract value — current: $79,800 → target of $200,000 on new deals.
- Net revenue retention of top 20 clients: 250%.
- Customer retention by logo count: 95%.
- Weekly pipeline: $1 million+ in new deals; conversion rate of 27%.
Target Metrics — 2026–2028
- $29.2 million in V7 Go revenue by the end of 2026 — 3.7× the April run rate.
- $35 million+ projected revenue over the next 12 months, including Darwin, according to management’s plan.
- Series B round targeted for late 2026 after V7 Go revenue crosses $10 million.
- Break-even: the Anthropic deal and the formation of a sales team in New York are key catalysts.
Investor Offer
A venture-type investment that provides returns exclusively through the growth of the company’s capitalization and the subsequent sale of ICLUB’s stake, without dividend payments.
- Minimum ticket: $5,000; venture model — return through capitalization growth.
- Timeline: deadline — 05.07.2026.
Exit Opportunities
- Strategic acquisition by Anthropic, Workday, Salesforce or Databricks at a valuation of $500 million–$3 billion.
- IPO: positioning for a public listing in 2028–2029 upon reaching $200 million+ in annual revenue.
- Consolidation of the operational enterprise artificial intelligence market.
Potential multiple: approximately 3–7× in the base-case acquisition scenario under favorable market conditions; up to 30×+ in the optimistic scenario.
Additional information about the project is available after registration in the app via the link.
Join the closed Telegram chat to learn about other current investment opportunities — https://t.me/+qNeq1Ir3irZhMTBi
