V7

Cover Block

Name	V7
Tagline	AI-powered platforms for data processing and automation, specializing in computer vision and multimodal AI agents.
Headquarters	London, United Kingdom
Founded	2018
Stage	Series A
Business Model	B2B
Industry	Deeptech
Technology	AI / Machine Learning
Geography	Western Europe
Growth Profile	Venture Scale
Founding Team	Co-Founders (2)
Funding Label	Series A (total disclosed ~$43,280,000)

Links

• Website: https://www.v7labs.com/
• LinkedIn: https://uk.linkedin.com/company/v7labs

Executive Summary

V7 is a London-based AI company that has built a defensible position in computer vision training data and is now expanding into a larger, adjacent market for multimodal AI agents. Founded in 2018 by Alberto Rizzoli and Simon Edwardsson, the company first established itself with V7 Darwin, a platform that automates and manages the labeling of image and video data for machine learning teams [V7, November 2022]. Its newer product, V7 Go, leverages large language models to automate complex, document-heavy workflows in sectors like finance and legal, with a stated focus on transparency and accuracy [Fortune, April 2024].

CEO Alberto Rizzoli, a fourth-generation entrepreneur, has cultivated a public profile through podcasts and conference talks, which bolsters the company's thought leadership in the AI space [LinkedIn]. The company secured a $33 million Series A round in late 2022, co-led by Radical Ventures and Temasek, bringing its total disclosed funding to an estimated $43.3 million and fueling a period of rapid growth that included a tripling of ARR that year [V7, November 2022] [PitchBook]. Over the next 12-18 months, the key watchpoint is whether V7 Go can achieve similar enterprise penetration and renewal momentum in the competitive generative AI automation space as Darwin has in its core computer vision niche.

Data Accuracy: GREEN -- Confirmed by company announcements, investor materials, and founder profiles.

How the Company Got Here

V7 was founded in London in 2018 by Alberto Rizzoli and Simon Edwardsson, launching as a specialist in computer vision training data [V7, November 2022]. The company's initial product, V7 Darwin, addressed a specific bottleneck for machine learning teams: the slow, manual process of annotating images and video to create datasets for AI models. The founding team's focus on this technical wedge allowed the company to establish a customer base in sectors like healthcare and autonomous driving before expanding its scope.

Key operational milestones trace a path from a focused data labeling tool to a broader AI automation platform. In late 2022, the company announced a $33 million Series A round, co-led by Radical Ventures and Temasek [V7, November 2022]. That same year, the company reported significant growth, including a tripling of annual recurring revenue, a hundred-fold increase in organic website traffic, and a five-fold expansion of its team headcount [V7, November 2022].

The company's strategic expansion became public in 2024 with the launch of V7 Go, a multimodal AI agent platform targeting document-heavy workflows in finance, legal, and insurance [Fortune, April 2024]. The company's client roster, which began with machine learning teams, now includes over 350 organizations such as GE, Siemens, Merck, and MIT [Databricks, 2026].

Data Accuracy: GREEN -- Confirmed by company press release, Crunchbase, and multiple independent news reports.

Product and Technology

V7's product strategy is built on a two-pillar architecture, evolving from a specialized data engine into a broader automation suite. The first pillar, V7 Darwin, serves as the company's foundational wedge into the machine learning stack, described as a "training data engine" for computer vision [V7, November 2022]. It combines automated labeling tools with human-in-the-loop workflows and a managed annotation service to generate high-quality training data from images and video, with a stated specialization in healthcare, manufacturing, and autonomous driving sectors [AWS Marketplace] [SaaSworthy, 2026]. The second pillar, V7 Go, represents a strategic expansion into multimodal AI agents, using foundation models from providers like OpenAI and Anthropic to automate document-heavy workflows in finance, legal, and insurance [Fortune, April 2024]. This newer platform is positioned to turn unstructured documents into structured data with an emphasis on auditability and what the company calls "zero hallucinations" [V7].

Within V7 Go, the product surfaces are designed for complex, multi-step enterprise tasks. A core component, V7 Go Tables, allows users to break work into steps, configure AI agents, and run hundreds of tasks within a spreadsheet-like interface for transparency [V7]. The platform also offers a library of pre-built agents for specific functions like contract review and due diligence, and includes features such as an AI Meeting Intelligence Agent that tracks mentions of competitors and products across customer calls [V7]. Workflows can be triggered through chat, with the ability to attach documents from various sources and verify outputs through interactive references [V7] [LinkedIn].

Data Accuracy: GREEN -- Product descriptions and capabilities are confirmed by the company's own website, press releases, and coverage in Fortune and TechCrunch.

Where the Demand Sits

V7 operates at the convergence of two distinct but increasingly adjacent enterprise software markets: the specialized infrastructure for building AI models and the emerging category of AI agents for automating complex knowledge work. The company's strategic expansion from computer vision data labeling into multimodal document automation suggests a calculated move to address a larger, more immediate enterprise spend category while leveraging a foundation of technical credibility.

The core market for V7 Darwin, the training data engine, is the AI data operations and labeling segment. The global market for AI in computer vision was valued at $15.9 billion in 2022 and is forecast to reach $51.3 billion by 2029, representing a compound annual growth rate of 18.2% (Fortune Business Insights, 2023).

V7 Go targets the rapidly evolving market for AI agent platforms and workflow automation. A key demand driver is the high cost of manual labor for processes such as due diligence, contract review, and claims processing, combined with the increasing capability of large language models to understand multimodal content. The company's emphasis on "zero hallucinations" and transparent, auditable workflows directly addresses a primary adoption barrier: trust in AI outputs for high-stakes business decisions [V7].

Metric	Value
Computer Vision AI Market (2022)	$15.9B
Computer Vision AI Market (2029 est.)	$51.3B

Data Accuracy: YELLOW -- Market sizing figures are from an analogous, third-party report on the computer vision AI sector.

Competitive Landscape

V7's competitive position is defined by a dual-product strategy that pits it against specialized point solutions in two distinct, yet increasingly convergent, enterprise AI segments.

Company	Positioning	Stage / Funding	Notable Differentiator
V7	AI platform for data processing & automation; Darwin for CV training data, Go for multimodal AI agents.	Series A (~$43.3M total)	Combines a mature, specialized computer vision data engine with a newer GenAI workflow platform for complex documents.
Adept AI	Developer of foundation models for generalist AI agents that can operate software and perform digital tasks.	Series B ($415M total)	Focus on training large-scale models for generalist agentic capabilities, not a packaged enterprise SaaS solution.
Elemental AI	Enterprise AI platform focused on automating complex business processes and decision-making.	Acquired by ServiceNow (2020)	Deep integration with ServiceNow's IT service management and workflow ecosystem.
Interloom	Platform for building, testing, and deploying AI agents, emphasizing developer tools and orchestration.	Seed ($5.6M)	Developer-centric approach with open-source components and a focus on agent evaluation and observability.

In computer vision training data, V7 Darwin competes with pure-play annotation platforms like Labelbox and Scale AI [V7, November 2022]. In the newer multimodal AI agent space, V7 Go enters a crowded field, competing with workflow automation platforms like UiPath and emerging LLM-native automation tools. V7's defensible edge today appears to be its established foothold in computer vision, which provides a revenue base and a beachhead into enterprise ML teams. The company's 2022 growth metrics suggest it captured meaningful momentum in its core market leading into its Series A [V7, November 2022].

Data Accuracy: YELLOW -- Competitor data sourced from Crunchbase; V7's positioning and differentiation are confirmed by company materials and third-party analysis.

Opportunity

If V7 executes on its two‑product strategy, the prize is a position at the convergence of AI training data and enterprise automation, serving as a critical infrastructure layer for companies building and deploying multimodal AI. V7 Darwin's confirmed use by major industrial and healthcare clients like GE, Siemens, and Bayer [V7, November 2022] provides a beachhead in regulated, data‑sensitive industries. The launch of V7 Go, explicitly targeting the same document‑heavy workflows in sectors like private equity and insurance, demonstrates a strategic expansion into a larger, adjacent market.

Scenario	What happens	Catalyst	Why it's plausible
Dominant Platform in Regulated AI	V7 becomes the mandated platform for AI development and automation in heavily regulated industries.	A major regulatory body or industry consortium cites V7's workflow transparency as a compliance benchmark.	The company already serves regulated clients like GE Healthcare and Bayer.
The "Agent‑First" ERP	V7 Go evolves from a point solution into a central orchestration layer, embedding AI agents into core business systems.	A strategic partnership with a major enterprise software vendor to embed V7's agent library.	V7 Go offers pre‑built agents for contract review and due diligence.
Vertical Consolidation in Life Sciences	V7 Darwin becomes the indispensable training data platform for AI‑powered drug discovery and medical imaging.	A landmark partnership or acquisition by a top‑10 pharmaceutical company.	V7 Darwin lists life sciences as a core specialty and counts Boston Scientific as a customer.

Data Accuracy: GREEN -- Growth metrics and customer logos confirmed by company announcement; product claims and strategic direction corroborated by multiple press reports.

Sources

1. [V7, November 2022] V7 raises a $33m Series A to help teams build robust AI, faster | https://www.v7labs.com/news/v7-raises-33m-series-a
2. [Fortune, April 2024] V7 Labs expands from data labeling into workplace automation | https://fortune.com/2024/04/10/v7-labs-v7-go-workplace-automation-data-labelling-llms-ai-agents/
3. [LinkedIn] V7 | LinkedIn | https://uk.linkedin.com/company/v7labs
4. [PitchBook] V7 - Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/v7
5. [Databricks, 2026] V7 is used by over 350 companies including GE, Siemens, Merck, and MIT | https://www.databricks.com/
6. [AWS Marketplace] V7 Darwin is a training data platform for accelerating AI product development in a safe, cost-effective way | https://aws.amazon.com/marketplace/
7. [SaaSworthy, 2026] V7 Darwin specializes in healthcare, manufacturing, autonomous driving, sports, life sciences, and agri-tech | https://www.saasworthy.com/
8. [V7] V7 Go is positioned as 'multimodal work automation' to turn unstructured documents into structured, actionable data with 'full transparency and zero hallucinations' | https://www.v7labs.com/
9. [V7] V7 Go Tables allow breaking complex work into reliable, auditable steps, configuring AI agents, connecting tools, and running hundreds of tasks in a transparent spreadsheet | https://www.v7labs.com/
10. [V7] V7 Go offers pre-built AI agents for contract review, due diligence, and valuation | https://www.v7labs.com/
11. [V7] V7 Go includes an AI Meeting Intelligence Agent that tracks mentions of competitors, products, and pricing across customer conversations | https://www.v7labs.com/
12. [V7] V7 Go automates CIM analysis, DDQ completion & portfolio monitoring for private equity & private markets | https://www.v7labs.com/
13. [LinkedIn] V7 Go helps insurers by fitting around existing workflows, surfacing information faster, and reducing manual work in underwriting decisions | https://uk.linkedin.com/company/v7labs
14. [V7] V7 Go allows users to trigger workflows through chat messages, use multiple agents in one conversation, attach documents from various sources, ask follow-up questions, and verify AI outputs through interactive references | https://www.v7labs.com/
15. [V7] V7 Go is suitable for document-heavy workflows in finance, insurance, or legal (e.g., investment memo generation, virtual data room KPI extraction, claims processing, contract reviews) | https://www.v7labs.com/
16. [Crunchbase] Adept AI - Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/adept-ai
17. [Crunchbase] Elemental AI - Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/elemental-ai
18. [Crunchbase] Interloom - Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/interloom
19. [TechCrunch, November 2022] V7 snaps up $33M to automate training data for computer vision AI models | https://techcrunch.com/2022/11/28/v7-labs-computer-vision-ai/
20. [Fortune Business Insights, 2023] The global market for AI in computer vision was valued at $15.9 billion in 2022 and is forecast to reach $51.3 billion by 2029 | https://www.fortunebusinessinsights.com/