Curvestone AI Raises $4M Seed to Make AI Automation Reliable for Regulated Industries
London-based Curvestone AI has secured $4 million in seed funding to push forward its ambitious mission: to build a dependable, high-accuracy AI automation platform tailored for document-intensive, compliance-heavy sectors such as financial services, insurance and legal. The round is led by MTech Capital, with participation from Boost Capital Partners, D2 Fund and Portfolio Ventures.
In an era when many organisations treat generative AI as an experimental productivity tool, Curvestone aims for something far more foundational, to deliver automation that can be trusted end-to-end, even in the most regulated and high-stakes workflows. According to the company, it is not enough for an AI to perform well on isolated tasks; when dozens of steps are chained together: from document ingestion, classification, compliance checks, legal reviews, to approvals, even small error rates multiply, often collapsing overall accuracy to unacceptable levels. Curvestone calls this the “compound error problem.”
By addressing this problem head-on with a purpose-built workflow automation platform, Curvestone is positioning itself not merely as a vendor, but as an essential infrastructure layer for the heavily regulated backbone of global finance, legal services and insurance operations.
Curvestone AI is Built by Industry Veterans, Designed for Real Workflows
Curvestone was founded by brothers Dawid Kotur and Sebastian Kotur, who bring deep experience from enterprise-level AI and automation programs at firms such as PwC, Metro Bank and GKN. Their journey began when they witnessed first-hand how traditional and even advanced AI tools repeatedly failed to deliver consistent, audit-ready results in regulated workflows. This awareness drove them to build a platform grounded in accuracy, compliance and operational integrity, not just speed or convenience.
Prior to accepting external capital, Curvestone had already achieved profitability while demonstrating impressive commercial growth: the company reports a 7× increase in revenue over 12 months and currently processes billions of tokens every quarter across its financial, legal and insurance clients.
In short: this is a functioning platform used in real-world, high-risk environments.
Curvestone AI is Solving the “Compound Error Problem” The Core Technical Challenge
What makes Curvestone’s value proposition unique is its ability to maintain stable accuracy through multi-step workflows, even under heavy compliance and regulatory constraints. According to public reporting, a workflow that chains a dozen or more steps including document extraction, validation, classification, compliance checks and approval cycles can see overall accuracy drop from 98% on a single task to only 30–40% by the final step. This drop effectively undermines AI’s usability in regulated sectors.
Curvestone’s platform approaches this problem holistically. It embeds automation at each step, validates and normalises data robustly, maintains audit trails and ensures that every output is compliant and traceable. As a result, firms that adopt Curvestone no longer treat AI as a “nice-to-have” assistant, but as a dependable operational backbone capable of handling mission-critical tasks with predictable outcomes.
For companies subject to strict regulation, legal scrutiny and compliance audits, that predictability is extremely essential.
Early Traction and Real-world Use Cases of Curvestone AI
Despite being in seed stage, Curvestone has already earned the trust of leading law firms, mortgage lenders, wealth managers and insurance operators across Europe. Notable clients include firms such as Walker Morris, Stephenson Harwood, Browne Jacobson and Pivotal Growth. In real cases:
- Walker Morris reportedly reduced service agreement review times from roughly four hours down to fifteen minutes, a dramatic productivity gain.
- Pivotal Growth shifted from spot-checking a small fraction of mortgage files to reviewing 100% of them across its advice teams, while preserving consistency and auditability.
They are measurable improvements in speed, risk reduction and operational control. In sectors where compliance failures can result in regulatory fines, reputational damage or financial penalties, such improvements are invaluable.
Why Does Curvestone Matters Right Now ?
As regulators worldwide tighten rules around data privacy, document retention, audit trails and compliance oversight, firms across finance, insurance and law are facing an urgent problem: how to modernise workflows without sacrificing accuracy or control.
Studies on AI-driven compliance automation echo this need, warning that AI tools working in isolation are insufficient, what’s needed are integrated, auditable systems that combine automation with governance and traceability.
Curvestone arrives at precisely this moment. Their $4 M raise isn’t just for growth, it’s strategic. The capital will accelerate product development, expand their library of validated workflow templates, deepen integrations with CRMs, document management systems and core business platforms, and accelerate go-to-market efforts across regulated sectors.
If successful, Curvestone may well become the default automation layer for regulated industries worldwide, the foundation upon which reliability, compliance and scale converge.
Curvestone AI represents a shift in the enterprise-AI narrative. For too long, generative AI has been sold as a magic wand that promises gains in creativity, speed and productivity. But in regulated industries where lives, money and reputations are at stake, reliability and auditability matter far more than flashy demos. By focusing squarely on the “compound error problem,” Curvestone is tackling the underlying weakness of enterprise AI: inconsistency under complex workflows. Their success so far: profitability, real client traction, seed funding and enterprise results suggests this is not a niche play, but the beginnings of a new infrastructure category.
If they deliver on their vision, Curvestone could become the backbone of compliance-ready automation across finance, insurance and legal. In a world where regulations tighten each year and workloads grow in volume and complexity, that kind of reliability could become indispensable. For enterprises and for the future of responsible AI adoption, Curvestone may prove to be exactly what the industry needs.