Most AI projects don’t fail because of the AI, they fail because they never make it to production. We all been there. The proof of concept works, the demo impresses stakeholders, the model generates the right answers, it’s time to deploy… This is when new challenges appear, such as governance, workflow orchestration, integrations, security, compliance, user adoption, and operational readiness. We can pinpoint it: this is exactly where many AI initiatives stall.

This case study shows how we helped a UK legal-tech startup bridge that gap. Rather than building another AI prototype, we transformed an existing proof of concept into an investor-ready, production-ready solution in just two weeks - reducing manual effort by up to 80% while accelerating the client’s path to market.

The problem

The client had already built an AI-powered legal platform, which worked, the AI performed well. But when investors and enterprise customers asked to see a complete Data Subject Access Request (DSAR) workflow, there wasn’t one. Instead, requests were handled across emails, manual reviews and disconnected systems.

There was no single process to:

• receive new requests
• classify them
• collect the required information
• generate response packages
• monitor statutory deadlines

The AI existed, but the business workflow didn’t. That meant the product wasn’t ready for enterprise customers, even though the underlying AI already was.

Why did this matter?

For an early-stage legal-tech company, this wasn’t just an engineering problem, it was a commercial one. Without an end-to-end workflow they couldn’t confidently demonstrate the product to investors or enterprise buyers.

Every delayed release meant slower go-to-market, delayed customer acquisition and increasing pressure on the leadership.

The solution

Rather than rebuilding the client’s platform, Peruzzi focused on what mattered most: creating the missing business workflow that transformed an AI capability into a product customers could actually use. We designed and delivered a complete DSAR process that automated request intake, AI-assisted classification, workflow management and response generation, while keeping legal professionals in control through a human-in-the-loop approach.

The result was a solution that could be demonstrated with confidence and scaled for real customer deployments.

Business impact

Within just two weeks, the client had an investor-ready DSAR workflow that dramatically reduced manual effort while accelerating product readiness.

- 70–80% reduction in manual effort

Routine administrative work across the DSAR process became largely automated, allowing legal teams to focus on review rather than repetitive administration. For employees, the time spent was reduced from 20-40 hours to 2-4 hours, which is a huge improvement in their workflow.

Faster path to market

Instead of spending months extending an internal prototype, the client was able to demonstrate a complete end-to-end workflow to customers and investors.

AI that fits regulated industries

The workflow was designed with human oversight built in, ensuring AI supported legal professionals without replacing decision-making.

Built for future growth

The solution provided the foundation for a scalable compliance platform rather than another isolated proof of concept.

Key takeaway

Many organisations believe their AI project is “almost finished” because the model works, while in reality, the hardest part is rarely the AI. It’s everything around it: from production workflows, through governance, integration security to human oversight. That’s the difference between a promising demo and a product customers are willing to trust.