How Cinven and compliance software firm Archer worked hand-in-hand to transform Archer from a carve-out to a category leader and turn a modest AI experiment into a game-changing platform.
The boom in generative artificial intelligence (AI) tools has enormous potential for serious impact at the enterprise level, reshaping how companies handle everything from customer service to compliance. These tools can accelerate tasks, for example by acting as assistants that search and collate information for knowledge workers. This can streamline operations, allowing companies to reduce costs.
The enthusiasm is certainly there, as recent data shows: a 2024 survey found that 72% of global businesses have already adopted AI in at least one function. Yet the gap between experimentation and value is stark: only 1% of firms say AI is fully embedded in their workflows and delivering significant business outcomes.
That’s where companies like Archer stand out. A mid-sized risk management software company, Archer had mixed success implementing AI capabilities but saw opportunities to accelerate the capabilities of its internal team. In just two years, it went from a blank-slate AI strategy to gaining a competitive edge via AI, transforming its product and closing the largest contract in the company’s history on the back of its new AI platform. For any business looking to scale with AI, Archer offers a case study in what effective implementation looks like.
From carve-out to contender
When the Cinven funds acquired Archer, the company had been spun-out of a cybersecurity business. It had a solid business strategy but lacked an AI roadmap. “AI wasn’t seen as a priority method of creating value in the diligence materials,” recalls Nathan Atkinson, an AI and machine-learning executive who works on digital transformation efforts across Cinven’s portfolio. “The focus was on go-to-market improvements and moving customers to SaaS (Software as a Service).”
Still, the potential was clear. Cinven and Archer collaborated to identify opportunities across Archer’s operations and create an AI strategy. “We looked at customer support, internal data and what could be done with the product itself,” says Atkinson. An initial round of collaborative workshops helped build trust and align priorities.
To demonstrate value early, Cinven and Archer began with some quick, pragmatic projects. A customer service chatbot was deployed to handle common admin queries – an implementation that delivered immediate gains. Next came an internal data platform, designed to consolidate CRM, product and usage data into a single view for sales, marketing and product teams. “That took about three months,” Atkinson notes. “We didn’t over-engineer it. We just delivered what was needed.”
Crucially, these early wins encouraged the board to expand its internal capabilities to support ongoing analytics work. The groundwork was now in place for a more ambitious move.
The breakthrough: product-led AI
The more transformative opportunity came from embedding AI directly into the Archer platform.
With support from AWS (Amazon Web Services), the team piloted a tool to scan global regulatory frameworks and map them against a customer’s internal controls, a time-consuming task that previously required manual review by risk teams.
Archer, in collaboration with the Cinven team, initially debated building this capability from scratch, but ultimately chose to integrate a third-party solution. “Integrating the external tool got us to market faster and the results speak for themselves,” says Atkinson.
The results were indeed dramatic. Archer secured its largest contract to date and saw a significant increase in the size of deals, compared to those it was making before the AI implementation. More are in the pipeline. “It’s not just about revenue,” Atkinson adds. “This fundamentally changed the way they compete. It’s true product differentiation.”
Not every AI initiative hits the mark, though. A chatbot focused on user experience (UX) ultimately wasn’t adopted. But Atkinson views that as part of the process. “You have to think like a VC, make smaller bets, double down when you see value and take the learnings when you don’t.”
Value creation, not vanity metrics
That mindset, combined with relentless focus on measurable outcomes, has been the hallmark of Archer’s AI adoption strategy. For each project, Cinven and Archer defined clear key performance indicators (KPIs), such as reduced support ticket volumes, internal Net Promoter Scores (NPS) and, ultimately, revenue growth from new product capabilities. “The goal isn’t AI for AI’s sake,” says Atkinson. “It’s revenue, margin or multiple expansion, and ideally all three.”
Another objective was to develop internal AI capabilities. Cinven worked with Archer not just to implement solutions, but to build the skills needed to run them long-term. “This isn’t consulting,” Atkinson says. “We own these businesses. They need to be able to carry the work forward.”
Archer’s story is not one of hype, but of strategic application. AI wasn’t part of the original case for investing in the business. But by identifying the opportunities where AI could offer advantages, delivering quick wins and betting big when it counted, Cinven helped the company pivot from a carved-out legacy business to a differentiated SaaS provider.
It’s a model that plays out across Cinven’s portfolio and one other mid-sized firms can learn from. For companies still struggling to move from AI pilots to production-scale impact, Archer offers a clear reminder: with the right support and expertise, even the most unassuming businesses can unlock breakthrough value. The challenge is in the execution.
