Freshfields is weighing a spinoff of Freshfields Lab, its in-house legal technology unit, potentially valuing it at over a billion pounds. The logic is seductive: build AI internally, prove it works, extract it as a standalone business, sell it to external investors. But this story matters to UK regulated firms because it masks a deeper problem. When a global practice with unlimited resources needs to separate its AI capability to justify its value, something is broken in how that AI was designed. The SRA Code and FCA Consumer Duty PS22/9 do not reward innovation theater—they reward documented outcomes, governance and demonstrable client benefit. A spinoff structure is a financial engineering play, not an answer to either of those requirements.

What Freshfields reveals is a pattern: the largest firms have built proprietary, closed AI systems—Harvey, Luminance, Legora—designed around their own workflows, their own data, their own risk profiles. These tools excel at what they were built for: internal efficiency for their creators. But they are not modular. They do not scale easily to other firms' processes. They assume other firms want to adopt the same architectural choices. And when the parent firm needs to justify billions in R&D investment, the spinoff becomes inevitable because the original AI product was never built to solve a market problem—it was built to solve a single firm's problem. That is why monetization looks like extraction rather than expansion.

Trovix takes the opposite approach. Instead of building a closed AI system that only works within our own practice, we build tools designed from the start to integrate with how other regulated firms actually work. Trovix Aria is not a replacement for a firm's knowledge management—it plugs into it. Trovix Sift handles document intelligence but respects the firm's existing workflows, not imposing new ones. Trovix Audit gives you the governance dashboard that the SRA Code and EU AI Act now require—not as a bolt-on, but as the spine of your AI operations. We are candid about what we can and cannot do. We cannot make an underfunded practice suddenly profitable. But we can document that your AI meets regulatory expectations, and we can show your partners exactly what their fee-earners are actually using it for. That transparency is what separates responsible AI integration from the venture-backed hype that Freshfields' spinoff represents.

If you run a mid-market law firm, insurer, financial services firm or accountancy practice, the lesson is this: do not wait for your own in-house AI team to produce a spinoff opportunity before you act. Do not assume that the tools built for firms twice your size will solve your problems at your cost. Instead, ask: what is the one thing my team does every day that AI could actually improve—and do I need to own the underlying technology to get there, or do I need to govern it and integrate it responsibly? That distinction will determine whether you end up reinventing Freshfields' problem or solving your own.

Source: PYMNTS