European law firms cannot continue building their tech stack on access that can be switched off overnight by a foreign government. Sovereign AI has been under the limelight in recent months, with emphasis on countries weaning off Silicon Valley. Law firms acting smartly are choosing to own enterprise-grade AI infrastructure with privacy-preserving technologies, instead of merely renting it.
In June, the US government shut down international access to Anthropic models, citing national security concerns, after which Anthropic agreed to comply. We can expect similar occurrences in the foreseeable. If Trump can pull the plug now, when law firms are still piloting AI solutions from US-based providers, what will happen when firms become totally dependent on them? This situation has highlighted that AI and compute are not just a tool but critical infrastructure, as essential to societal functioning as the internet or the national grid.
The urgency to own AI is more acute than ever. Firms are aggressively shifting from generic AI pilots to owning custom-built, proprietary AI infrastructure independent of US hyperscalers. This gives firms the greatest competitive edge while staying in line with compliance by protecting data security – while also granting them autonomy and robustness in the face of geopolitical turbulence. Firms falling behind by renting software, on the other hand, risk data leaks and global shutdowns.
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Law firms are eager to innovate but face security risks
In the face of competition, firms are impatient to reap the benefits of legaltech to draft and analyse contracts, streamline research and automate document review.
For example, Kirkland & Ellis knows not to rely on a single, out-of-the-box LLM. The firm is building native infrastructure and fine-tuning open-source LLMs using its own on-premise GPU environments, investing €430m to take the collective intelligence of their lawyers and deploy that throughout the firm. German firm RÖDL’s sovereign European AI architecture ensures 100% data sovereignty, keeping hosting within Germany to comply with the EU AI Act and GDPR regulations.
Firms are bound to strict client confidentiality. Uploading unredacted client information, personal data or sensitive case files to public, non-secure AI platforms is heavily restricted and violates client privilege. Many law firms currently use external AI models like Gemini or Anthropic.
The problem is the hosting methods used by such models. If you send data from sensitive workflows to a central company for analysis and that company has access permissions, it inevitably violates privacy and exposes client data. There is also a risk of them using the prompts to train their models.
Even enterprise agreements with such companies – which guarantee API endpoints, basic privacy, and no improving models with firms’ raw prompts – on their own only address part of the problem. It does not integrate the LLM into legacy software, permission hierarchies or audit pipelines; nor does it determine when human verification is required and assume responsibility for business outcomes, compliance or operational errors.
FLock.io’s solution
Enterprises like FLock.io are emerging to build regional, compliant, private AI infrastructure for law firms. FLock.io acts as the delivery layer, sending Forward Deployed Engineers (FDEs) on-site to wire the model safely into frontline workflows.
As model access becomes commoditised and cheap, writing code or generating text approaches near-zero cost. The true bottleneck in highly regulated settings (law, healthcare, finance) is connecting in: keeping data in-domain, permissions, auditing, acceptance against business metrics and ongoing operations.
- Where are the legal/regulatory boundaries?
- How is auditing handled?
- How do you ensure data stays within client-controlled boundaries while making the workflow actionable and auditable?
In the SaaS era you sliced vertically by industry and were forced to average everything out. In the AI era the tool is horizontal. What’s truly scarce is the layer of judgment that connects it into each highly sensitive workflow. That judgment used to be called FDE; now we forge it into FDA (forward Deploy Agent) – a horizontal delivery capability that is scalable, that accrues, and that others can’t copy.
The raw data, the vertical models trained on it, the deployed tools and workstreams all stay inside the firm’s domain and belong to the firm. FLock.io captures the abstract structure of the workflow judgment (e.g., risk rules, question ordering, escalation triggers) into a reusable digital asset called an FDA, and the firm owns the FDA not a single individual.
Individual lawyers using generalised AI products is inefficient and risks breaking confidentiality
Lawyers work notoriously long hours. Despite their intense education, much of their day is spent doing repetitive tasks that no longer need a human for their entirety. To lift their workload, individual lawyers are using generic AI tools. This can shorten their office hours, or free up time for tasks that truly require a human with years of studies under their belt. However, the benefits of doing this independently is a shadow of what a workforce could achieve as a whole if the firm implemented a team-wide custom AI solution.
It’s not just inefficient but a security and competitive risk. Individual lawyers copying and pasting sensitive documents into AI tools often sends data from sensitive workflows to a central server. Elite firms’ legal data is a goldmine, and yet firms are willingly sending it to centralised corporations where it can be used for model training. In industries with sensitive information, leaks and exposures can be disastrous – but this is not the only danger. Corporations may create AI products or even an entire elite law firm that competes with your firm, reaping your valuable knowledge base.
European law firms face several obstacles
IT departments, compliance officers and lawyers often have very different goals. IT prioritises security, whereas lawyers want efficiency. Moreover, many firms do not have centralised budgets. This results in fragmented, siloed tool adoption across different teams.
Firms face a frustrating trade-off: if they prioritise complete data security through locally deployed open-source models, they often end up with a model with high hallucination rates and poor memory. If they want cutting-edge reasoning capabilities, they risk data leaking out of the firm’s strict security boundaries. Balancing AI product quality with strict privacy compliance is critical. The product must align with high usability standards while complying with data privacy for law firm trust.
What a privacy-preserving AI automation tool for a law firm looks like
The ultimate goal for elite law firms is to build an AI solution that self-improves the more its lawyers use it. This is possible through a continuous data flywheel: every edit a lawyer makes to an AI draft feeds more data into the model, automatically fine-tuning it. This refines the firm’s proprietary internal AI systems and Standard Operating Procedures (SOPs).
Firstly, an AI readiness audit identifies which parts of the legal workflows can be automated or require human oversight. Then, a pilot is run focused on generating term sheets, share purchase agreements and joint venture agreements with minimal intervention. The pilot runs until a final review. The resulting software will retain all IP and usage data within the law firm, preventing centralised AI corporations from accessing sensitive workflows.
One use case is an AI tool generating full contracts aligned with firm style and standards. Lawyers can input term sheets and receive 46 to 60-page agreements formatted exactly to the firm’s font and paragraph style. The AI assists in iterative clause refinement, reducing hours of manual drafting to minutes. Future plans include automating due diligence reports by analysing collected evidence and web data, targeting repetitive tasks common across law firms and auditors. This helps firms achieve efficiency gains in routine legal work, freeing resources for higher-value activities.
Lawyers are known to spend hours refining their wording with specific clauses. A tool can help to streamline this. It can also format contracts to the law firm’s existing font, spacing and paragraphing styles to minimise manual rework.
For large law firms with over 5,000 lawyers, such tools present the opportunity for an additional revenue stream. They can leverage their custom AI solution while licensing lower grade versions to smaller firms. This reinforces their market leadership through proprietary AI tools.
In highly sensitive industries such as law where data cannot leave its domain, FLock.io is the delivery team that truly connects AI into the business process and answers for the business outcome. We turn the “judgment” accumulated in every on-site engagement into the company’s digital assets (FDA), making our delivery capability replicable and scalable.
Full AI workflow transformation vs. improvements
For some law firms, full AI workflow transformation is the best way forward. In such cases, customised solutions are the wiser choice than readily available generic products. A custom solution can support both transactional and non-transactional workstreams, as well as litigation and non-litigation.
Other firms are not currently pursuing an entire transformation of their workflows. This could be because they are already technically advanced, and they are wary of cloud AI risks. In the next phase, they want to improve the privacy and security of their system to avoid data leaks. Off-the-shelf products do not make the cut for firms with these ambitions. Instead, they are seeking to improve certain aspects with privacy-preserving technology. The FLock.io team can also deliver this while ensuring secure and customisable integration.
More about FLock.io
FLock.io is an AI research and infrastructure company pioneering enterprise-grade federated learning and distributed AI solutions. Its decentralised federated learning architecture and production-ready platforms (AI Arena, FL Alliance, and FLock API Platform) enable organisations to train and deploy their own custom AI models on local hardware while maintaining full data privacy, model ownership, and regulatory alignment by design.
Email us at hello@flock.io to steer your firm’s legaltech journey in a direction that will satisfy your compliance department and clients alike.
