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Bringing Legal-Specific AI to Every App

Bringing Legal-Specific AI to Every App

AI That Works Where Lawyers Work

AI adoption in legal tech has been fragmented. Firms have relied on standalone tools like contract review platforms, research assistants, or proprietary vendor solutions that operate in isolation. Meanwhile, concerns over cloud-based AI solutions as data security, compliance and limited firm-wide deployment have slowed broader adoption.

Microsoft’s new Windows AI APIs change that, as now firms can deploy their own AI models, whether built in-house or sourced from vendors, and integrate them directly into the tools lawyers already use.

This means AI doesn’t have to be something lawyers go out of their way to use, it can become a firm-wide capability, enhancing workflows across office suites, document management systems, case management tools, and even contract drafting software, basically anywhere that makes use of these APIs.

Why Local AI Matters


One of the biggest changes here is the ability to run AI models locally on your devices. Legal work involves sensitive client data, and keeping AI processing on-device means firms don’t have to worry about data leaving their infrastructure.

Instead of sending documents to the cloud for analysis, firms can deploy smaller, more efficient legal-specific models like KL3M that run directly on user devices. This means:

  • Stronger security and compliance: Data stays within the firm, reducing privacy risks.
  • Faster processing: No delays from cloud-based inference, making AI tools more responsive.
  • Offline functionality: AI remains available even without an internet connection.

By moving AI processing closer to the user, legal teams can use AI-driven insights while keeping control over how and where their data is processed.


With these APIs, AI can finally be embedded into the tools lawyers already use, solving key pain points:

  • Legal Aware Outlook: AI trained on legal email data could automatically assess privilege, route client requests to the right team, and flag risky language in email threads. It could also detect missing attachments in court filings and suggest responses based on prior legal communications.
  • Smarter Document Management: AI within document management systems could auto-tag contracts, track version changes in deals, and flag missing provisions based on firm playbooks. This would address version control headaches and compliance risks in document retention policies.
  • Policy Aligned Drafting: AI models trained on a firm’s writing guidelines and compliance rules could ensure consistency in document drafting and approvals, flagging issues before they reach senior lawyers.
  • Contract Drafting That Learns: AI fine-tuned on a firm’s past agreements could offer real-time drafting suggestions, ensuring alignment with previous deal terms, reducing risk, and improving turnaround times.


This isn’t just another AI feature, it’s a rethinking in how AI is deployed in legal firms. Instead of being locked into one-size-fits-all vendor solutions, firms now have the ability to train and deploy (or simply source) their own models, tailored to their specific needs.

Fine-Tuning: The Real Differentiator

Fine-tuning a model to truly understand a firm’s way of working isn’t simple. It requires expertise, high-quality data, and ongoing refinement. But for firms that take on this challenge, the rewards are significant.

A well-trained legal AI model could become a real differentiator, so not just improving internal efficiency but also shaping how clients interact with legal services. Firms could even extend their fine-tuned models to in-house legal teams at client companies, embedding AI-driven expertise into their workflows.

This would mean clients aren’t just getting legal services, they're getting AI-powered legal intelligence that aligns with their specific business and compliance needs.

The Stakes: Why Firms Should Act Now

For too long, legal tech as a whole has been driven by external solutions that often limit firms’ control over data, workflows, and customisation. While these platforms offer valuable functionality, they also come with constraints that don’t always align with firm-specific needs. The shift to firm-specific AI models isn’t just a competitive advantage: it’s a necessity.

The firms that master AI customisation today will be defining the legal services market of tomorrow. Those that hesitate risk being locked into vendor-driven AI, unable to tailor technology to their specific legal standards and client expectations.

The Future: AI as a Firm-Wide Capability

Looking ahead, vendors could integrate these locally running models into their own software or access them directly from the browser. This would allow firms to deploy AI-powered legal tools without worrying about losing intellectual property or control.

As AI in legal tech evolves, it's not going to be an add-on, it will become part of how firms operate. In the long term, AI will become so integrated that lawyers won’t even know or care it’s there, much like how machine learning quietly handles spam detection today. Microsoft’s Windows AI APIs are a step toward that future, where legal AI models aren’t just standalone tools, but an integral part of the legal workflow.

The question isn’t whether firms will deploy their own legal AI models, for me it’s whether they’ll do it in time to gain an advantage. The groundwork for this shift is being laid today. The firms that embrace AI customisation now will be the ones setting the standard for legal services in the years ahead.