Data Reporting
Sorting leads takes time, and too often that time goes to incomplete info, inconsistent review, and opportunities that stall. Deciding which cases to pursue, refer, or reject can slow intake and leave firms guessing about where to focus their efforts.
QualifyAI is Lawmatics’ newest beta feature, bringing artificial intelligence into the intake process in a way that’s practical, transparent, and built for law firms. Using your firm’s own data, it evaluates new leads and recommends next steps with clear reasoning, helping teams move faster and focus on the cases that matter most.
This session, hosted by Lawmatics co-founder and CEO Matt Spiegel and CTO Krijn van der Raadt, pulls back the curtain on the new beta feature and how it fits into the Lawmatics platform. Matt shares Lawmatics’ vision for building AI that supports real firm workflows, while Krijn demonstrates how to create a scoring model, review recommendations, and fine-tune results with feedback.
Time stamps of key takeaways
3:50 — Lawmatics’ approach to AI
Matt opens with Lawmatics’ broader vision for AI and why it’s critical to build automation that’s targeted and relevant. Rather than bolt-on tools, he explains, AI should live within the platform itself: aligned to real law firm workflows and transparent about how decisions are made.
14:48 — Setting up your lead scoring model
To kick off the demo, Krijn walks through how to create a qualification profile using the data already in your account. At setup, the system reviews past leads, pipelines, and forms to suggest criteria for what defines a qualified lead in each practice area. From there, QualifyAI references those firm-defined standards to recommend next steps — whether to pursue, reject, or refer a matter.
21:40 — How QualifyAI makes its recommendations
Next, Krijn shows how the tool evaluates incoming leads in real time. Each recommendation includes a confidence level and a short explanation of why — factors like case type, location, or claim details — so firms can see the reasoning before deciding how to proceed.
28:00 — Giving feedback to your AI model
Users can review QualifyAI’s recommendations, mark them as accurate or off-base, and add notes for context. That feedback feeds directly back into the system, refining future results. Krijn demonstrates how updating a single “Chase” call to “Refer Out” instantly adjusts how similar leads will be handled going forward.
40:00 — Q&A
The session wraps with questions on multi-practice support, privacy safeguards, and how QualifyAI fits into the client experience. Matt and Krijn also share a glimpse of what’s next for AI in Lawmatics, including tools designed to further enhance intake and lead management.
Webinar slide deck
Legal analytics transforms how you handle the mountains of court records, client information, and case documents competing for your attention. Instead of drowning in data, it allows you to organize it, spot trends, and work smarter.
And the numbers speak for themselves: A 2024 Lex Machina survey notes 68-70% of law firms use legal analytics, with 70% of those users citing improved litigation outcomes as the primary driver. If you're not using it yet, you're missing out on opportunities to increase your operational efficiency.
In this guide, we’ll cover everything you need to know about legal analytics, from the key benefits to the challenges of its applications.
Types of Legal Analytics Measurements
Legal analytics uses large datasets to draw insights, identify patterns, and predict outcomes. Often powered by AI algorithms, analytics tools parse court records, client data, and internal firm information to make connections that would otherwise take weeks or months to do manually.
Legal analytics come in three types: