Thousands of cases. One strategy.
Whether as claimant or in defense: one large-volume mandate, thousands of nearly identical cases. DEPLAW automatically extracts and clusters every incoming case, develops a unified strategy from it for the majority of proceedings – and keeps the client updated in real time throughout. Each case is only reviewed individually once it actually deviates from the pattern.
Back to the Law Firms overviewExample mandate on the platform
The starting point
Case-by-case review doesn't scale to thousands of cases.
Volume
Thousands of nearly identical cases arrive at the same time – whether as claimant or in defense, there simply isn't time for individual review.
Speed
Deadlines run across hundreds of parallel proceedings simultaneously, not one after another.
Consistency
Without a unified line, contradictory argumentation patterns emerge across hundreds of filings.
The process in three steps
From thousands of cases to one unified strategy.
DEPLAW maps the path from case intake to client reporting in three steps that build on one another. Each step takes over work that lawyers have traditionally done by hand in a classic large-volume mandate – from the first review to the ongoing report to the client. Using defense against incoming complaints as the example, here's what the process looks like in practice; the same AI extraction and clustering logic carries serial enforcement of a firm's own claims just as well.
Step 1 of 3 · Triage & clustering
Complaint triage & automatic clustering
Thousands of incoming complaints are read immediately, clustered by claim type and prioritized – before a lawyer opens the first case file. In no time, a confusing inbox becomes a structured, prioritized overview of the entire complaint volume in the large-volume mandate.
Avg. AI read time per complaint: a few seconds · 1 platform for the entire large-volume mandate.
Step 2 of 3 · Defense strategy
Unified defense strategy
The AI recognizes argumentation patterns across all complaints and proposes a unified defense from them. Cases that deviate from this pattern aren't forced into the template strategy — they're automatically escalated to full individual review.
A proposed strategy for a cluster consists, for example, of a template filing tailored to that specific claim cluster, an identified lead case with a prepared referral to the Federal Court of Justice (BGH), and calculated settlement ranges that the client is informed about.
Pattern recognition across case files
The AI compares the facts, legal basis and argumentation of every incoming case file against the entire body already captured – not just the most recent complaint – and so also recognizes patterns that only emerge across hundreds of case files.
Accounts for local case law
Nationwide waves of litigation play out before different courts with different rulings. The AI assigns every case to the court of jurisdiction and adapts strategy and argumentation to the local case law that actually applies there, instead of assuming a single nationwide line.
RAG instead of keyword search
An LLM-powered retrieval-augmented generation approach finds matching rulings and parallel proceedings running in tandem by meaning – through phrasing and factual context – not only when the exact same terms appear verbatim.
1 template filing for thousands of proceedings. More on the architecture behind the AI orchestration in theAgentic AI whitepaper.
Step 3 of 3 · Controlling & reporting
Client controlling & automated reporting
The client can see the status of all proceedings at any time – success rates, costs and forecasts. Reports are generated automatically, with no need for the firm to compile them by hand.
1 platform for firm and client.
Example · lawyer time per case
AI preparation per cluster instead of individual review of every complaint.
–80% lawyer time per case, at 94% coverage from the template strategy in the example mandate.
Example · from complaint intake to response
One process for thousands of parallel proceedings.
Technically, every complaint passes through five stations that map onto the three strategic steps: intake and AI triage form step 1, template strategy and lawyer sign-off form step 2 – client reporting closes the loop as step 3.
Adapts to your system landscape
For law firms in mass proceedings, we build the automation that makes thousands of similar complaints manageable in weeks instead of years.
Legal Data Technology · Mass proceedings projects
Automate your next large-volume mandate.
Model it as a workflow once, and the strategy scales to any number of proceedings – no coding required, beA natively integrated, hosted on German servers and TÜV-certified.
Book a demo for mass proceedings