Swiss law firms and in-house legal teams usually do not compare Legartis because NDA review is fundamentally wrong, but because day-to-day work rarely stops at NDAs. As volume, contract types, and internal standards grow, three questions become decisive: Do we work directly in the document, are results traceable, and does the model scale without cost surprises?
CASUS is a Swiss legal AI platform built for exactly that reality: document work directly in Microsoft Word or in the web app, hosting in Switzerland or the EU, no data transfer to the US, with zero data retention and no human review.
Quick Overview: Who This Comparison Is For
Law Firms: Quality, Traceability, Standardization
For law firms, it is not only about speed, but also whether a review is traceable and repeatable internally. When multiple associates work on the same contract type, standards must be visible, deviations must be assessed consistently, and results must be transferred cleanly into the document. This is where “pure review” separates from a workflow that actually supports law-firm quality.
In-House Legal: Volume, Speed, Scaling Across Contract Types
In-house work often means many similar documents, changing templates, different counterparties, and tight timelines. What matters is whether the system scales across contract types without having to rebuild each process from scratch, and whether the work happens where the team already works: in the Word document.
Why Teams Look for Legartis Alternatives
When NDA Review Is Not Enough: More Contract Types, More Workflows
NDA review is a good entry point. In practice, DPAs, MSAs, procurement contracts, licenses, or side letters quickly follow. Then you need more than a list of findings, you need different workflows: check standards, prioritize risks, ensure quality and consistency, and in larger cases evaluate many documents in parallel.
When Per-Contract Pricing Slows Growth
As document numbers rise, a per-contract model often becomes a control problem: teams start counting, batching, or postponing reviews. That does not improve quality, it creates workarounds. In legal operations, scaling works better through predictable budgets than hard limits per document.
When Legal Wants to Work in the Document: Implement Results Directly in Word
Many tools deliver results in an interface that sits next to Word. In reality, that means: read findings, find the passage, adjust manually, fix formatting. Especially with long contracts, the context switch is the biggest time sink. Teams look for alternatives when they realize the bottleneck is not analysis, but implementation.
Legartis at a Glance: Strengths and Typical Focus
Legartis is often associated with structured contract review, especially for standardized checks around NDAs. For teams whose work matches that pattern and who intentionally keep implementation steps separate, this focus can make sense.
The comparison becomes relevant when you need not only review, but also standardization, different workflows, and direct document work.
CASUS as an Alternative: The Decisive Difference in Daily Work
Everything in Word and in the Web App – No Tool Switching
CASUS is designed so lawyers work where the document lives. That means: ask questions, find passages, get recommendations, and implement changes without copy-paste and without losing formatting. For many teams, this is the biggest productivity lever, because implementing changes in the document often takes more time than the analysis itself.
More Workflows, Not Just Contract Review
CASUS does not only cover review, but multiple workflows that typically happen back-to-back in law firm and in-house processes: check standards against a playbook, prioritize risks, finalize language and structure, integrate legal research when needed, and for large volumes create a matrix or extraction view.
Predictable Flat Pricing Instead of Contract Limits
When usage is not capped per contract, two things change: teams automate more consistently and also use workflows for smaller documents where it otherwise “would not be worth it.” Over time, that leads to more uniform outcomes and fewer errors across the board.
The 6 CASUS Features Explained Briefly
AI Chat with Agent Mode in the Document: Find Sources and Apply Changes
AI Chat answers specific questions about the document and links responses to relevant passages so you can jump directly to the right section. In Agent Mode, CASUS can execute changes in the document, for example inserting clauses or rewriting text, while respecting structure, numbering, and formatting.
Practical example: You want to know whether liability has a cap and where exceptions are defined. Instead of searching and scrolling, you ask directly, jump to the relevant clauses, and have a cap formulation inserted in the right place.
Benchmark: Make Standards and Deviations Systematically Visible
Benchmark compares a document against a reference standard based on your playbook or best practices and highlights deviations, gaps, and missing topic areas. CASUS can also insert suitable clauses at the right place with correct formatting and show an overall alignment percentage.
Practical example: An MSA is missing a clean termination mechanism or liability language is incomplete. Benchmark flags this as structured findings and provides a ready-to-insert addition.
Proofread: Ensure Consistency, References, and Drafting Quality
Proofread checks language and formal consistency, including Swiss spelling, terminology, definitions, cross-references, annexes, and typical final checks such as numbering, placeholders, or deadline contradictions.
Practical example: Before sending a contract to the counterparty, Proofread catches incorrect clause references, inconsistent party names, and open placeholders like [●] before they enter negotiations.
Risk & Quality Review: Prioritize Risks and Structure Results for Reporting
Risk & Quality Review identifies risks and red flags, assigns them to parties, and prioritizes severity as low, medium, or high. For each finding, CASUS provides concrete drafting options that can be inserted into Word directly, correctly formatted and without copy-paste.
Practical example: A supply agreement contains one-sided SLA penalties. CASUS prioritizes the risk, shows the impacted party perspective, and provides alternative fallback wording.
Legal Research
Legal Research is a mode within AI Chat for legal research and structured first assessments based on statutes, case law, and reliable legal sources. Results are prepared so they can flow directly into work product, for example as pro and contra arguments, risk drivers, and recommended actions including fallback options.
Practical example: You want to back up a negotiation position on a liability disclaimer. Legal Research delivers a structured argument line you can use in a negotiation email or an internal memo.
AI Data Room: Compare Many Documents, Extract Clauses, Gain Oversight
The AI Data Room analyzes many documents in parallel. You define what to extract, each column is based on your prompt. The result is usable as a table, ideal for Excel, due diligence, or compliance, including highlighting and prioritizing outliers based on defined criteria.
Practical example: In a portfolio of 120 supply contracts, you want to compare terms, termination notice periods, and liability caps. You get a clause matrix, spot outliers, and can renegotiate or report risks efficiently.
Legartis vs CASUS: Feature and Workflow Comparison
Contract Types: NDA, DPA, MSA, Procurement Contracts, Licenses, Side Letters
If your daily work is mostly NDAs, a focused review approach can be sufficient. But as soon as multiple contract types appear regularly, the question becomes whether you can cover standards, risk prioritization, quality checks, and bulk document work without building a new setup for every process. CASUS is designed for this breadth of workflows.
Output Quality: Structure, Prioritization, Traceability, Sources
In practice, the winning tool is the one that does not only give answers, but delivers them in a way you can implement in the document and defend internally. CASUS emphasizes linked sources, structured findings, and direct implementation in Word, including formatting and numbering.
Team Standardization: Playbooks, Benchmarks, and Consistent Outcomes
Standardization rarely fails because a playbook is missing, it fails in daily execution. Benchmark makes the standard visible, highlights deviations systematically, and enables consistent insertion of standard clauses. This supports uniform outcomes across teams without each person manually interpreting the playbook.
Pricing: Why CASUS Gets Cheaper as You Grow
Legartis Packages: Limited Per Contract
When packages are limited per contract, a practical ceiling emerges. A simple example without specific vendor pricing: if a team wants to review 60 contracts per month but a package only covers 30, you either incur additional costs or set internal rules about which contracts are “worth” reviewing. This often prevents legal AI from becoming a standard process and keeps it as an exception.
With a flat pricing model, the logic shifts: instead of counting, you focus on process quality. Teams apply workflows more consistently because each additional review does not trigger a variable barrier.
Who Should Choose What
Legartis Fits If …
your focus is clearly on standardized contract review for NDAs
your monthly volume is low and contract limits do not matter in practice
you deliberately want to work in a separate tool interface and accept implementation in the document as a later step
CASUS Fits If …
you want to work in Word and implement changes directly in the document
you need multiple workflows: Benchmark, Risk & Quality Review, Proofread, Legal Research, AI Data Room
you want to standardize across contract types and teams
you prefer predictable costs without contract limits, especially as volume grows
you value hosting in Switzerland or the EU, no data transfer to the US, zero data retention, and no human review
Conclusion: CASUS as a Legartis Alternative for Lawyers Who Want to Work Without Limitations
Those who use Legartis as a reference often are not looking for yet another review tool, but for a workflow that goes from finding the relevant passage to a cleanly formatted change inside the Word document, while enforcing standards and quality across the team. CASUS is built for exactly that: document work in Word or the web app, multiple workflows for legal day-to-day operations, and a model that does not become a brake as you grow.
FAQ
Is CASUS Just as Good for NDA Review
Yes. CASUS can analyze NDAs and apply different workflows depending on your needs: quick clause clarification via AI Chat, risk prioritization via Risk & Quality Review, or standard alignment via Benchmark if you have an NDA playbook. The practical advantage is that you can implement changes directly in the Word document instead of exporting findings.
What Is Required Technically for the Word Add-In
CASUS is designed for document work directly in Microsoft Word. For team usage, what typically matters is that Word is used and access to CASUS can be provisioned. The Add-in can be downloaded directly from the Microsoft Add-in Store or deployed by an admin. More details you can find in the CASUS Help Center.
How Do Hosting, Swiss DPA and GDPR, and Security Work
CASUS is hosted in Switzerland or the EU with no data transfer to the US. In addition, zero data retention and no human review are in place. For internal approvals in law firms and companies, these points are often central because they simplify data flow and access scenarios.
How Fast Is Setup and Onboarding
In practice, setup and onboarding mainly depend on whether you already have playbooks or standard clauses defined and which workflows you want to introduce first, for example Risk & Quality Review for quick negotiation prioritization or Benchmark for standardization. A sensible starting point is often to begin with one contract type and then expand to additional workflows and document types.
