Discovery Review Is Broken. Here's How AI Fixes It — Without the Privacy Risk.
Generic AI tools can't safely run over sensitive discovery sets. A litigation-focused RAG system built on local models changes the calculus entirely.
The Discovery Problem Every Litigator Knows
Discovery review is one of the most time-consuming, expensive, and error-prone phases of litigation. Associates bill thousands of hours reviewing documents that could be processed in a fraction of the time. Critical documents get missed. Privilege logs are incomplete. And the whole process is a drag on the economics of litigation.
AI promises to fix this. But most AI tools introduce a problem that's arguably worse than the one they solve: privacy risk.
Why Generic AI Tools Fail in Discovery
When you upload sensitive client documents to a generic AI platform — ChatGPT, Claude, Gemini — you're sending that data to a third-party server. For most use cases, that's fine. For attorney-client privileged materials, confidential business records, and sensitive personal information, it's a serious problem.
Bar ethics opinions are still catching up to AI, but the consensus is clear: attorneys have a duty of competence and confidentiality that extends to how they handle client data with technology tools.
The Citadel Approach
Citadel is ForVerdict's answer to this problem. It's a Retrieval-Augmented Generation (RAG) system built on locally-deployed language models — meaning your discovery data never leaves your infrastructure.
Here's how it works:
- Your discovery set is ingested and indexed locally
- The RAG system retrieves relevant documents based on your queries
- A locally-running language model synthesizes answers from those documents
- Nothing is transmitted to external servers
The result is AI-powered discovery review with the privacy protections that litigation actually requires.
What You Can Do With Citadel
- Ask natural language questions across your entire discovery set
- Surface documents relevant to specific legal theories
- Generate privilege log entries from document metadata
- Identify inconsistencies across witness statements
- Build chronologies from scattered documents
The Bottom Line
Discovery review doesn't have to be a billable-hour black hole. But fixing it requires tools built for the specific constraints of litigation — not generic AI platforms repurposed for legal work.
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