Preview:
The AI Document Review Playbook
Pages 1 and 2. The full printable PDF is free.
More pages in the full checklist
Proofs 10 to 20, the evasion tells, the walk-away red flags and the side-by-side sheet for scoring three finalists out of 40.
The AI Document Review Playbook
A practical field guide for legal teams evaluating AI-assisted review in modern eDiscovery workflows. Learn how to justify AI adoption internally, deploy defensible review workflows, reduce review costs, and maintain court-ready transparency across TAR, CAL, and GenAI-assisted review.
Law firms
Lit support
eDiscovery teams
Partners
What's inside
- Why linear document review no longer scales.
- The difference between TAR, CAL, and GenAI workflows.
- Where the biggest review time savings actually come from.
- How to justify AI review to partners, clients, and courts.
- A 5-step deployment framework for AI-assisted review.
- ROI models and cost-saving benchmarks for law firms.
- Common AI review risks and how to avoid them.
Frequently Asked Questions
Everything you need to know about Venio's eDiscovery platform
1. What is AI-assisted document review in eDiscovery?
AI-assisted review uses technologies like TAR, CAL, and GenAI to prioritize, classify, summarize, and streamline document review workflows during discovery.
2. Is AI review accepted by courts?
Yes. Courts have broadly accepted technology-assisted review when firms use defensible workflows, validation testing, and documented human oversight.
3. What’s the difference between TAR, CAL, and GenAI?
TAR and CAL are used to prioritize and classify documents for review, while GenAI is commonly used for summarization, privilege log drafting, and issue spotting.
4. Can AI review reduce legal review costs?
Yes. AI-assisted workflows can significantly reduce reviewer hours, document volumes, and turnaround times compared to traditional linear review methods.
5. Do attorneys still need to review documents when using AI?
Yes. Human oversight remains essential for validation, privilege decisions, quality control, and defensibility in AI-assisted review workflows.
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