Summary To choose a metadata cleaning solution for your law firm, evaluate three things: accuracy (deterministic vs AI), scope (metadata cleaning vs data loss prevention), and deployment (desktop, cloud, or server). Rules-based metadata cleaning is the safer choice for legal work because it applies your firm's policy with certainty and produces the same result every time...

Part 1: The Case for Change R&D performance, Q1 FY2025 through Q2 FY2026 By Greg Ingino, Chief Technology Officer, Litera Eighteen months ago, I walked out of an Hg conference in Silicon Valley knowing that how we built software was about to change completely. We had just seen a demo of Cognition's Devin, the AI coding agent, and what followed has been one of the most...

Summary To remove metadata from email attachments in Outlook, open the Litera tab, clean with one click, and the attachment goes out without its hidden history. Litera detects risk automatically across classic Outlook, new Outlook, Outlook for Web, and Mac, flagging tracked changes, unresolved comments, and other hidden data before the email leaves Outlook. As Litera's...

Summary The Legal Knowledge Engineering team at Litera evaluated both Claude Sonnet 5 and Claude Fable 5 on legal tasks inside Lito, the award-winning Legal AI agent from Litera. All are former practicing lawyers across multiple jurisdictions and practice areas. Sonnet 5 is the faster, more responsive choice for pace-sensitive work like checking provisions and working...

AI Summary AI in legal RFPs creates exposure that most technology sections weren't drafted to find. General counsel updating outside counsel AI guidelines should expand the RFP technology section to cover three exposures beyond data security. The first is AI hallucination risk under ABA Model Rules 1.1, 1.6, 3.3, and 5.3. The second is privilege and confidentiality loss...

AI Summary Legal AI adoption inside corporate legal departments has surged past 78%, but actual daily use lags far behind. Most Legal AI tools for in-house teams sit idle within months of purchase. A single hallucinated citation or misread clause is often enough to kill lawyer confidence across the team, and nobody opens the tool again. This guide covers why Legal AI fails...

AI Summary This post is for GCs and senior M&A counsel at Fortune 500 and private equity firms evaluating their due diligence process. Generalist AI tools create material accuracy risk in high-value contract review, and these risks rarely surface until after a deal closes. Readers walk away knowing where that risk sits in their diligence workflow and what to ask outside...

AI Summary This guide walks CIOs, IT administrators, and legal ops leaders through safe legal AI deployment across a legal organization. It covers what to look for in a Legal AI platform for law firms and legal departments, why deterministic AI carries less risk on high-stakes legal work than probabilistic models, and how legal AI governance works in practice. It also...

AI Summary Can you trust AI to redline a contract? The answer depends on which kind of AI you're using. This page explains the difference between deterministic and probabilistic AI, why that distinction determines legal AI accuracy on high-stakes work, and how partners, associates, and general counsel can evaluate any AI contract redlining tool before relying on it for...

AI Summary Litera's Kira Grid Chat is a cross-document Q&A feature inside Litera's Kira Analysis Grid. It answers natural-language questions across every contract in a worksheet by reasoning over Kira's validated extraction data and linking back to specific extracted data points. General-purpose AI chat tools generate answers directly from document text, which is harder to...