Legal AI, architecture, and the work around the work.
Practical perspectives for law firms, in-house legal teams, legal operations leaders, and technologists working with AI, copilots, agents, MCP, governance, and intelligent workflows.
ChatGPT vs Claude vs Microsoft Copilot for Legal Teams
Comparing ChatGPT, Claude, and Microsoft Copilot for legal work? A practical framework covering security, context, tool access, and where each one fits.
Read article →Copilot Cowork for legal teamsMicrosoft Copilot Cowork for Legal Teams: A Practical Guide
What Copilot Cowork can do for legal teams, five use cases worth piloting, and the governance model to put in place before you delegate legal work to AI.
Read article →MCP for legal teamsMCP for Law Firms and Legal Departments: Architecture Guide
How Model Context Protocol fits legal AI architecture. What MCP is, what it is not, authorization design, and the questions to ask before exposing tools.
Read article →intelligent legal workflowsLegal Workflow Automation with AI: A Practical Guide
What separates intelligent legal workflows from basic automation. The seven layers, when to use rules vs AI, real examples, and the metrics that matter.
Read article →legal AI governanceLegal AI Governance: 10 Controls Before You Deploy
Legal AI governance starts before deployment. Ten concrete controls covering data, authorization, human review, logging, and agent actions, plus a matrix.
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