Resources
Written by the people deploying them.
Traditional workflow tools like HighQ, iManage and Litera Transact run repeatable processes well but stall on unstructured work. AI agents handle the judgement-heavy work the templates can't reach. A guide to where each fits in a modern firm.
How to design compliance architecture for AI agents: identity, data boundaries, action authorisation, immutable audit, and policy-as-code. A reference architecture for legal, financial services, and government deployments.
When an AI agent queries your document management system, whose permissions does it use? For most platforms, the answer is a shared service account. That's a problem.
A technical analysis of the Model Context Protocol's security model, its gaps for regulated industries, and the governance controls needed to deploy MCP servers in compliance-sensitive environments.
The EU AI Act deadline for high-risk AI systems is August 2, 2026. Financial services, insurance, and legal firms deploying AI agents must act now on conformity assessments, technical documentation, risk management, and human oversight to avoid penalties of up to 35 million EUR.
How law firms can adopt AI without compromising SRA compliance, legal professional privilege, or client confidentiality. Covers regulatory requirements, the privilege problem with US-hosted tools, and practical private deployment architecture.
Audit trails, approval workflows, identity, data boundaries, and policy-as-code enforcement: a technical reference for AI agent governance in regulated industries.
A practical reference covering the regulations that apply to AI agent deployments in financial services, legal, and healthcare, from GDPR and FCA Consumer Duty to the EU AI Act and MiFID II.
Most AI agent demos show them booking restaurants. The actual hard problem is deploying agents where every decision needs an audit trail and a wrong answer has regulatory consequences.
