Case Ready Intake AI

Overview

Case Ready Intake AI is the legal AI intake product discussed by Dan Driver in EP 40: Governance First: The Architecture Framework That Makes AI Auditable, Defensible, and 99% Cheaper.

Current Profile

The product is positioned as a bounded legal-intake organizer, not an attorney substitute. It helps users structure a case around narrative, timeline, and evidence while avoiding legal advice and unauthorized practice of law. Its distinctive architecture is that compliance-sensitive decisions are documented and routed through deterministic checks before LLM generation.

Key Characteristics

• Produces narrative, timeline, and evidence-list outputs for legal intake preparation.
• Avoids legal advice and uses UPL exposure as a central design boundary.
• Uses Python-based checks for dates, scope, warnings, and pass/fail decisions.
• Runs pre-flight checks before spending tokens on full generation.
• Uses runtime QA and human review to keep output aligned with the product charter.

Evidence

• Output boundary: EP 40: Governance First: The Architecture Framework That Makes AI Auditable, Defensible, and 99% Cheaper says the product produces narrative, timeline, and evidence list outputs.
• UPL boundary: EP 40: Governance First: The Architecture Framework That Makes AI Auditable, Defensible, and 99% Cheaper says a UPL exposure audit delayed launch and shaped the product’s constraints.
• Deterministic controls: EP 40: Governance First: The Architecture Framework That Makes AI Auditable, Defensible, and 99% Cheaper says Python handles dates, scope, warnings, and go/no-go decisions.
• Runtime review: EP 40: Governance First: The Architecture Framework That Makes AI Auditable, Defensible, and 99% Cheaper describes final AI checks against the charter and human review through GitHub pull requests.

Qualifications

The episode does not provide an external product audit, legal opinion, benchmark, customer outcome study, or cost accounting. Claims about the product’s launch, cost reduction, and defensibility remain source-scoped.

What Changed

• Initial product profile created as the concrete case for governance-first legal AI architecture.

Relationships

• Dan Driver - founder and architect associated with the product.
• Driver AI Agency - company behind the product.
• Governance-First Legal AI - architecture frame the product exemplifies.
• Deterministic Legal AI Controls - technical pattern used in the workflow.
• Unauthorized Practice Of Law AI Boundary - legal boundary the product is designed around.