Help people who call a legal help hotline get screened, triaged, and routed to the right help through a voice-based AI assistant that works alongside human staff.
Each workflow in the Legal Help Commons produces a set of shared assets. Here is where each one stands for Voice AI Intake.
A checklist of every capability a voice AI intake system should have, organized by what happens during a call: greeting, consent, information gathering, classification, routing, safety escalation, and handoff. Use it to scope a build, write an RFP, or evaluate a vendor proposal. Select your system's scope level to see which capabilities apply to you.
Read the agenda →The quality bar a system must clear before it should be trusted with real callers. Organized into five gates: does it perform accurately, can callers actually use it, does it handle safety situations correctly, can staff work alongside it, and can the organization maintain it over time. Each gate has specific pass/fail criteria.
Read the standards →A bank of realistic caller scenarios that you run through your system to see how it performs. Each scenario includes the caller's situation, the correct classification, what good intake looks like, and what bad intake does wrong. Includes straightforward cases, ambiguous situations, crisis callers, and edge cases. Use it during development or for independent evaluation.
View the test suite (Google Sheet) →A technical blueprint showing how the pieces of a voice intake system fit together: how a phone call becomes structured data a human can act on. Describes each component (speech-to-text, conversation orchestrator, language model, text-to-speech, case management integration) and the design decisions that matter most.
Join the cohort to contribute →Case studies from teams that have built or are building voice AI intake systems. What they chose, why they chose it, what surprised them, and what they would do differently. Designed so the next team building this does not start from scratch.
Join the cohort to contribute →A hands-on course that walks a team through the decisions involved in building, deploying, and maintaining a voice AI intake system. Each module is built around a real decision the team has to make, and ends with that decision written down. We are looking for teams willing to go through a draft version and give us feedback.
Sign up to test the masterclass →The resources build on each other. The functional agenda defines what the system must do. The conformance standards define how well. The test suite provides the specific scenarios to verify it. The reference architecture shows one proven way to build a system that meets the specification. Case studies show how specific teams did it. The masterclass walks you through the whole process.
You do not need all of them. Pick the resources that match your role.
Not everyone interacts with legal help through a screen. Many of the people who most need help — older adults, people with limited English proficiency, people in crisis, people without reliable internet — are more likely to pick up a phone than visit a website. Legal help hotlines handle millions of calls a year, and most go to voicemail or end in long holds.
Voice AI intake is a system that answers a legal help hotline call, gathers enough information to understand the caller's situation, classifies the legal issue, checks basic eligibility, and routes the caller to the right service. The AI handles the initial screening. Human staff handle the advice, representation, and complex judgment.
This is not a replacement for human intake workers. It extends their reach. A voice AI system can answer every call on the first ring, collect the essential facts while the caller is engaged, and hand off a structured summary to the human team.
Who this serves: Legal help hotline callers, court self-help phone lines, pro bono intake programs, and any organization that receives more calls than its staff can answer.
The Voice AI Intake working group is developing the shared assets on this page. The cohort steers what gets built. Members shape the agenda, review standards, and contribute implementation experience.