Automate PI Client Intake with a Custom Voice AI
No major voice AI provider specializes in legal intake for personal injury attorneys. Firms build custom systems using telephony APIs from Twilio and language models from Anthropic.
A custom build is necessary because generic voice assistants cannot handle specific legal terminology or the complex, branching logic of a PI client interview. The system must integrate directly with case management software like Clio or Filevine, which off-the-shelf tools do not support.
We built an intake system for a 7-attorney PI firm that handled 150 new inquiries per month. Their paralegals spent 20 minutes per call manually entering data. The AI system now qualifies leads and creates new case files in under 90 seconds, operating 24/7.
What Problem Does This Solve?
Most PI firms first try to solve after-hours intake with generic answering services or IVR systems from providers like RingCentral. These services can forward calls, but they cannot conduct a detailed intake. The operators are not legally trained and frequently miss critical details like the date of the incident or prior medical treatment, forcing paralegals to waste time re-asking basic questions.
A more technical firm might attempt to use a platform like Google Dialogflow. They quickly discover these tools require thousands of example conversations to train effectively and lack the sophisticated reasoning to handle a real, non-linear client conversation. Trying to connect Dialogflow to a legal-specific CRM like MyCase requires complex middleware that a small firm cannot build or maintain.
The core failure is that these tools are either too simple (IVR) or too general (Dialogflow). A PI intake requires specific legal context, dynamic questioning based on prior answers, and direct integration with the firm's central record-keeping system. Using a general-purpose tool results in high error rates, frustrated callers, and hours of manual data correction by paralegals, defeating the purpose of automation.
How Does It Work?
We begin by provisioning a new phone number through the Twilio API or porting your existing intake line. We then map your firm's exact intake script, typically 20-30 questions, into a state machine using Python. This ensures every question required for qualification is asked in the correct order, with branching logic for different case types like auto accidents versus slip-and-falls.
The live conversation is handled by Anthropic's Claude 3 Sonnet API. We use its function-calling capabilities to guide the conversation and ensure we capture specific entities. All AI responses are engineered to have a latency under 800ms to feel natural to the caller. The system transcribes the conversation in real time and can be tuned on your firm's specific terminology.
Immediately after the call ends, a separate process summarizes the conversation and extracts key data points into a structured JSON object. This data includes the claimant's name, phone number, incident date, injury description, and at-fault party details. Using httpx for asynchronous requests, we push this structured data directly to your case management system's API, creating a new matter in under 5 seconds.
The entire application is built as a FastAPI service and deployed on AWS Lambda, allowing it to scale from one call to one hundred simultaneously. Hosting costs for up to 1,000 intake calls per month are typically under $50. We implement structured logging with structlog for full auditability and configure CloudWatch alerts to notify your team of any integration failures.
What Are the Key Benefits?
Qualify Leads in 90 Seconds, Not 20 Minutes
The AI agent completes a full intake and creates a case file in under 90 seconds. Your paralegals are freed from hours of repetitive data entry.
Pay for Usage, Not Per User
A custom build avoids monthly per-seat SaaS fees. Hosting on AWS Lambda costs pennies per call, not hundreds per user per month.
You Own the Intake Logic and Data
We deliver the full Python source code to your firm's GitHub account. You are never locked into a vendor and can modify the intake script anytime.
Real-Time Alerts on Failed Intakes
We configure CloudWatch alerts that post to a Slack channel if the CRM integration fails or call volume drops unexpectedly. Nothing falls through the cracks.
Connects Directly to Your Case Management System
Native API integration with Clio, Filevine, and MyCase. No more copy-pasting notes from a separate system or dealing with messy email notifications.
What Does the Process Look Like?
Week 1: Intake Script Mapping
You provide your current intake questionnaire and read-only API access to your case management system. We deliver a detailed process flow diagram for approval.
Week 2: Core System Build
We build the voice AI agent and data extraction logic using the Claude API. You receive a private phone number to test the conversational flow.
Week 3: Integration and Deployment
We connect the agent to your CRM and deploy the system on AWS Lambda. You receive a runbook detailing the system architecture and maintenance procedures.
Weeks 4-6: Live Monitoring and Handoff
We monitor the first 100 live calls for accuracy and performance. After a 2-week stabilization period, we formally hand over the system and review the maintenance plan.
Frequently Asked Questions
- What does a custom voice intake system cost to build?
- The primary cost factors are the complexity of your intake script and the specific case management system we integrate with. A script with 15 linear questions is simpler than one with 40 questions and complex branching logic. Integrating with a modern CRM with a well-documented REST API is more straightforward than an older, on-premise system. We provide a fixed-price quote after our initial discovery call.
- What happens if the AI misunderstands a caller?
- The system is designed to handle ambiguity. If the AI cannot confidently extract a critical piece of information, like a phone number, it will re-prompt the caller up to two times. If it still fails, the agent apologizes and offers to transfer the call to a live person during business hours. A full audio recording and transcript of every call is saved for manual review.
- How is this better than using an offshore virtual assistant service?
- A custom AI provides perfect consistency, 24/7 availability, and enhanced data security. There is no risk of a human agent having a bad day or mishandling sensitive client information. The per-call cost is also significantly lower over time compared to paying a service per minute or per call. The AI follows your script exactly, every single time, ensuring no compliance steps are ever missed.
- How accurate is the transcription and data extraction?
- For structured data like names, phone numbers, and dates, the extraction accuracy is over 99% after tuning. For unstructured summaries of the incident, the quality is comparable to a trained paralegal's notes. The system is significantly more accurate than a general-purpose answering service operator who is not familiar with legal terminology and may be handling multiple calls at once.
- Can the system handle languages other than English?
- Yes, the underlying Anthropic and Twilio APIs support multiple languages, including Spanish. Building a Spanish-language intake agent requires a separate development track for prompt engineering, testing, and script translation. This would be scoped as a distinct feature during the discovery process and would extend the standard 3-week build timeline.
- What does the optional flat monthly maintenance plan cover?
- The maintenance plan covers proactive system monitoring, security patches, and dependency updates for libraries like FastAPI. It also includes rotating API keys and managing cloud infrastructure. You get a private Slack channel for support and up to three hours per month for minor changes to your intake script, such as adding or modifying a question. Major new features are scoped separately.
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