AI that answers inbound calls, qualifies cases, checks conflicts, and routes qualified leads to the right attorney—while your team focuses on clients already in the door.
Quick Answer
Legal intake automation uses AI to handle the first steps of converting a prospect into a signed client—without manual staff time at each step. An AI system answers inbound calls, extracts case details, scores leads against your firm's criteria, checks conflicts, and routes qualified cases to the right attorney automatically. The result: faster response times, consistent qualification, and more cases signed without adding headcount.
Last updated: July 30, 2026
A prospective client calls your firm at 7 pm on a Friday. If your intake team isn't available, that call goes to voicemail—and a competing firm's AI answers immediately. Studies consistently show that speed-to-response is one of the strongest predictors of whether a prospect signs. Every hour of delay cuts conversion odds.
Clio's annual Legal Trends Report—the most comprehensive study of law firm operations in North America—consistently finds that response speed is among the strongest predictors of intake conversion. Prospective clients typically contact multiple firms and engage with the first to respond meaningfully. Every hour without a response is an opportunity your competitors can claim.
Manual intake also introduces inconsistency. Different staff members ask different questions, weight criteria differently, and sometimes miss conflict checks under volume pressure. A prospective client who slips through without a proper conflict screen is a malpractice risk. One who doesn't meet your minimum case threshold but gets passed to an attorney wastes billable time.
An automated intake system doesn't go home, get tired, or deviate from protocol. It asks the same qualifying questions every time, scores every lead against the same criteria, runs the conflict check before the case enters your pipeline, and hands the attorney a structured summary—not a post-it note.
An AI receptionist for a law firm answers inbound calls 24/7, the same role a human receptionist or a traditional answering service fills. The difference shows up after the call connects. A traditional answering service or virtual receptionist takes a message and passes it to staff for follow-up. An AI receptionist built for legal intake goes further: it conducts a structured intake interview, transcribes the conversation, scores case viability against your firm's criteria, checks for conflicts, and routes qualified leads directly to the right attorney—before a human ever touches the file.
That distinction matters because message-taking and case-qualifying are different jobs. A receptionist or answering service can tell you someone called; it can't tell you whether the case clears your statute-of-limitations window, matches your minimum damages threshold, or conflicts with an existing client. An AI receptionist for legal intake answers that call and makes that determination in the same conversation.
Never miss a lead because it came in at midnight. Our voice AI answers inbound calls, conducts a structured intake interview, and transcribes every word—so the conversation is ready for attorney review when they open their inbox at 8 am. Web chat intake available in the same system.
The AI evaluates each intake against your firm's criteria—statute of limitations, minimum damages, jurisdiction, practice-area fit—and assigns a viability score. High-scoring cases route instantly to the right attorney or practice group with a structured summary. Low-scoring cases receive a courteous decline or referral, automatically.
Before a case enters your pipeline, the system screens it against your conflict database. Integration with Clio, MyCase, PracticePanther, or a custom conflict list means no manual lookup required. Potential conflicts flag for human review before the intake is completed—protecting your firm without slowing the process.
After a qualified intake, the system sends a secure document request to the prospective client—medical records, incident reports, prior correspondence—and processes returned files with AI extraction. Structured summaries land in the case file before the attorney's first call, cutting prep time significantly.
After a settlement announcement or advertising campaign, inbound volume spikes instantly—and manual intake can't scale with it. An AI intake system handles simultaneous calls, extracts incident details, calculates statute of limitations windows, screens for prior representation, and routes qualified leads to the right attorney in minutes. You capture the full wave without hiring a surge staffing team.
Sensitive intake requires consistency and empathy. Voice AI handles the initial information gathering with a calm, patient tone—collecting party details, children's ages, asset overview, and urgency signals—then hands off to an attorney who already knows the situation. Estate planning intake collects asset types, family structure, and existing documents before the consultation so the attorney can focus on strategy, not data collection.
Time is critical when someone calls a criminal defense firm—often from a courthouse or after an arrest. AI intake captures charges, jurisdiction, court date, and any co-defendants immediately, flags high-urgency cases for same-day attorney callback, and ensures conflict checks run before any engagement begins. Immigration intake can collect country of origin, visa history, and pending deadlines to pre-qualify cases before consultation.
In-house legal departments and litigation-support teams route a different kind of volume than a plaintiff-side firm: subpoenas, discovery requests, and outside-counsel matter intake, all needing consistent triage before a deadline. AI intake logs each incoming request, flags response deadlines, checks it against active matters and conflicts, and routes it to the assigned attorney or legal ops team with a structured summary—the same conflict-check and CRM-routing pipeline described above, applied to corporate and enterprise legal ops workflows instead of new-client intake.
A prospect calls, submits a web form, or starts a chat. The AI intake layer responds immediately—24/7, with no hold time and no voicemail. Voice calls trigger a conversational AI interview; web and chat flow through the same qualification logic.
The AI conducts a structured intake interview, collecting contact information, matter type, incident date, jurisdiction, opposing parties, and any prior legal representation. Every word is transcribed and retained for attorney review.
Each intake is evaluated against your firm's configurable criteria: statute of limitations window, minimum claimed damages, geographic jurisdiction, practice-area fit, and any disqualifying factors. Leads receive a viability score before a human ever sees them.
Before the case enters your pipeline, the system screens it against your conflict database—integrated with Clio, MyCase, PracticePanther, Filevine, or a custom conflict list. Potential conflicts flag for human review; clear cases continue automatically.
Qualified leads route to the right attorney or practice group with a structured summary: intake transcript, viability score, conflict check result, and flagged statute-of-limitations risk. The attorney walks into the first call fully briefed.
Unqualified leads receive an empathetic, professionally worded decline or referral. Qualified prospects receive a document request or consultation scheduling link automatically. No lead goes without a response, regardless of staff availability.
This scoring step is deliberately rules-based rather than free-generated text—an intake decision is exactly the kind of output that has to be auditable and can never be quietly hallucinated. We built the same pattern for a different regulated eligibility problem in the Live Oak Home Access case study: a ten-question intake maps deterministically to funding programs, with no LLM in the eligibility path.
Not all legal intake solutions are built the same. Whether you are evaluating vendors or planning a custom system, these six criteria separate effective intake software from expensive voicemail.
Prospective clients call when they need help, not when your staff is available. Intake software must handle after-hours calls, weekends, and volume surges without adding headcount or routing to voicemail.
Generic intake tools apply one-size-fits-all rules. Look for systems where you define the criteria: minimum case value, SOL windows, geographic coverage, and practice-area fit—matched exactly to your firm's intake standards.
Any intake system handling client information needs encrypted storage, role-based access controls, audit logging, and a signed Business Associate Agreement (BAA) from the vendor. Confirm BAA coverage before selecting any software.
Qualified leads should create draft matters directly in your case management system—Clio, MyCase, Filevine, PracticePanther. Manual re-entry between intake and CMS introduces errors and delays that erode the ROI of automation.
The intake system must screen against your conflict database before a case enters the pipeline. Post-intake conflict discovery wastes attorney time and creates malpractice exposure. Integration with your existing matter list is non-negotiable.
The best intake automation knows when to hand off to a human. High-value, urgent, or emotionally complex cases should route to a live attorney immediately—not enter a queue. Configurable escalation thresholds are essential.
Off-the-shelf legal intake solutions—Clio, MyCase, Lawmatics, Gavel, and similar platforms—are real, credible products, and for many firms they are the right call. The honest tradeoff is what you give up in exchange for faster setup: your scoring logic runs inside their rule builder, your workflow bends to their intake form structure, and every added user is another per-seat license. Here is where each approach actually wins.
Most firms evaluating legal intake solutions are really choosing between these two paths, not between vendors. Moon Sherpa Labs builds the second—a system designed around your firm's existing intake criteria and case management stack, not a vendor's template.
Moon Sherpa Labs is based in Austin, Texas. Our first production legal intake deployment—the Archuleta Law Firm case study below—was for an Austin firm, built and proven on real caseloads before we offered it to other clients. Being local means we can sit with an intake team in person, watch how calls actually get handled, and design the scoring and routing logic around the way your firm really works.
The same system serves law firms across Texas and nationwide on a remote-first model—Dallas, Houston, San Antonio, and firms outside Texas entirely get the same scoping, build, and support process, with in-person availability for Austin-area clients when it adds value.
Case Study
Full disclosure: our founder's family firm—and our first production deployment. Everything below ran on real caseloads before we offered it to clients.
Archuleta Law Firm was buried in manual intake. Leads came in through phone, web form, and referral—with no consistent qualification process and no visibility into pipeline health. Staff were spending hours each week on intake calls that often ended in unqualified cases. Response time to qualified leads averaged several hours.
We deployed an AI intake layer: voice capture for inbound calls, structured case scoring against practice-area criteria, conflict check integration with their case management system, and automatic routing of qualified leads to the right attorney with a summary brief. Unqualified leads received an automated, empathetic decline.
“Before Moon Sherpa Labs, our intake team was drowning—leads slipped through the cracks, follow-up was inconsistent, and we had no visibility into our pipeline. Now, every lead is scored, prioritized, and our response time dropped from hours to minutes.”
Yes—when built correctly. Moon Sherpa Labs designs intake systems with HIPAA-compliant data handling: encrypted storage, access controls, BAA-covered infrastructure, and no unnecessary retention of protected health information. All AI processing happens in compliant environments. Every firm's obligations differ—consult qualified legal counsel for your specific requirements. Read our guide to HIPAA-compliant AI for law firms →
The AI extracts structured data from the intake conversation—incident date, jurisdiction, claimed damages, opposing party, prior representation—and scores each lead against configurable criteria: statute of limitations windows, minimum case thresholds, geographic coverage, and practice-area fit. Leads above threshold route to the right attorney with a summary. Leads below threshold receive an automated, courteous decline or referral.
Yes. We integrate with Clio, MyCase, PracticePanther, Filevine, and most practice management systems via API. The conflict check uses your existing matter database, and qualified leads create draft matters directly in your case management system—so nothing requires a second data entry step. For firms on proprietary software, we work with available APIs or file-based exports.
A focused intake system—voice AI, case scoring, conflict check integration, and CRM routing—typically takes six to ten weeks from scoping to go-live. Complexity grows with the number of practice areas, integrations required, and compliance constraints. We always start with a scoping conversation before committing to a timeline. Book a free strategy call to get a realistic estimate.
An answering service captures a message and passes it to staff for follow-up. Automated legal intake qualifies the lead, scores the case, runs the conflict check, and routes the intake brief to the right attorney—without any staff involvement at each step. The result is not just faster message-taking; it is a completed qualification decision delivered in minutes, at any hour, with consistent criteria applied to every lead.
An AI receptionist for a law firm answers inbound calls the same way a human receptionist or answering service would, but it doesn't stop at message-taking. It conducts a structured intake interview, extracts case details, scores viability against your firm's criteria, checks for conflicts, and routes qualified leads to the right attorney—all in the same call, without staff involvement at each step.
Yes—our legal intake automation includes a voice AI front end that answers inbound calls 24/7, the same role a human receptionist or answering service fills. The difference is what happens after the call is answered: instead of just taking a message, the AI transcribes the conversation, extracts case details, scores viability against your firm's criteria, checks for conflicts, and routes qualified leads directly to the right attorney—all before a human ever touches the file.
Yes. In-house legal departments and litigation-support teams use the same intake pipeline for a different job: logging subpoenas and discovery requests, flagging response deadlines, checking new matters against active conflicts, and routing each item to the assigned attorney or legal ops team with a structured summary. It's the same conflict-check and CRM-routing engine described above, configured for corporate and enterprise legal ops workflows instead of new-client intake.
Law firms typically choose among three types of legal intake solutions: live answering services that take a message for staff to follow up on later, standalone intake software that your team operates manually, and AI-driven intake systems that answer, qualify, conflict-check, and route cases automatically without staff involvement at each step. Moon Sherpa Labs builds the third category—a complete automated pipeline, not a message-taking service or a tool your staff still has to run by hand.
It depends on how standard your intake process is. Off-the-shelf legal intake software—Clio, MyCase, Lawmatics, Gavel, and similar platforms—gets you live in days at predictable per-seat pricing, and is the right call if a template covers your workflow well. A custom-built system costs more upfront and takes longer to launch, but the scoring logic matches your firm's actual criteria instead of the closest preset in a vendor's form builder, it connects directly to whatever case management system you already run, and there's no per-seat license as you add staff. High-volume, multi-practice-area, and corporate legal ops workflows are where a generic template usually stops fitting cleanly.
Yes. Moon Sherpa Labs is based in Austin, Texas, and our first production legal intake deployment was for an Austin firm—but the engagement model is remote-first. Firms in Dallas, Houston, San Antonio, and anywhere else in the country get the same scoping, build, and support process as Austin-area clients, with in-person meetings available locally when it adds value.
Book a free 30-minute strategy call. We'll map your current intake workflow, identify where leads are slipping through, and show you what an AI intake system would look like for your firm.