Glossary
AI for law firms, defined plainly.
The terms that come up in our work — voice agents, RAG, GEO, AEO, LiveKit, LangGraph, SIP trunks. No marketing spin, no acronym soup.
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AI legal intake
AI legal intake is the use of conversational AI — voice agents or chatbots — to qualify potential law-firm clients, capture structured matter data (matter type, jurisdiction, urgency, prior representation, conflicts), and create matters in a practice management system like Clio without manual re-keying. Done well, it shifts intake from a labor-intensive bottleneck to a 24/7 always-on process.
AI voice agent
An AI voice agent is software that answers phone calls and holds two-way spoken conversations with callers, then takes structured actions — qualifying leads, booking appointments, creating CRM records, transferring to a human — based on what the caller says. Modern agents combine speech recognition (turning audio into text), a large language model (deciding what to say next), and speech synthesis (turning the response back into audible speech), with all three running in real time so the conversation feels natural.
Answer Engine Optimization
Answer Engine Optimization (AEO) is the practice of optimizing content to win direct-answer placements in search engines — featured snippets, knowledge panels, "people also ask" boxes, and Google AI Overviews. Where traditional SEO targets the ten blue links and Generative Engine Optimization targets AI-generated answers in chat interfaces, AEO targets the structured-answer real estate inside the search results page itself.
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Intent classification
Intent classification is the natural-language-understanding task of mapping a user’s utterance to one of a finite, predefined set of intents — "book appointment", "ask pricing", "report a bug", "qualify a personal injury claim". Traditional conversational AI systems were built around intent classifiers as their central abstraction; modern LLM-based agents do this implicitly through the language model’s reasoning, but the concept still matters in production design.
Interactive Voice Response
Interactive Voice Response (IVR) is the traditional "press 1 for sales, press 2 for support" automated phone system — a finite-state routing tree that uses prompts and DTMF (touch-tone) inputs or limited speech recognition to direct callers to the right destination without a live operator. IVRs ruled business phone systems for thirty years; modern AI voice agents are progressively replacing them in contexts where natural conversation matters more than pure routing.
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LangGraph
LangGraph is an open-source framework, built on top of LangChain, for orchestrating stateful, multi-step LLM agents as directed graphs of nodes (steps) and edges (transitions). It is particularly useful when an agent needs branching logic, persistent state across turns, sub-agents, or conditional control flow — the cases where a simple "prompt the LLM in a loop" pattern breaks down.
LiveKit
LiveKit is an open-source real-time voice and video infrastructure platform. In the AI voice agent ecosystem, it has become the de facto underlying layer for production deployments — handling audio routing, turn detection, interruption handling, and SIP/telephony integration so agent builders can focus on the language model and tool-calling logic above. LiveKit is what powers the voice layer at Vasquez Law Firm in the Hodos360 reference deployment.
LLM agent
An LLM agent is software that uses a large language model as its decision-making layer to perform multi-step tasks autonomously. Unlike a single LLM call (which produces one response), an agent runs in a loop: it observes the current state, chooses an action (often by calling external tools or APIs), observes the result, and repeats — until the task is complete. This pattern is the foundation of modern AI voice agents, autonomous coding assistants, and many "AI workflow" products.