AI Esquire is based in Trumbull, Connecticut, and was founded by Eric Hoffman, Esq., a Connecticut trial attorney and former litigation practitioner. The company exists because the first contact with a prospective client is too important to depend on voicemail, inconsistent scripts, or a next-day callback queue.
Eric spent years in litigation practices where intake failures were visible in real time. Calls arrived while attorneys were in court. Prospective clients called after staff had left. Notes varied by employee. Follow-up depended on who saw the message first. Large firms could add people. Smaller firms needed a more reliable operating model.
His legal background includes plaintiff personal injury, civil litigation, subrogation, uninsured and underinsured motorist matters, premises liability, motor vehicle cases, and workplace injuries. Before founding AI Esquire, he also managed teams and built operational training programs.
The product is not designed to perform legal work. It handles a defined first layer: answer, collect, route, schedule, and summarize. The firm approves the workflow and retains conflicts review, professional judgment, advice, and representation decisions.
A narrow scope makes the system easier to test, supervise, and improve. It also makes the business case measurable. A firm can compare completed intakes, consultations, signed matters, and staff time before expanding coverage.
A useful intake system must work outside a polished demo. It must handle hesitation, interruptions, unusual answers, transfer failures, language changes, and calls that do not fit. It must create a record that a real team can review, and it must make exceptions visible rather than smoothing them over.
That is the standard behind Intake AI: controlled workflows, direct scheduling, transparent records, early-call quality assurance, and firm ownership of every consequential decision.
Built inside the problem, not beside it.
A working session begins with the intake failure your firm can describe and measure.
