Public‑service chatbots and court‑facing AI assistants are specialized conversational systems used by governments, courts, and legal aid organizations to streamline access to information, triage cases, and assist with routine procedural tasks. As of 2026‑01‑04 these systems are increasingly deployed—but also subject to tighter regulatory scrutiny and practical constraints around reliability, data protection, and auditability. Key risks include hallucinations or incorrect legal guidance, sensitive data leakage, opaque decision trails, and unclear lines of human responsibility. Tool and platform trends that shape this space include enterprise virtual assistants and multi‑agent orchestration (IBM watsonx Assistant, Microsoft 365 Copilot), private and customizable LLM infrastructure (Cohere), managed agent platforms that integrate enterprise systems (Synthreo/BotX), and no‑code or low‑code builders that prioritize rapid, domain‑specific deployments with audit features (Cimba.AI, Anakin.ai). Conversational foundations such as Anthropic’s Claude family supply core dialogue and reasoning capabilities, while autonomy platforms like Shield AI illustrate the importance of deterministic middleware, verifiable behaviors, and secure execution for mission‑critical contexts. Effective public and court use requires a combination of technical and governance controls: model selection and testing against domain benchmarks, retrieval‑augmented approaches with provenance, strict access controls and data minimization, human‑in‑the‑loop escalation, continuous monitoring and red‑teaming, and compliance workflows that generate auditable logs for regulators. Regulatory compliance and AI security governance tools must therefore be embedded into deployment lifecycles rather than treated as afterthoughts. The result is a pragmatic, risk‑aware approach that enables useful automation while preserving accuracy, privacy, and legal accountability.