In regulated work, an AI hallucination is a liability risk, not merely an inconvenience. A fabricated case citation, a compliance narrative built on a figure absent from the firm's PMS, or a cited provision that does not exist can reach a client, a court, or a regulator before being caught. Unplex is built specifically to prevent this.

Note: the underlying principle — no output without a named, verifiable source — is the same constraint described in What is Unplex?, Section 1. This article covers the technical mechanisms that enforce it.

ReAct agent architecture: every response passes through a Reason–Act–Observe loop. Unplex reasons about the question, takes an action (searching FedLex, BGer, or the firm's PMS/CRM), and observes the result before generating output. Intermediate results are checked for plausibility and consistency before any final output is produced.

Confidence and evidence scoring: each output is scored for confidence and evidence quality. Where confidence falls below a defined threshold, the response is restricted, rejected, or escalated for clarification rather than returned as a low-confidence answer.

Schema-validated tool calls: all tool calls — including database lookups and document retrievals — use schema-validated JSON outputs. Invalid results trigger automatic fallbacks or abort the query, preventing malformed or empty results from being passed silently into a response.

Tenant-specific guardrails: each workspace has configurable safety rules, including protection against prompt injection following OWASP Top 10 for LLM applications.

Human-in-the-loop escalation: where sources conflict or critical content cannot be resolved automatically, an explicit review step is triggered rather than an ambiguous answer being returned.

Every finding in an Unplex output carries a named source: the original FedLex provision, the BGer decision, the commentary reference, or the underlying PMS/CRM record can be opened directly. An item that cannot be verified is not included. This does not replace professional judgment — it provides the evidence needed to exercise it faster.

For documents drafted with other AI tools, or by associates using general-purpose AI, citation and compliance verification provides an additional safety layer: the finished document or documentation set is scanned for citations or entries that do not exist, have been repealed, or are inconsistent — catching hallucinated references before they leave the firm. See How to Verify Citations & Compliance with Unplex.

Related articles: Data Security and Privacy at Unplex · What is Unplex?