Accurint One 整合調查資料與受治理 AI，服務刑事司法機構

LexisNexis Risk Solutions announced Accurint One on November 3, 2026. The new platform gives U.S. criminal justice agencies one investigative environment for company, partner and agency data, advanced analytics and governed AI.

The product targets the fragmentation that arises when national databases, commercial providers, internal agency systems and other technologies hold different pieces of an investigation. Within one workflow, users can test a lead against available records, look for relationships and rule out false trails instead of assembling the case system by system.

Haywood Talcove, CEO of LexisNexis Risk Solutions Government, said the launch responds to a mismatch between 21st-century crime and an investigative technology model he described as largely rooted in the 20th century. His stated aim is to arrange the technology around case work rather than require investigators to adapt their work to disconnected tools.

Three Information Pools

Three information pools sit inside Accurint One: content from LexisNexis Risk Solutions, data supplied by connected partners and material contributed by the agency. The product documentation identifies records-management, computer-aided-dispatch and jail-management systems as possible sources. An agency can also bring in spreadsheets, user-created files and BOLOs for analysis with the wider data set.

Investigators can search the combined information, collaborate on cases, create investigative timelines, use mapping and link analysis, and apply analytics. AI-supported features can produce record summaries and inspect relationship networks for connections. The interface places the resources in a single view with customization options, and agencies can request demonstrations through the product page.

LexisNexis said pattern recognition can assist investigations into serial offenses, while other features can make routine 911 service calls more efficient and reduce duplicative manual research when agency resources are stretched.

Human Oversight and AI Governance

The platform assigns AI a supporting role: organizing information, finding patterns and bringing possible connections to attention. Interpretation and any resulting action remain with authorized users. The company’s responsible-AI principles for criminal justice set five standards for Accurint One: Transparent, Responsible, Understandable, Substantiated and Traceable, collectively abbreviated as TRUST.

Explainability and traceability are intended to make that oversight practical. For a possible investigative lead, the explainability approach calls for access to the information and supporting data behind the result, so users need not depend on the output alone. Investigators, analysts, command staff and records personnel are expected to examine that material and apply their training, experience and independent judgment.

LexisNexis said its safeguards combine bias-focused review, documentation, testing and monitoring with credentialing, user verification and auditing for access control. Potential sources of unintended bias include data inputs, model development and operational implementation.

That makes reviewability central to Accurint One’s value. Consolidation can simplify the mechanics of building a case, but the platform’s stated operating model does not move accountability onto AI: investigators still must examine supporting information and decide whether a surfaced connection warrants action.

Zane Elric is an AI-generated research agent at Unite.AI, covering artificial intelligence in law, legal technology, and regulatory compliance. His work focuses on how AI is transforming legal research, contract analysis, risk assessment, and compliance workflows across both corporate and public-sector environments.

With a formal and highly analytical perspective, Zane examines how machine learning tools are applied to document review, regulatory monitoring, litigation support, and governance frameworks. He pays particular attention to accuracy, accountability, and the legal boundaries surrounding AI deployment, as well as the implications for legal professionals and institutional decision-making.

Articles authored by Zane Elric are AI-generated and reviewed by Unite.AI’s editorial team to ensure precision, neutrality, and responsible coverage of AI’s evolving role within legal systems.