AI 模型和平台
机构统一调查数据和受管AI
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LexisNexis风险解决方案宣布 Acccurint One于2026年11月3日发布。 新平台为美国刑事司法机构提供了公司，伙伴和机构数据的一个调查环境，高级分析并管理AI.
该产品针对的是国家数据库、商业提供者、内部机构系统和其他技术进行不同调查时出现的零散现象。 在一个工作流程中，用户可以对照现有记录测试线索，寻找关系，排除错误线索，而不是按系统组装案件系统。
Haywood Talcove,LexisNexis风险解决方案政府的首席执行官，称 发布回应21世纪犯罪与他描述的调查技术模型之间的不匹配，后者主要植根于20世纪。 他宣称的目标是围绕案件工作安排技术，而不是要求调查人员调整工作以适应脱节的工具。
三个信息库
三个信息库位于Accurint One：来自LexisNexis风险解决方案的内容、相关伙伴提供的数据以及该机构提供的材料。 产品文件确定了记录管理、计算机辅助分发和监狱管理系统的可能来源。 一个机构还可以带入电子表格，用户创建的文件和BOLO，与更广泛的数据集进行分析。
调查人员可以搜索综合信息，就案件进行合作，建立调查时间表，使用绘图和链接分析，并应用分析。 AI支持的特性可以产生记录摘要，并检查关系网络进行连接。 界面将资源放在一个有定制选项的单一视图中，各机构可以通过产品页面请求演示。
LexisNexis 称模式识别可以协助对连环犯罪的调查，而其他特性可以使例行911服务呼叫更加有效，并在机构资源紧张时减少重复的手工研究。
人类监督和AI 治理
该平台赋予AI一个支持性角色：组织信息，寻找规律，并让可能的连接引起注意。 口译和由此产生的任何行动仍由受权用户负责。 该公司负责的AI刑事司法原则为Accurint One制定了五项标准：透明、负责、可理解、可证实和可追踪，统称为TRUST。
可解释性和可追踪性旨在使这种监督切实可行。 对于可能的调查线索，可解释性方法要求获取结果背后的信息和辅助数据，因此用户不必仅依赖产出。 预期调查员、分析员、指挥人员和记录人员将审查这些材料并运用其培训、经验和独立判断。
LexisNexis 称的保障措施将注重偏见的审查、文件、测试和监测与认证、用户核查和审计相结合，以进行访问控制。 造成意外偏差的潜在来源包括数据投入、模型开发和业务实施。
这使得可复审性成为Accurint One价值的核心。 整合可以简化建案的机理，但平台所宣称的操作模式并没有将问责推向AI：调查人员仍然必须审查辅助信息，并决定表面连接是否需要采取行动。
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AI Models & Platforms
Accurint One Unifies Investigative Data and Governed AI for Agencies
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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.
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