Services
CRIME NABI for Modern Enterprise
AI Security Optimization by CRIME NABI
CRIME NABI, the crime prediction AI proven effective by Brazilian police, optimized for corporate security operations.
Visualize security resources and equipment placement → Optimize → Validate effectiveness, simultaneously enhancing safety and reducing costs.
We have previously implemented placement optimization for cameras, vehicles, and other assets with government agencies, confirming quantifiable deterrent effects. Meanwhile, private security sites face challenges like reliance on precedent and intuition, coupled with a lack of evaluation metrics for security effectiveness.
CRIME NABI supports the PDCA cycle for optimal deployment and operational improvement of multiple resources—cameras, robots, drones, vehicles—based on security effectiveness KPIs. The future of physical security lies in AI × human collaboration. We drive this transition through AI security optimization.
Value Proposition
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Cost Reduction and Labor Savings
Quantify staffing efficiency to eliminate unnecessary on-site presence and patrols. Achieve accountability and optimization simultaneously. -
Enhanced Security Quality
Visualize risks to create rational plans free from reliance on intuition. Improve safety and efficiency concurrently. -
Operational Efficiency (Planning to Day-of Operations)
High-speed standardized planning and replanning without specialized knowledge. Reduce preparation time and level out day-of operations.
Our Services
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Public Safety Risk Visualization Service and Crime Prediction Data Sales
・Crime prediction-based public safety reports/API provision
・Utilization in B2C applications
・Support for multinational corporations and logistics providers in site selection and safety assurance
Our crime prediction data is also utilized in a crime prevention smartphone app in Uruguay, South America.
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Robots × AI Security Collaboration
・Robot Patrol Route Optimization Based on Crime Prediction
・Case Study: Field Test with Boston University and Outdoor Autonomous Robots
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Drones × AI Security Solution
・Aerial security support ideal for monitoring difficult terrain and wide areas
For infrastructure companies such as oil plants and mines, frequent incidents of unauthorized intrusion and resource theft pose a serious challenge, leading to significant damage to facilities and equipment. Based on risk predictions from CRIME NABI, we provide a security solution combining drones with human security personnel. By utilizing drone-based security, we efficiently cover large areas, achieving both high-quality security and cost-effectiveness.
CRIME NABI for Crowd Control Security
Optimized for crowd control operations, the crime prediction AI “CRIME NABI” proven effective by Brazilian police.
Prevents dangerous crowd incidents with optimized security measures.
A new solution revolutionizing large-scale event security through cutting-edge AI and data analysis.
Fusing security expertise with science, it delivers next-generation crowd control methods that enhance safety while reducing costs.
Bringing quantitative metrics to the security industry.
Data-driven optimization.
Issue
The security industry faces labor shortages and rising costs, yet lacks metrics to evaluate “security effectiveness.” Resource allocation follows precedent within a billing system based on deployed resources.
CRIME NABI for Crowd Control quantifies the effectiveness of security guard patrols and deployment using a proprietary algorithm. It visualizes data showing where guards contribute to crowd control, enabling safety assurance while reducing waste. This achieves both human resource optimization and accountability.
Solution
Predict risks of accidents, chaos, and petty crime in advance at areas experiencing large crowds, such as countdown events, fireworks displays, and tourist attractions. By optimizing the placement of security personnel and surveillance cameras, we reduce security costs while maintaining both safety and service quality.
Predict crowd-related risks (accidents, disturbances, crime) at large-scale events and tourist destinations in advance. Optimize the placement of security personnel and surveillance cameras. Integrates with camera monitoring to reduce security costs while maintaining safety and service quality. Also features KPI-based visualization and evaluation of security operations quality, supporting the PDCA cycle for on-site improvements.
Implementation Example at a Marathon Event:
Security personnel are prioritized for deployment along the course at high-risk locations. Lower-priority areas (less crowded points) rely solely on AI camera surveillance, with mobile response teams dispatched for anomalies. Real-time analysis detects rising risks, enabling the security headquarters to immediately adjust deployment plans.
Value proposition
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Reducing Security Costs and Labor Savings
By evaluating and explaining the effectiveness of security personnel deployment based on numerical data, we can eliminate waste while ensuring safety. This achieves both optimization of human resources and accountability, enabling cost reductions through labor savings in security staffing.
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Improving Security Quality
Visualizing security effectiveness based on data and optimizing personnel deployment enables rational security planning that doesn't rely on experience or intuition. Plans backed by AI and data enhance safety while improving efficiency, ultimately leading to higher security quality.
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Streamlining Event Operations
Advanced accident and crime prevention utilizing cutting-edge AI becomes achievable without specialized knowledge. This significantly reduces time spent on security planning, contributing to more efficient preparation and smoother event operations on the day itself.
~Improving Safety and Reducing Costs Through Scientific Evidence~
CRIME NABI quantifies the effectiveness of security guard patrols and deployment using proprietary algorithms.
It visualizes data showing where guards contribute to crowd control, enabling objective verification of security plan effectiveness.
秋葉原ラジオ会館前での人流解析による
交通整理計画最適化実証実験について
本エリアでは、東京都が実施するスタートアップ連携事業「KING SALMON PROJECT（キングサーモンプロジェクト）」 (https://kingsalmon.metro.tokyo.lg.jp/）の一環として、人流測定カメラの映像データを活用した 人流・車両流動の解析に関する実証実験 を行っています。本実証は、千代田区の協力のもと、秋葉原駅周辺における 安全で安心なエリアづくりに資する知見の創出 を目的として実施されるものです。
1. 実証目的
本実証実験は、秋葉原駅周辺における以下の課題解決を目的としています。
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歩行者・自転車・車両が混在するエリアの状況把握と安全性向上に向けた検討
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混雑状況や通行特性を把握し、事故やトラブルが発生しやすい傾向の可視化
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人流・車両流動データを活用した、将来的な安全対策検討に資する知見の整理
取得したデータは、事故やトラブルの未然防止および誰もが安心して訪れることができる街づくりへの活用を目的として、本実証実験の範囲内で利用されます。
2. 個人情報の取扱方針
本実証実験において取得される映像データは、個人情報の保護および個人のプライバシー保護に最大限配慮して取り扱われます。
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映像は 人や車両の流れ・密度・動線等の分析 にのみ使用されます
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顔認識や個人を特定・識別する処理は一切実施していません
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特定の個人の行動や属性を把握することはありません
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分析後のデータは 統計的に処理された匿名データとして扱われます
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関係法令および自治体の指針に基づき、適切に管理 されます
来街者の皆さまのプライバシーや心理的な安心感にも十分配慮した運用を行っています。本実証実験は期間限定で実施されるものであり、実証期間終了後に、本実証の目的を超えてデータを利用することはありません。
3. 実験概要（取得データの内容等）
実証内容
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人流測定カメラ映像を用いた 人流・車両流動の把握および分析
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混雑状況・時間帯別傾向・リスクが高まりやすい状況の可視化
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分析結果を踏まえた 交通整理や安全性向上に向けた検討
主に取得・分析するデータ
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歩行者・自転車・車両の通行量
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時間帯別の混雑傾向
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交錯や滞留が発生しやすいエリアの傾向
※個人が特定される情報は取得・分析の対象ではありません。
実施期間・場所
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実施期間：令和8年2月初旬〜3月上旬まで（予定）
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実施場所：JR秋葉原駅 電気街南口周辺（千代田区）
本実証で得られた知見は、今後の 都市部における安全・安心な街づくり に活用される予定です。
4. 実施主体
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千代田区（事業協力）
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実証実施企業：株式会社Singular Perturbations