An AI-powered tool decreased report-writing time by 82%, allowing officers to enhance public safety.

Client: 

Axon Enterprise, Inc. (Axon) is a global leader in public safety technology, dedicated to empowering law enforcement and public safety professionals with innovative tools and solutions. Headquartered in Scottsdale, Arizona.

Problem Statement: 

Police officers spend a significant portion of their shifts writing reports, which reduces their ability to interact with the community. Axon sought to address this challenge by streamlining the report-writing process.

Results: 

• 82% reduction in time spent on reports.
• Enhanced work-life balance.
• Improved public safety.

AI Solution Overview:

Draft One, powered by Azure OpenAI Service, is an advanced AI tool designed to generate draft reports for police officers. By automating the report-writing process, the tool provides officers with an initial draft that can be quickly reviewed and finalized, significantly reducing administrative workload.

The tool transcribes body-worn camera audio and drafts high-quality narratives for police reports in seconds. 

This tool can be used with any body camera audio to transcribe and translate the incident into a draft narrative that is ready within minutes, significantly reducing the time spent on paperwork. 

References: 

1. Axon enhances public safety and cuts report-writing time in half using Draft One, an AI-powered solution built on Microsoft Azure. https://www.microsoft.com/en/customers/story/19236-axon-enterprise-azure

Industry: Public Safety

Vendor: Microsoft

Client: Axon Enterprise, Inc.

Publication Date: 2024

The post An AI-powered Solution to Empower Police Officers appeared first on StopCorruption.AI.

The implementation of AI in Hellenic Cadastre, responsible for Greece’s property records, reduced processing time from hours to 10 minutes, cut costs, and improved efficiency and transparency. This transformation boosted the Greek economy by enabling faster and more secure property transactions.

Client: 

Hellenic Cadastre, under Greece’s Ministry of Digital Governance

Problem Statement: 

The manual, paper-based property transaction process was slow and inefficient. Citizens faced delays of months to finalize property ownership, and the system burdened local registry offices with repetitive tasks, increasing costs and errors.

To streamline the process, Hellenic Cadastre wanted to introduce AI into the property buying process. 

Results: 

• Reduced processing time from hours to under 10 minutes.
• Cost per transaction assessment decreased from €15 to €0.11.
• 90% of transactions processed online, providing real-time transparency and data access.
• 94% of time saved on property assessments.
• 150 public servants are upskilled with AI literacy.

AI Solution Overview:

Hellenic Cadastre leveraged Azure OpenAI Service to:

1. Automate Document Analysis: AI reads, categorizes, and assesses property contracts, applying legal rules to streamline decision-making.
2. Digital Assistant: A chatbot answers citizen queries, reducing workloads at registry offices.
3. Predictive Analytics: Power BI integrates performance data for resource allocation and financial planning.

References: 

1. From months to days: Hellenic Cadastre speeds up land registry transactions with Azure OpenAI. https://www.microsoft.com/en/customers/story/20308-hellenic-cadastre-azure-open-ai-service

Industry: Public Services

Vendor: Microsoft

Client: Hellenic Cadastre, Greece

Publication Date: 2024

The post Accelerating Land Registry Transactions with AI appeared first on StopCorruption.AI.

By implementing AI-driven solutions, clinic transitioned from siloed operations to an integrated system enabling operations staff to optimally allocate patients, proactively reduce wait times, strategically load balance across facilities, and ultimately drive increased patient volume without sacrificing quality of care. 

Client: 

Cleveland Clinic

Problem Statement: 

In 2022 alone, the organization processed 303,000 hospital admissions and 270,000 surgeries. Despite these high volumes, critical operational data—bed management, staffing, and equipment usage—was fragmented across multiple systems. This resulted in limited insights, inefficient manual processes, and suboptimal resource allocation, hindering overall efficiency and patient outcomes.

Results: 

• A 75% reduction in the time required to assess and determine bed capacity.
• Over a 10% rise in the number of daily hospital transfers successfully admitted.
• A 20% boost in efficiency when assigning beds for transfer requests.
• Approximately a 1-hour reduction in the average time patients spend in the emergency department awaiting a bed each day.

AI Solution Overview:

Palantir deployed its Foundry platform to unify Cleveland Clinic’s disparate data sources into a centralized, actionable interface. 

The software integrates patient flow and workforce scheduling data, utilizing advanced AI and machine learning to provide unprecedented insights into optimizing hospital capacity management.

Key functionalities included:

1. Consolidation of bed management, staffing, and patient flow data from multiple systems.
2. AI models predicted patient admission trends, equipment needs, and staffing requirements, allowing preemptive adjustments.
3. Tailored interfaces provided actionable insights for caregivers, administrators, and operational leaders.
4. The solution accommodated Cleveland Clinic’s diverse and growing operational needs.

References: 

1. Cleveland Clinic / Palantir. https://www.palantir.com/impact/cleveland-clinic/
2. Palantir for Hospitals. https://www.palantir.com/offerings/palantir-for-hospitals/

Industry: Healthcare

Vendor: Palantir Technologies

Client: Cleveland Clinic

Publication Date: 2023

The post Enhancing Capacity Management at Clinic with AI appeared first on StopCorruption.AI.

By adopting a data-informed approach and leveraging AI fraud detection tools, the firm achieved an 85% fraud detection rate while maintaining a seamless customer experience. 

Client: 

A top five global financial institution (FI) offering a comprehensive suite of services: consumer banking and lending, commercial banking, corporate and investment banking, and wealth management. 

Problem Statement: 

The rise of instant payment channels brought significant opportunities but also exposed vulnerabilities to fraud. The FI needed to balance its fraud prevention measures with maintaining a seamless customer experience. The overarching goal was to create a data-driven fraud prevention strategy that minimized financial losses while preserving customer trust and satisfaction.

Results: 

• €1.7 million in attempted fraud prevented monthly.
• Achieved an 85% Value Detection Rate (VDR), significantly enhancing fraud detection capabilities.
• 50% faster alert resolution times.
• Enhanced customer experience by minimizing false positives and maintaining the seamlessness of instant payments.

AI Solution Overview:

NICE Actimize collaborated closely with the financial institution to enhance its fraud detection and prevention capabilities.

Advanced machine learning models were optimized to prevent performance degradation over time.

Fraud detection rates were preserved, ensuring high accuracy even as fraud tactics evolved.

References: 

1. Global FI prevents €1.7 million of attempted fraud monthly. https://www.niceactimize.com/Lists/CustomerSuccesses/Attachments/48/case_study_instant_payments.pdf

Industry: Banking and Financial Services

Vendor: NICE Actimize

Client: Global top five financial institution

The post Preventing Millions of Fraud with Anti-Money Laundering AI Solution appeared first on StopCorruption.AI.

An AI platform has reduced the resources needed to administer the process by an impressive 80%, streamlined operations, and improved service delivery.

Client: 

UK Department for Work and Pensions (DWP)

Problem Statement: 

The DWP faced inefficiencies in managing thousands of low-value, one-off invoices annually. The existing invoice handling process was heavily administrative, time-consuming, and prone to delays, adversely impacting the timely delivery of jobseeker training and delaying individuals’ return to work.

Results: 

• £2.5 million annual savings.
• Improved procurement compliance rates across the business.
• 10x efficiency gain in processing orders.
• 80% reduction in invoice processing resources.
• Improved ability to deliver training.

AI Solution Overview:

Since 2006, Basware has worked closely with the DWP to gain a comprehensive understanding of the department’s objectives and priorities. This collaboration was integral to addressing the department’s challenges effectively.

In 2007, as part of the DWP’s finance transformation program, Basware integrated its eMarketplace solution with Oracle’s ERP system. This integration formed the backbone of the department’s GSI Hub e-procurement platform.

Basware introduced an innovative LVP initiative to automate and expedite the procurement of jobseeker training services. Key features of this initiative include:

• Automated Sourcing: DWP officials can instantly source training services from pre-registered suppliers, eliminating the need for manual sourcing.
• Prompt Payments: Suppliers receive purchase orders and return invoices online, ensuring timely payments.
• Inclusive Market Access: SMEs, previously excluded from government contracts due to high entry costs, can now participate without additional financial barriers.

References: 

1. Department for Work and Pensions. Streamlining procurement to change lives. https://www.basware.com/en/why-basware/customers/department-for-work-pensions
2. e-Procurement Software Solutions. https://www.basware.com/en/solutions/e-procurement/

Industry: Government Procurement

Vendor: Basware

Client: UK Department for Work and Pensions (DWP)

The post Transforming Government Procurement with AI appeared first on StopCorruption.AI.

The AI solution enables fact-based, quality-assured information retrieval while adhering to user trust, transparency, and the human-in-the-loop principle.

Client: 

The Federal Ministry of Defence of Austria (BMLV) is the ministry in charge of all matters relating to military affairs, especially the Austrian Armed Forces.

Problem Statement: 

BMLV sought an AI solution that could deliver verified, traceable, and transparent fact-based responses while minimizing hallucination risks. The system needed to ensure quality assurance, align with human-in-the-loop principles, and provide customizable user access and interface features. However, no off-the-shelf solution met these stringent requirements.

Results: 

• High-Quality Responses: ChatZentDoc delivers accurate answers based on verified sources.
• Source Referencing: All responses include cited sources to foster transparency and trust.
• Seamless Integration: The solution connects to existing systems and updates the knowledge database daily.
• Customizable Interface: Users can filter queries and export responses with associated source documents.
• Feedback Functionality: A feedback feature allows continuous improvement of the solution.

AI Solution Overview:

IBM partnered with the Austrian Federal Armed Forces’ Central Documentation Department (ZentDok) to develop “ChatZentDoc,” a generative AI solution based on IBM watsonx.ai technology.

ZentDok has a long history of using IBM technology for data collection and has relied on the IBM Watson Explorer solution for natural language processing (NLP) since 2016. Building on this foundation, the BMLV chose to advance with IBM watsonx.ai AI studio technology for their new AI solution.

ChatZentDoc introduces an interface powered by NLP to deliver fact-based answers. Its custom-designed front end allows users to search the database and refine results using filtering options. Responses can be downloaded along with their source documents. By operating with daily updated information, ChatZentDoc ensures up-to-date accuracy. This functionality establishes it as an OSINT (Open-Source Intelligence Tool), adaptable for broader use within public administration contexts.

References: 

1. IBM develops watsonx-based generative AI solution to provide fact-based information for the Austrian federal armed forces. https://www.ibm.com/case-studies/the-federal-ministry-for-national-defence-bmlv

Industry: Public Administration and Defense

Vendor: IBM 

Client: The Federal Ministry of Defence of Austria

The post An AI Solution Delivers Fact-based Answers appeared first on StopCorruption.AI.

The AI solution enhanced access to information, improved user experience, and optimized resource allocation, enabling the council to better serve its community.

Client: 

South Waikato District Council (SWDC) is the territorial authority for the South Waikato District in New Zealand. Founded in 1989, the council acts as the governing body for the district, overseeing local infrastructure, public services and regulatory functions.

Problem Statement: 

The SWDC faced challenges in providing timely and accurate information to citizens and employees. Data was siloed across repositories, making it difficult to locate answers, sometimes requiring hours or even days to resolve queries. The council’s initial attempt to develop a virtual assistant failed due to technical limitations and inconsistent results. So the SWDC called upon IBM to help.

Results: 

• 91.5% accuracy validated across 300 test questions.
• Enhanced user interactions with natural language queries and conversational search.
• Improved functionality through document filtering with Watson Discovery.
• Increased transparency with integrated document URLs for deeper insights.
• Reduced employee workload, allowing resources to focus on community initiatives.

AI Solution Overview:

IBM collaborated with the council to develop a proof of concept (POC) for a smart virtual assistant. This innovative solution integrates IBM® watsonx.ai, IBM watsonx Assistant, and IBM Watson® Discovery to deliver a robust and intelligent system. 

The assistant leverages watsonx.ai to enhance the advanced intelligence features of watsonx Assistant, enabling it to provide precise and accurate answers to user queries. Additionally, Watson Discovery equips the solution with powerful data discovery capabilities, allowing it to efficiently search through archival materials and hard-to-access documents to uncover the required information.

With its foundation in generative AI and a focus on transparency, IBM and the council emphasized maintaining clarity and trust in every user interaction during the development process.

References: 

1. New virtual assistant gets it right with IBM watsonx. https://www.ibm.com/case-studies/south-waikato-district-council 

Industry: Public Sector (Local Government)

Vendor: IBM

Client: South Waikato District Council

The post The Territorial Authority Transformed Its Citizen Services by Implementing AI appeared first on StopCorruption.AI.

By integrating facial recognition with AI, biometric and conventional security systems have made security surveillance more effective and efficient in providing real-time data analytics. 

Client: 

Paris 2024 Olympics Organizing Committee

Problem Statement: 

The Paris 2024 Olympics prioritized safety for millions of attendees while ensuring smooth operations. Large-scale events like this face challenges such as unauthorized access, real-time threat detection, and managing crowds without delays. Increasing globalization and cyber threats further heighten security risks. 

Traditional methods often lack the accuracy and scalability needed, making advanced solutions like facial recognition essential for real-time identification, fraud prevention, and efficient access control.

Results: 

• Reduced risks of unauthorized entry and criminal activity.
• Security teams allocated resources effectively, improving response times.
• People in the crowd were recognised from lists of unreliable persons, even if masks hide their faces.
• Reduced the number of cybercrimes, financial and reputational risks.
• Facial recognition expedited visitor authentication at entrances, cutting wait times.
• Ensured safety of athletes.

AI Solution Overview:

RecFaces utilizes facial recognition technology powered by advanced AI algorithms to boost security by enabling real-time identification, preventing fraud, and simplifying access control processes.

Their AI-driven software, Id-Guard, enhances traditional video surveillance systems by incorporating identification capabilities within video streams, significantly extending the functionality of standard security systems.

References: 

1. Enhancing Olympics 2024 security with Recfaces facial recognition technology. https://www.sourcesecurity.com/tags/artificial-intelligence-ai/news/enhancing-olympics-2024-security-recfaces-facial-co-1603983074-ga.1721284692.html

Industry: Sports Event Security

Vendor: RecFaces

Client: Paris 2024 Olympics Organizing Committee

The post AI Algorithms Improved Security by Enabling Real-time Identification appeared first on StopCorruption.AI.

A company leveraged AI to analyze images and videos for detecting potential risks. By automating the extraction of critical data from visual and textual content, the company improved its efficiency in risk assessment and compliance monitoring for its clients.

Client: 

KPMG is a global network of professional services firms providing audit, tax, and advisory services. With a presence in over 140 countries and territories, KPMG serves businesses, governments, and non-profit organizations. 

Problem Statement: 

KPMG needed a robust solution to analyze large volumes of visual and textual data from images and videos to identify compliance issues, fraudulent activities, and other risks. Manual analysis was time-consuming, error-prone, and insufficient for handling the scale and complexity of modern data sources.

Results: 

• Reduced time required for risk analysis within two days.
• Achieved higher accuracy in identifying potential risks from images and videos. 
• Improved compliance.
• Streamlined compliance monitoring and reporting processes, saving significant operational costs.

AI Solution Overview:

KPMG integrated Azure Cognitive Services to enhance its AI capabilities across various functions. By incorporating Azure Cognitive Service for Speech into its Magna platform, the company automated the transcription of conversations, making them searchable through detailed transcripts. Azure Cognitive Service for Language helps KPMG extract and organize text efficiently from documents.

Using Azure Computer Vision, KPMG improves its ability to detect and analyze visual content, including leveraging optical character recognition (OCR) APIs to extract text from images and videos. Serving banking clients globally, KPMG deals with a workforce and clientele that often communicate in multiple languages, including regional slang and informal expressions. To address this, the company implemented Azure Translator within Magna, enabling both prebuilt and customized translation solutions.

To consolidate its capabilities further, KPMG adopted Azure Cognitive Search, which provides contextualized searching of unstructured data within customer ecosystems and enhances the accuracy of search results. Additionally, KPMG utilizes semantic search in preview mode—advanced machine learning models trained on extensive Bing query data—to deliver highly nuanced and contextually relevant search results across its indexed data.

References: 

1. KPMG helps banking customers identify financial risks by unifying data with Azure AI. https://www.microsoft.com/en/customers/story/1554364202574065104-kpmg-professional-services-azure-ai

Industry: Financial Services and Emotion detection

Vendor: Microsoft

Client: KPMG

Publication Date: 2022

The post AI Finds and Analyzes Images and Videos to Identify Financial Risk appeared first on StopCorruption.AI.

Leveraging the emotion detection AI tool, the research group from a leading academic institution achieved efficiency and accuracy in extracting insights, transforming the approach to financial data analysis.

Client: 

A research group from a renowned academic institution specializing in behavioral economics and finance.

Problem Statement: 

The research group aimed to analyze hours of financial-related video content to detect and quantify emotional cues impacting decision-making in high-stress financial environments. Traditional methods required extensive manual analysis, which was time-consuming, prone to bias, and lacked scalability. The challenge was to find an AI solution capable of processing large-scale video datasets with precision and efficiency.

Results: 

• Reduced data analysis time, allowing researchers to focus on insights rather than manual coding.
• Achieved more accurate and comprehensive conclusions, outperforming human analysis benchmarks.
• Developed a speaker recognition feature recognizing speakers from audio or video files.  

AI Solution Overview:

Imentiv AI’s Emotion AI leverages advanced deep learning algorithms to analyze video datasets in real-time.

Engineers designed a custom feature that enabled bulk video uploads and streamlined processing, minimizing manual effort and expediting the initial data preparation phase.

The AI facilitated the identification of emotions, personality traits, and other key factors, making it possible to uncover overarching trends and dominant patterns that would be nearly impossible to detect through manual analysis.

The platform provided comprehensive insights into emotional nuances, including valence (positive or negative sentiment) and arousal (intensity of emotional engagement).

By leveraging advanced AI capabilities, the platform delivered unbiased results, eliminating the influence of human subjectivity and ensuring research accuracy and reliability.

References: 

1. How Imentiv AI Enhanced Financial Research Efficiency: A Case Study. https://imentiv.ai/case-studies/how-imentiv-ai-enhanced-financial-research-efficiency-a-case-study/

Industry: Financial Analytics and Emotion Detection

Vendor: Imentiv AI

Client: A research group from a renowned academic institution

The post How Emotion Detection AI Enhanced Financial Research Efficiency appeared first on StopCorruption.AI.