Intelligent Data Analysis

Veraqor’s AI solutions extract insights from diverse data, enhancing business competitiveness with advanced language models for generic and specific requirements.

Growth in Gen AI

$128B

is the projected value of the generative AI market by the end of 2024.

30%

of generative AI users can clearly identify its practical applications.

70%

of Copilot users report significant productivity improvements.

What You Can Do

Overcoming the inability to extract meaningful insights from data to drive informed decision-making.

Transforming complex datasets into actionable insights allows organizations to unlock valuable information from both structured and unstructured data, facilitating informed decisions that enhance performance and strategic planning.

Addressing limited understanding of patterns and trends to enable proactive strategies.

Advanced machine learning solutions can uncover hidden patterns and trends within large datasets, enabling organizations to adopt proactive strategies, adapt to market changes, and stay ahead of the competition.

Mitigating underutilization of data to ensure no growth opportunities are missed.

By harnessing the full potential of data, organizations can identify hidden value and insights, ensuring they capitalize on growth opportunities that may have otherwise gone unnoticed, driving innovation and expansion.

Reducing high operational costs due to ineffective data management to optimize resource allocation.

A tailored data analysis strategy can streamline data processing and management, enhancing overall operational efficiency. By reducing costs associated with ineffective data handling, businesses can optimize resource allocation and improve their bottom line.

Technical Capabilities

Our Partnerships

PRimo-RPA-white

Growth Recognition

CL-KSA
USA

See How Organizations Are Innovating

Situation

Cineplex, a leading media company, faced inefficiencies in manual business processes across departments, resulting in over 30,000 hours annually spent on repetitive tasks. This impacted areas like finance and guest services, necessitating a solution to streamline operations and enhance productivity.

Solution

Cineplex adopted Microsoft Power Platform, utilizing Power Automate for RPA and AI-driven copilots. Led by Bo Wang, the team developed over 1,700 Power Automate flows, creating 400+ automation solutions. These included scalable RPA desktop flows and AI-powered tools for tasks like ticket refunds and customer inquiries.

Impact​

The implementation saved Cineplex over 30,000 hours annually, allowing employees to focus on strategic tasks. AI-driven copilots and automated workflows reduced handling times for ticket refunds and inquiries, improving efficiency and satisfaction. The success of these projects fostered a culture of innovation, driving further interest in generative AI capabilities.

Situation

Gunnebo faced challenges in properly analyzing log data generated by their security devices. The manual log analysis process was time-consuming and complex, causing bottlenecks and inefficiencies. Skilled engineers were required to spend significant time sifting through log data, which hindered the company's ability to promptly address device performance issues.

Solution

Gunnebo partnered with Microsoft to implement Azure OpenAI Service, leveraging the GPT-4 model to streamline and automate log analysis. This AI solution allows Gunnebo to collect and standardize log data from various sources, such as telemetry, raw log files, and mobile app data. Using a web-based application, engineers can now use GPT-4 to quickly analyze log files, generate summaries, and detect abnormal behaviors.

Impact​

The adoption of GPT-4 has transformed Gunnebo's operations, making log analysis ten times more precise and reducing the analysis time from hours to seconds. This has led to improved efficiency for engineers, who can now focus on higher-value tasks. Customers benefit from enhanced device monitoring, operation, and maintenance, leading to better security and performance of Gunnebo's products.

Situation

PWN struggled to manage extensive data stores essential for monitoring water quality and operational efficiency. Their existing on-premises SAP system couldn't handle the complexity of their needs, and integrating disparate systems for better asset management and customer communication was a challenge.

Solution

PWN migrated its SAP estate, including ERP, BW, CRM, and IoT water management data, to Microsoft Azure. This unified platform facilitated seamless data management and improved visibility. Power BI was used for data visualization, enhancing asset management and customer communication. Azure also enabled rapid innovation by allowing quick creation and removal of test environments.

Impact​

The migration to Azure resulted in significant cost savings, enhanced data security, and compliance with European regulations. The improved data extraction and visualization capabilities optimized asset management and operational efficiency. Predictive analytics from integrated IoT data helped PWN address climate change challenges and optimize water usage, leading to better service quality and customer satisfaction.

Generating Business Value Across Functions

Human Resources Talent Analytics
Utilize Generative AI to analyze employee data, performance metrics, and industry trends. AI can identify top talent, predict employee turnover, and recommend personalized development plans, helping organizations retain and develop their workforce effectively.
Advanced Predictive Analytics for Retail
Leverage Generative AI to analyze sales data, customer behavior, and market trends. By generating predictive models, AI can forecast future sales, optimize inventory management, and personalize customer experiences, resulting in higher sales and customer satisfaction.
Real-Time Financial Fraud Detection
Deploy Generative AI to analyze transactional data and detect anomalies in real-time. By learning from historical data and identifying unusual patterns, AI can flag potential fraud cases promptly, reducing financial losses and enhancing security measures.
Enhanced Cybersecurity Threat Detection
Implement Generative AI to continuously monitor network traffic and user behavior for signs of cyber threats. By analyzing large volumes of data in real-time, AI can detect and respond to potential security breaches faster than traditional methods, minimizing risks and safeguarding critical data.
Personalized Healthcare Treatment Plans
Apply Generative AI to patient data analysis, including medical histories, genetic information, and real-time health metrics. AI can recommend personalized treatment plans, predict patient outcomes, and assist in the early diagnosis of diseases, improving overall patient care and treatment efficacy.
Precision Agriculture and Yield Prediction
Utilize Generative AI to analyze agricultural data from various sources such as satellite imagery, weather forecasts, and soil sensors. AI-driven insights can optimize planting schedules, predict crop yields, and recommend optimal resource allocation, leading to increased agricultural productivity and sustainability.
Marketing Campaign Performance Optimization
Employ Generative AI to analyze data from multiple marketing channels, including social media, email campaigns, and website analytics. AI can identify the most effective strategies, optimize campaign parameters in real-time, and predict future campaign performance, maximizing marketing ROI.
Supply Chain Risk Management
Use Generative AI to analyze data across the supply chain, identifying potential risks such as supplier delays, geopolitical events, and natural disasters. By predicting these risks and recommending mitigation strategies, AI enhances supply chain resilience and ensures continuity of operations.