E-mail: info@denovonet.com

About Us

Data-Driven Insights, Unlock Knowledge

About Us

Our Mission

Denovonet is structured to enable and empower businesses with a competitive edge by leveraging the transformative abilities of data-driven AI and ML methodologies. We design and develop efficient processes and provide clean data in supporting solutions that industries can use to streamline the decision making process.

At Denovonet we believe that data is world’s most valuable resource. We are very client centric and work with them to understand their challenges and help build strong culture and excellence around data driven, data informed and data aware strategies to drive efficiency and solve complex problems for growth and advancement of client operations. Denovonet is fully committed to steering new era of innovation, productivity and profitability.

Our Business Solution

Predicting Criminal Hotspots

We have developed a crime prediction application using machine learning algorithms that assists predictive policing and surveillance. It aims to forecast criminal activities, improve public safety and allocate police resources more efficiently in a given area and time by analyzing historical crime data and relevant factors. We are able to analyze patterns and trends in crime that may evade human analysis. There is continuous improvement in predictability as the data and models are refined.

Introduction

Crime prediction is a crucial application of machine learning that aims to forecast criminal activities in a given area and time. By analyzing historical crime data and relevant factors, machine learning algorithms can help law enforcement agencies and communities make informed decisions to prevent and manage criminal incidents. The significance of crime prediction lies in its potential to enhance public safety, allocate resources more effectively, and proactively address criminal activities. AI has established itself in predictive policing and surveillance.

Decision Tree

Using the Random Forest algorithm also helped us explain our predictions. Since the Random Forest algorithm has Decision Trees at its base, we can simply follow the path taken by the most confident tree in this forest to allow us to explain why our model made a particular decision. This would help the law enforcement agencies to make sense of the prediction and not accept it as is. Hence, our best performing model would not simply be a black box decision maker.

Our Skills

Our Team

We have team of highly skilled data scientists, machine learning engineers and software developers. They have deep knowledge of algorithms, statistics, data engineering, model training and deployment. Team members have deep knowledge in different business domains, it includes the finance and fintech, healthcare, e-commerce, autonomous vehicles and manufacturing industry. Brief Bios of the core team is provided.

Dr. Salman Iqbal

Chief Executive Officer

Dr. Salman Iqbal has over 30 years of experience in software development and technology services with proven leadership capability in successful execution of commercial and business strategies.

Imran Bashir

Director of Strategy

Imran is a goal-oriented and entrepreneurial individual, a change agent who has led organizations in creating innovative solutions to some of the toughest business challenges around.

Yassir Ahmed

Director of Software Engineering

Yassir has over 20 years of progressive experience in software development, architecture, and infrastructure, demonstrating an outstanding record of delivering high-impact software projects in complex distributed environments.

Dr. Nilufer Sari

Lead Data Scientist

Dr Nilufer Sari, an active researcher in urban mobility and geospatial data analysis, has contributed to smart city development through her work with machine learning applications. With published research and numerous citations, Dr Sari focuses on connecting theoretical research with practical, sustainable urban solutions, engaging in global discussions about intelligent urban planning and development.

Dr. Qaisar Malik

Director of Data Engineering

With a proven track record, Qaisar specializes in crafting resilient data engineering solutions tailored to the unique requirements of organizations. These solutions empower companies to harness their data effectively, whether for AI applications or decision-making processes.