childish-page-banner

Other indsutries

We at VECTOR Labs are dedicated to providing innovative and advanced digital solutions to transform customer experiences and drive business growth. With our expertise in next-gen technologies, we offer custom software development and data science services tailored to meet our clients' specific needs in various industries.

A stellar team that delivers scalable solutions

Our team of experts has extensive experience in custom software development and data science. It has a proven track record of delivering top-notch scalable, robust, and efficient solutions. We work closely with our clients to understand their unique business needs and requirements, and we develop solutions that are aligned with their goals and objectives.

We have worked with clients across various industries, including healthcare, pharma, banking, computer vision, finance, insurance, education, manufacturing, retail, logistics, and more. Our solutions are designed to address each industry's specific challenges and opportunities, and we leverage the latest technologies to create solutions that deliver tangible results and drive business growth.

End-to-end solutions

We strive to provide end-to-end solutions for our clients, from ideation to deployment and beyond. Our team works closely with clients to understand their unique business needs and goals and then develops comprehensive solutions tailored to them. Our approach employs agile methodologies and continuous communication to ensure that our clients are involved in every step of the development process and have complete visibility into the progress of their projects. 

Our services include initial creativity and strategy to design, development, testing, and ongoing maintenance and support. We are committed to delivering high-quality, scalable, and secure solutions that help drive their business forward.

Other industries Case Studies

banner

AI screening tool for a recruitment software

Overview: The client was a start-up solving the problem of managing numerous processes within a recruitment department. Hiring teams have data from a variety of sources, which are difficult to process and analyze. Our task was to structure and develop a data structure and create an AI tool for screening candidates.

Approach: Our team of data engineers, data scientists, and ML engineers started with a research phase to understand the client's requirements and identify the best approach for the project. We conducted a thorough analysis of the recruitment data landscape and the different types of data sources used in the industry. We then developed a solution architecture that could handle the complex data structures and AI models required for the project. We selected AWS as the primary provider for data storage and combined it with other ETL tools to work with different formats from multiple sources.

Once the data structure and pipelines were set up, we used semantic analysis with NLTK preprocessing to extract the necessary information for each candidate. The semantic analysis allowed us to identify the candidate's skills, experience, and education from their resume, cover letter, and social media profiles. We then developed the ML model using Keras, TensorFlow, and SKLearn to sort the candidates into predefined groups and factors, such as experience level, job title, and location. The output was presented in a structured database of candidates, which could be easily searched and filtered by hiring teams.

Key Metrics: The AI screening tool provided significant benefits for our client's recruitment process. The applicants in the system were automatically shortlisted, and the hiring teams only needed to review the screening results. 

The solutions achieved their goal of optimizing the time a recruitment team needs for manual review of the CVs of candidates and reducing it by half. The increased productivity allowed them to focus on more strategic tasks, such as conducting interviews and assessing candidate fit.

banner

Web platform with CRM for travel reservations exchange

Overview: SpareFare is a UK start-up connecting people who have bought a flight ticket or a hotel reservation but cannot use it anymore, with people who want to buy a discounted ticket. Their team was looking for a development partner with top-notch engineers to help them build the complex architecture behind their platform. The platform had to include complex transactions between the different users and the back office.

Solution: When we joined the project, the client already had an existing platform. The scale-up of the business and the increasing number of clients required to have rebuilt from scratch while keeping the core functionalities and design. Our team had to create a scalable platform, add missing elements and features both in the user interface and the CRM.

The development involved the structure of multiple roles and permissions, payment processing through multiple sources, and payment approvals. The back-office team had to work in a well-structured and quick CRM which we built as a fully custom solution in order to respond to the dynamic requests. 

The system also involved multiple integrations with service providers. The biggest challenge was the exchange of constantly changing information about the price of flight tickets. The task required a highly experienced team of developers. Apart from the front-end and back-end development, we supported them with Cloud, DevOps and UX advisory at every step. Our data engineering team was actively involved as well so that the system was ready to grow in a predictive analytics platform in the future.

Team: The solution was built using Python development, React.JS development, Data engineering, UX, DevOps engineering, QA, and Project management.

Results: The platform was successfully implemented, resulting in an increased loading speed of more than 300% and improved UX. Overall, the project was a success and met the client's needs for a complex and user-friendly platform for travel reservation exchange.

banner

IoT tool for electricity consumption analysis

Overview: Our client needed a tool to analyze electricity consumption based on the data from sensors integrated into electrical sockets, in real-time and historically, with the ability to track any critical moments. The client also required the tool to be scalable and applicable to other sensors in the market.

Solution: To ensure that the tool met the requirements, our team collaborated with the client's team to understand their needs and preferences. We analyzed the data collected by the sensors to develop algorithms to accurately track the electricity consumption of each socket. We then integrated the algorithms into a user-friendly interface that allowed users to easily track their electricity usage over time. We used Python, Django and Angular to develop the backend and front end of the tool, respectively, ensuring a scalable solution that could be easily extended to support other sensors in the market.

Our team also implemented various features to enhance the user experience. We included notifications and snapshots for critical moments, such as extreme power consumption, electrical fault or a sudden surge in electricity usage. We also generated heat maps for each socket, providing users with visual information about their electricity usage over time. We ensured that the tool was responsive and could be used on mobile devices, enabling users to monitor their electricity usage on the go.

Tech stack: Python, Django, Angular, AWS.

Outcome: Our electricity consumption analysis tool provided the client with an innovative solution that accurately tracked the electricity consumption in real-time and historically. The tool's user-friendly interface, along with its ability to generate heat maps and send notifications, made it easy for users to track their electricity usage and identify areas where they could reduce consumption. The tool is successfully used in facility management and manufacturing. 

Let's work together

By clicking the Accept button, you are giving your consent to the use of cookies when accessing this website and utilizing our services. To learn more about how cookies are used and managed, please refer to our

Cookie Statement & Privacy Policy