Travel Management Software That Automated 83% of Bookings

Travel Booking Software for Automated Bookings

Travel Management Software That Automated 83% of Bookings

Timspark has crafted a comprehensive mobile and web application to streamline the process of finding and reserving accommodations at ski resorts across the globe. The travel booking software is enhanced with a 24/7 support system and features an intelligent bot that efficiently routes user inquiries for prompt assistance.

#HoReCa

#TravelTech

Client*

Our client operates a global online travel agency dedicated to assisting customers in planning unforgettable holidays at the world’s premier ski resorts.

*We cannot provide any information about the client or specifics of the case study due to non-disclosure agreement (NDA) restrictions.

Project in numbers

duration
14 months
team
21 specialists

The team involved in the project

industry
HoReCa, Travel
solution
Software for hotel booking
technologies
Java, REST, Spring Boot, Spring Data, Kubernetes, React, TypeScript, Redux, Material UI, Android, iOS, Kotlin, Swift, SwiftUI, Python

1 x Project Manager

1 x Business Analyst
1 x UX/UI Designer
4 x Front-end Developers
4 x Back-end Developers
2 x Data Engineers
2 x Machine Learning Engineers
4 x Mobile Developers
2 x QA Engineers

Challenge

The client needed unified B2C travel management booking software for easy resort search, booking, and comparison. It also needed an up-to-date, responsive system for resort information, pricing, streamlined booking, flexible payments, and real-time availability.

Objectives

Develop a powerful travel booking software with an integrated booking engine
Automate bookings
Implement smart pricing
Boost revenue

Solution & functionality

Our team developed custom hotel booking software with supplier integrations, booking process management, and customizable search rules. We also created a secure back-office ecosystem and a B2C travel booking platform with user profiles and resort details. For customer support, we implemented a dedicated service and service bot. Additionally, we launched a mobile app for Android and iOS.

Price adjustment system and supplier management

Our travel management booking software includes critical components like a price adjustment system and supplier management. It allows online travel agencies (OTAs) to access real-time information via APIs and directly links with ski resorts’ property management systems for timely updates.

The software also features price tracking and adjustment, dynamically altering commissions based on factors like seasonal trends and competitor pricing. An integrated machine-learning algorithm suggests personalized accommodations based on users’ past preferences.

Smart recommendations and booking flow tracking

The travel booking software provides tools for defining resort search parameters and allows agency staff to modify them as needed swiftly. Travelers can specify their resort searches based on: Date, Price, Location, Resort size, Ski slope difficulty, Guest ratings, Room availability, Amenities, Catering options, Ski training availability, Popularity score.

This customization lets the agency quickly adjust search criteria and maintain a competitive edge with unique offers and prices that reflect the latest tourism trends.

Booking and payment simplification

Our B2C travel management booking software streamlines the comparison of search results from different sources to prevent duplicate listings. The booking tracking system facilitates effortless room reservations at ski resorts, supporting immediate bookings or holds with just a few clicks.

The platform’s API messaging system instantly forwards booking requests to service providers and guides users through the payment process. It supports various payment methods, such as credit cards, PayPal, Apple Pay, Google Pay, and WebMoney. This comprehensive setup ensures a frictionless booking experience for users and enhances satisfaction and loyalty.

Results and business value

Drawing on our expertise, we crafted a dynamic app for seamless bookings at top ski resorts worldwide. Integrating advanced features like pricing recommendations and intelligent support, it streamlines agency operations and ensures competitive pricing and efficient management.

83%

of all bookings are automated

14%

higher revenue with smart pricing

Benefits for client

The upgraded hotel booking software has been praised for its user-friendly design, intuitive navigation, and comprehensive automation features. It has also earned acclaim from both our clients and their end-users.

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    IoT & ML-based Energy Management Solution

    IOT FOR ENERGY MANAGEMENT

    IoT & ML-Based Energy Management Solution

    The team developed software for IoT energy management, specifically tailored to monitor wind turbines and manage energy production.

    #IoT

    #Energy

    #ML

    Client*

    A leading business in the renewable energy industry for over 20 years, specializing in wind energy and overseeing a vast network of wind turbines across multiple regions.

    *We cannot provide any information about the client or specifics of the case study due to non-disclosure agreement (NDA) restrictions.

    Project in numbers

    duration

    Ongoing project

    team

    14 specialists

    The team involved in the project

    industry

    Energy

    solution

    Data analytics

    technologies

    JavaScript, React, Redux, Python, FastAPI, Apache Spark, Kubernetes, Docker, AWS, PostgreSQL, Grafana

    Services

    1 x Business analyst

    1 x Project manager

    1 x Solution architect

    3 x Back-end developers

    1 x Front-end developer

    1 x Embedded developer

    1 x ML developer

    1 x DE developer

    1 x DevOps Specialist

    2 x QA engineers

    1 x Stakeholder’s SME

    Challenge

    Build an IoT energy management solution empowered with ML algorithms for real-time monitoring and predictive analysis of wind turbine performance. The main goal is to prevent system malfunctions that could cause power outages and costly repairs.

    Solution & functionality

    The team came up with an IoT & ML-driven energy management software solution that predicts energy production. An advanced platform provides real-time updates on the status of each wind turbine based on the information accumulated from meteorological sensors and turbines.

    Programmable logic controllers (PLC)

    We utilized programmable logic controllers (PLCs) to gather data from sensors placed across the wind turbines. They monitor various operational metrics, like wind speed, turbine rotation speed, temperature, vibration, and torque, process the data and provide a precise overview of the wind turbine’s current performance, identify faults, and energy production efficiency. Additionally, system detects deviations, like an unexpected temperature rise or increased vibration — to prevent damage, it triggers alarms or shuts down the turbine. Such timely maintenance and malfunction prevention ensures balanced energy production and extends equipment lifespan.

    Data visualization

    To visualize data, our project team chose Grafana dashboards. We created customized actionable charts for IoT energy management displaying data like daily power output, turbine locations, weather patterns, and predicting future trends. Thanks to these visualizations operational managers have access to a real-time overview of turbine performance, while maintenance teams can quickly address turbine issues.

    Data lake

    The client needed a robust data lake, as they operate wind turbines across various regions. Our developers created a central repository to collect and store data from all turbines, regardless of their location, including structured, unstructured, and semi-structured data such as logs, sensor readings, and images. Data is collected from the PLCs and then stored and processed using AWS IoT Core and Lambda functions. Large datasets can be processed simultaneously, which greatly supports predictive maintenance and accelerates analysis and reporting.

    Error prediction

    Leveraging data science and MLOps, we developed a predictive model that evaluates various factors influencing turbine health, such as vibration and temperature levels, and performance metrics. This model continually learns from incoming data and enables the operational managers to detect warning signs of failures early. Upon identifying them, the energy management control system sends alerts to the maintenance teams so that they proactively address the issues before they cause breakdowns.

    Analytical reports

    The energy management system can generate analytical reports based on the historical and real-time data to provide insights into wind turbine performance. This data helps identify well-operating turbines and those needing maintenance. Also, by analyzing performance trends and external factors like weather, the system suggests ways to optimize energy consumption, determine ideal times for energy harvesting, manage storage, reduce costs, and streamline maintenance.

    Results and business value

    The team successfully implemented IoT in energy management, providing the client with a scalable energy management control system.

    up to 6%

    increase in energy production

    18%

    reduction in maintenance and repair costs

    26

    critical threats prevented

    Benefits for client

    The solution helps prevent system malfunctions that could cause power outages and costly repairs. As a result, the client achieved 18% reduction in maintenance and repair costs and up to 6% increase in energy production.

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      Call Center Monitoring Software That Automates 27% of Client Requests

      IoT PLATFORM

      Call Center Monitoring Software That Automates 27% of Client Requests

      Timspark crafted a tailored AI-powered call center monitoring software for a major telecom enterprise, seamlessly linking operators and customers within an integrated platform.

      #Telecom

      #AI

      #Python

      Client*

      The client operates as an internet provider and offers a diverse array of internet services to customers situated across the European Union.

      *We cannot provide any information about the client or specifics of the case study due to non-disclosure agreement (NDA) restrictions.

      Project in numbers

      duration

      13 months

      team

      20 specialists

      The team involved in the project

      industry

      Telecommunications

      solution

      AI call center software

      technologies

      React, Redux, Typescript, .Net Core, C#, .Net WebAPI, FluentMigrations, RabbitMQ, MassTransit, Windows, Linux, Python

      1 x Project manager

      2 x Business analysts

      2 x Front-end developers

      4 x Back-end developers

      3 x Full-stack developers

      1 x DevOps engineer

      1 x VoIP engineer

      2 x QA engineers

      1 x UI/UX designer

      1 x Solutions architect

      2 x ML engineers

      Challenge

      Our ISP client aimed to enhance customer satisfaction and support by developing custom call center software for improved scheduling. They required seamless integration with their CRM and task-tracking system to help operators quickly access client information and automate issue resolution.

      Major objective

      Empower customer service interactions with AI

      Related objectives

      Automate request processing

      Build intuitive interface

      Ensure security compliance

      Smoothly integrate infrastructure

      Solution & functionality

      Timspark created advanced AI-driven call center monitoring software to direct client calls to appropriate operators through AI-powered voice recognition and request identification. Our solution utilizes a .Net-based microservices architecture for robust back-end implementation, including SIP and soft PBX servers. 

      The front end, developed with React and Electron, offers a user-friendly desktop application interface. The system efficiently handles call routing, adhering to predefined regulations, and maintains GDPR compliance throughout its interconnected components to keep operator communication and responses swift.

      AI-driven voice recognition and call routing

      Our team integrated artificial intelligence into contact center operations to automate client support processes. Interactive voice response, call routing, and smart voice recognition capabilities are now managed by AI. Using modern natural language processing techniques and BERT models, the system engages callers, identifies their requests, and performs tasks like changing tariffs or ordering additional services. 

      For complex inquiries, the AI routes call to the appropriate operator or department to provide specialized assistance. Intelligent routing optimizes customer interactions and allows operators to focus on exceptional service delivery and the resolution of complex issues.

      Client request cards

      Our AI call center software automated card creation and enables operators to access and update client details quickly. When a call is received, the system identifies the client and presents their card with personal information and interaction history. Each card includes an action plan tailored to the request to guide operators through the resolution process with step-by-step instructions.

      Call recordings and statistics

      The call center monitoring software software securely stores call recordings and provides customizable statistics and tools for analytics. Supervisors can monitor performance metrics, track interactions processed by AI, and optimize team efficiency. This part of call center software features enhances issue resolution and facilitates call operator training through comprehensive call logging and recording.

      Automated task setting

      Integrated with the company’s task management and CRM systems, our call center monitoring software enables efficient task creation and assignment. Operators can generate tasks from client interactions, transferring all relevant details automatically. Task progress can be tracked within the system to provide supervisors with insights into workload distribution and resolution status.

      Results and business value

      Our AI call center software boosts task management, optimizes workloads, and streamlines customer support. Its user-friendly interface enables quick responses, while its flexibility promotes collaboration across departments beyond telecom services.

      Benefits for client

      Timspark’s AI call center software is a significant improvement that has reduced the workload for staff to keep focus on more complex customer issues.

      41%

      faster customer success

      27%

      of requests automated

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        How Computer Vision in Agriculture Helps Track Bee Population and Health

        Computer Vision in Agriculture

        How Computer Vision in Agriculture Helps Track Bee Population and Health

        Timspark used AI to make mobile computer vision software to track the beehive life. We also predict how the bee population will grow and how healthy it is overall.

        #AI

        #MobileDevelopment

        #ComputerVision

        Client*

        It was Timspark’s internal project. We were eager to independently grow expertise in Machine Learning and built an ML-powered app with prediction functionality for agriculture.

        Project in numbers

        duration

        6 months

        team

        4 specialists

        Team involved in the project

        industry

        Agriculture

        solution

        Mobile computer vision software for beehive tracking

        technologies

        Python, PyTorch, YOLOv3, Google Cloud Platform, DigitalOcean, Swift 5

        1 x Lead Data Scientist

        1 x iOS Developer

        1 x Data Engineer

        1 x Project Manager

        1 x QA

        Challenge

        Our team did it all for this project – from planning the product’s architecture to labeling the data and training the neural network. This hands-on approach to computer vision services helped us become experts in the field and led to a fully working product as the outcome. We tackled a set of machine learning challenges and industry-related standards of using computer vision in agriculture, too.

        Solution & functionality

        Our ready-made solution is a mobile app that uses computer vision in agriculture to count bees in the hive accurately. It also creates user-friendly charts and graphs, making it easy to monitor the hive’s growth and health.

        Object detection for beehive population count and health tracking

        We have harnessed object recognition technology, so now it is possible to scan and instantly figure out how many bees are in the hive. Also, the solution helps distinguish the regular bees from the queen bees.

        A modern user-friendly mobile app

        Our team built mobile computer vision software from the ground up with an easy-to-use interface. We also added a feature where a client can get automatic reports about the hive’s status using the information uploaded.

        Results and business value

        We’ve successfully crafted computer vision solutions for iOS, designed to assist beekeepers in caring for their beehives more effectively.

        Benefits 

        Our app offers a major time-saving advantage. With traditional manual inspections taking up to an hour per beehive, our computer vision services help beekeepers inspect a hive in just 10 minutes or even less.

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          How to Use Computer Vision in Agriculture for Detecting Diseased Banana Leaves

          Computer Vision in Agriculture

          How to Use Computer Vision in Agriculture for Detecting Diseased Banana Leaves

          Our team developed a computer vision software that checks banana seedling leaves for damage all on its own. We also use advanced analytics to help our client reduce crop loss probability.

          #AI

          #WebDevelopment

          #ComputerVision

          Client*

          Top banana seeding supplier in the world

          *We cannot provide any information about the client or specifics of the case study due to non-disclosure agreement (NDA) restrictions.

          Project in numbers

          duration

          4 months

          team

          5 specialists

          The team involved in the project

          industry

          Agriculture

          solution

          Computer vision software for plant disease detection

          technologies

          Python, Pandas, Numpy, Pytorch, Streamlit, Opencv

          1 x Lead Data Scientist

          1 x Data Scientist

          1 x Data Engineer

          1 x Project Manager

          1 x QA

          Challenge

          The client was concerned about the possibility of using computer vision in agriculture to detect plant disease and prevent crop loss automatically. On the tech side of things, our team faced a scarcity of data available to train AI-based computer vision solutions.

          Solution & functionality

          We came up with a solution to place cameras in the greenhouse, putting them up high and to the side. These cameras take periodic snapshots of banana seedlings. The client can adjust the frequency of these snapshots.

          Deep learning for object detection and classification

          Timspark made a computer vision software module that grabs pictures of the leaves spotted by the camera. These pictures later get sent to the deep learning classifier model, which has a closer look at images and tells if a banana leaf is healthy or damaged. It can even figure out what kind of damage it is.

          Plant condition reports and analytics

          Our computer vision software checks out the uploaded pictures and generates a PDF report with the results. It further gives recommendations on what to do next based on the analyzed data.

          Results and business value

          Timspark didn’t just create and tweak the classifier model; we did it thoroughly, making sure it fits the project’s special needs and industry standards. The client is satisfied with the outcome and still partners with us on more projects to facilitate computer vision in agriculture.

          Benefits for client

          Thanks to computer vision services, the customer has successfully put this technology to work and significantly cut down on banana seedling losses.

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