
SurveyJS is a set of four open-source JavaScript libraries that offer the benefits of a tailor-made in-house survey application, while considerably reducing the time and resources needed to deploy the system. These libraries are independent of specific server code or database requirements and seamlessly integrate with popular JavaScript frameworks, including React, Angular, Vue.js, jQuery, Knockout, and more. They are designed to communicate with any server that can handle JSON requests, ensuring compatibility with various server architectures and databases.
The product family is composed of:
- An open-source MIT-licensed rendering library that renders dynamic JSON-based forms in your web application, and collects responses.
- A self-hosted drag & drop form builder that features an integrated CSS-based theme editor and a GUI for conditional rules. It automatically generates JSON definitions (schemas) of your forms in real time.
- PDF Generator, a library that renders SurveyJS surveys and forms as PDF files in a browser;
- The Dashboard library that allows you to simplify survey data analysis with interactive and customizable charts and tables.
Visit our website to try out and evaluate our full-scale demo for free.
Learn more

JOpt.TourOptimizer is an enterprise optimization engine for route planning, scheduling, and resource allocation across logistics, transportation, dispatch, and field service operations. It is built for organizations that need to solve complex planning problems under real-world business constraints rather than simple consumer-grade route calculation. The platform supports vehicle routing and scheduling scenarios such as VRP, CVRP, VRPTW, pickup and delivery, multi-depot planning, heterogeneous fleets, and workforce scheduling.
JOpt.TourOptimizer can model time windows, working hours, visit durations, capacities, skills and expertise levels, territories, zone governance, overnight stays, alternate destinations, and custom business rules. This makes it suitable for production deployments where feasibility, transparency, and operational reliability matter. It is designed to generate practical plans that help teams balance travel time, service commitments, workload distribution, and operational cost in demanding enterprise environments.
The solution is available both as an embedded Java SDK and as a Docker-based REST API with OpenAPI and Swagger support. This allows software vendors, enterprise developers, and system integrators to embed advanced optimization into TMS, ERP, CRM, WMS, dispatch systems, customer platforms, and field service applications. With support for scalable integration and modern service architectures, JOpt.TourOptimizer helps organizations improve planning efficiency, service quality, SLA compliance, transparency, and operational resilience at scale. It also supports enterprise integration strategies that require reproducible optimization runs, structured outputs, and flexible deployment models.
Learn more
Bokeh
Bokeh simplifies the creation of standard visualizations while also accommodating unique or specialized scenarios. It allows users to publish plots, dashboards, and applications seamlessly on web pages or within Jupyter notebooks. The Python ecosystem boasts a remarkable collection of robust analytical libraries such as NumPy, Scipy, Pandas, Dask, Scikit-Learn, and OpenCV. With its extensive selection of widgets, plotting tools, and user interface events that can initiate genuine Python callbacks, the Bokeh server serves as a vital link, enabling the integration of these libraries into dynamic, interactive visualizations accessible via the browser. Additionally, Microscopium, a project supported by researchers at Monash University, empowers scientists to uncover new functions of genes or drugs through the exploration of extensive image datasets facilitated by Bokeh’s interactive capabilities. Another useful tool, Panel, which is developed by Anaconda, enhances data presentation by leveraging the Bokeh server. It streamlines the creation of custom interactive web applications and dashboards by linking user-defined widgets to a variety of elements, including plots, images, tables, and textual information, thus broadening the scope of data interaction possibilities. This combination of tools fosters a rich environment for data analysis and visualization, making it easier for researchers and developers to share their insights.
Learn more
PyQtGraph
PyQtGraph is a graphics and GUI library developed in pure Python, utilizing PyQt/PySide alongside NumPy, designed primarily for applications in mathematics, science, and engineering. Despite its complete implementation in Python, the library achieves impressive speed by effectively utilizing NumPy for numerical computations and the Qt GraphicsView framework for efficient rendering. Released under the MIT open-source license, PyQtGraph supports fundamental 2D plotting through interactive view boxes, enabling line and scatter plots with user-friendly mouse control for panning and scaling. Its ability to handle various data types, including integers, floats, and different bit depths, is complemented by functionalities for slicing multidimensional images at various angles, making it particularly useful for MRI data analysis. Furthermore, it facilitates rapid updates suitable for video display or real-time interactions, along with image display features that include interactive lookup tables and level adjustments. The library also provides mesh rendering capabilities with isosurface generation, while interactive viewports allow users to rotate and zoom with ease using the mouse. Additionally, it incorporates a basic 3D scenegraph, simplifying the programming process for three-dimensional data visualization. With its robust set of features, PyQtGraph caters to a wide range of visualization needs and enhances user experience through interactivity.
Learn more