Files.com
6,000+ companies trust Files.com to automate and secure business critical transfers.
We obsess about security, compliance, reliability, and performance so your critical business processes just work every time. Easily manage any transfer flow without writing scripts or code, and onboard workloads and partners effortlessly.
We support standard file transfer protocols (FTP, SFTP, AS2) for working with external partners and also provide native apps for high performance internal transfers.
As a fully Cloud-Native SaaS, there are no servers for you to buy or maintain, there is no installation required, and high availability and redundancy are built in and free.
Our InfoSec Program is audited annually by Kirkpatrick Price, a leading information security CPA firm. Our audit covers the scope of the entire Files.com business (not just datacenter operations) and names Files.com specifically. Beware of smaller competitors who try to pass off someone else’s audit as their own.
Technical capabilities include encryption at-rest and in-transit, four types of two-factor authentication, nine enterprise identity (SSO) integrations, configurable password and session policies, and a perfect “A+” score from Qualys SSL Labs.
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JOpt.TourOptimizer
If you are developing software for Logistics Dispatch Solutions, which contain challenges:
-For staff dispatching, such as sales reps, mobile service, or workforce?
-For truck shipment allocation in daily transportation and logistics (scheduling, tour optimization, etc.)?
-For waste management and District Planning?
-Generally, highly constrained problem sets?
And your product does not have an automized optimization engine?
Then JOpt is the perfect fit for your product and can help you to save money, time, and workforce, letting you concentrate on your core business.
JOpt.TourOptimizer is an adaptable component to solve VRP, CVRP, and VRPTW class problems for any route optimization in logistics or similar fields. It comes as a Java library or in Docker Container utilizing the Spring Framework and Swagger.
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tox
tox is designed to streamline and automate the testing process in Python. This tool is a key component of a broader initiative to simplify the packaging, testing, and deployment workflow for Python applications. Serving as a universal virtualenv management tool and a test command-line interface, tox allows developers to verify that their packages can be installed correctly across multiple Python versions and interpreters. It facilitates running tests in each environment, configuring the preferred testing tools, and integrating seamlessly with continuous integration servers, which significantly minimizes redundant code and merges CI with shell-based testing. To get started, you can install tox by executing `pip install tox`. Next, create a `tox.ini` file adjacent to your `setup.py` file, detailing essential information about your project and the various test environments you plan to utilize. Alternatively, you can generate a `tox.ini` file automatically by running `tox-quickstart`, which will guide you through a series of straightforward questions. After setting up, be sure to install and validate your project with both Python 2.7 and Python 3.6 to ensure compatibility. This thorough approach helps maintain the reliability and functionality of your Python software across different versions.
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LiteRT
LiteRT, previously known as TensorFlow Lite, is an advanced runtime developed by Google that provides high-performance capabilities for artificial intelligence on devices. This platform empowers developers to implement machine learning models on multiple devices and microcontrollers with ease. Supporting models from prominent frameworks like TensorFlow, PyTorch, and JAX, LiteRT converts these models into the FlatBuffers format (.tflite) for optimal inference efficiency on devices. Among its notable features are minimal latency, improved privacy by handling data locally, smaller model and binary sizes, and effective power management. The runtime also provides SDKs in various programming languages, including Java/Kotlin, Swift, Objective-C, C++, and Python, making it easier to incorporate into a wide range of applications. To enhance performance on compatible devices, LiteRT utilizes hardware acceleration through delegates such as GPU and iOS Core ML. The upcoming LiteRT Next, which is currently in its alpha phase, promises to deliver a fresh set of APIs aimed at simplifying the process of on-device hardware acceleration, thereby pushing the boundaries of mobile AI capabilities even further. With these advancements, developers can expect more seamless integration and performance improvements in their applications.
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