What open API means for today’s IT and physical security strategies
What is open-source security software?
Open-source software is nothing new. In fact, it’s been around since the 1990s when it was popularized during the dot-com boom. Open source software makes it free to use and modify the source code. While similar, open application programming interface, or API, software takes this a step farther. Open API still gives developers universal access to software programs, but it’s also a tool for making platforms communicate with each other. Through open API, companies can let outside users and developers access code resources to quickly and efficiently make different programs work together with less code to write from scratch.
Just because the software claims to be open, however, doesn’t mean it has good open API design. A great open API source will be easy to work with, straightforward, and contain all the necessary information to use the code properly.
Benefits of open API software for IT and physical security
Choosing the right business and security software is no short order. These are big, important investments, and it’s hard (and expensive) to switch systems once you’re already working with one. But open source and open API security software can make it easier to future-proof security systems and adapt to new challenges as they arise.
For example, when navigating the challenges of reopening an office building during the pandemic, buildings leveraged the open API of their access control to connect credentials to completed health forms or temperature screenings. This API structure allowed businesses to quickly pivot their security and health strategies while not needing to o rip and replace their existing access control system. Open API utilizes the existing platform to communicate in new ways to establish safe security processes for the new situation.
When deciding whether or not to use open API software, businesses should consider the following key benefits:
- Flexibility – Open software is often more adaptable and customizable than closed API or proprietary software, letting businesses choose how to use the software to fit their specific needs.
- Interoperability – Going with open software gives businesses the option to leverage and connect with more third-party systems. Open API is essential for creating powerful full-building integrations, in which all systems communicate with each other and datastreams are analyzed as a single entity.
- Performance – If you’re looking to improve security posturing through technology, open platforms often have more intuitive design, making them easier to use with less training than proprietary solutions.
- Cost savings – Proprietary software licensing is often expensive, and requires regular renewals to continue using it. Most API is available for free, but the better support and third-party management justifies the cost of SaaS products. The ease of implementation, without the need for expensive training, also adds to the cost savings.
- Security – Simply by being an open platform, providers need to fix bugs and address vulnerabilities as soon as they arise. On the contrary, proprietary system providers sometimes choose not to address an issue until they have a new release that fixes it, which can leave their customers vulnerable in the meantime.
Examples of top open-source security software providers
Openpath (a Motorola Solutions company)
As one of the top open API cloud-based access control providers, Openpath allows organizations to create full-building security systems that work together seamlessly. While the software itself is flexible and adaptable, the Openpath platform offers unlimited integration capabilities, and partners with the top technology companies to provide native integrations with video surveillance systems, identity management solutions, visitor and tenant platforms, communication apps, and analytics tools.
Why is RPA the fastest-growing enterprise software in the world?
Why is RPA the fastest-growing enterprise software in the world?
When you combine RPA’s quantifiable value with its ease of implementation relative to other enterprise technology, it’s easy to see why RPA adoption has been accelerating worldwide.
RPA can help many different types of industries address their specific operational issues in new and powerful ways.
Leaders of functional areas from finance to customer service to marketing to human resources and beyond find that RPA improves many processes, yielding higher capacity, faster throughput, and fewer errors for key processes.
From a CFO’s perspective, an investment in RPA technology delivers rapid ROI and requires minimal upfront spending compared to other enterprise technology.
IT executives find that RPA can be implemented with little disruption. And because software robots can easily access and work within legacy systems, RPA has become a key enabler for digital transformation. And modern RPA technology offers scalable, enterprise-ready platforms.
Employees find that it’s easy to adopt robotic assistants into their workdays, and that RPA’s low-code approach lets them become citizen developers who can build their own simple automations.
Is RPA the same as artificial intelligence (AI)?
RPA is not AI; AI is not RPA. But the combination of RPA and AI unlocks massive new possibilities for enterprises everywhere. For one thing, RPA technology now makes it possible to insert advanced AI skills in the form of machine learning models, natural language processing (NLP), character and image recognition, and more into RPA robots. Giving robots these AI skills dramatically expands their ability to handle cognitive processes that require things like:
Understanding documents including semi-structured or unstructured data
Visualizing screens (including virtual desktops)
Comprehending speech and carrying on conversations and chats
AI is also making it possible to scientifically discover a complete range of automation opportunities and build a robust automation pipeline through RPA applications like process mining.
And at a time when companies need to accelerate their integration of AI into front-line activities and decisions, many are finding that RPA can serve as AI’s ‘last-mile’ delivery system. Robots can be configured to apply machine learning models to automated decision-making processes and analyses, bringing machine intelligence deep into day-to-day operations.
