A serverless architecture inverts this paradigm completely: rather than relying on a dedicated server that is always on, even when nobody is visiting the site, serverless applications rent just the compute power needed to serve up the application purely on an on-demand basis. Traditionally, when building web-based applications, a dedicated server (or servers) that is always online is used to process and store data and serve up content whenever a user visits the website or application. Parsel is built using a serverless architecture. Our architecture ensures that we can analyse your document as quickly as possible, while completely isolated from any other processes. Furthermore, any data we store in our private cloud environment is fully encrypted-at-rest.

Any communication with the outside world is fully encrypted (encrypted-in-transit), and thus not at risk of being stolen or spied on, as encrypted data is meaningless without knowledge of the protected private encryption key. Our entire software architecture is hosted on AWS on our own Private Virtual Cloud, which is a private, secure and closed off virtual environment. To ensure this, we encrypt your document from the moment you upload it, all the way to the point where you download your desired output. We understand that documents and images contain sensitive information that must be kept private at all costs. All documents processed by Parsel are transmitted and stored securely In this post we hope to convince you that these principles matter, and show why they're the architectural foundation that Parsel was built upon. With all of this in mind, we set out to define an architecture that adhered to the above three principles. We also wanted to be able to improve the product in an organic way, by iterating fast on new features without worrying about breaking anything in the document processing pipeline. We also knew that processing workloads would be spiky and therefore it would be hard to predict the level of computational resources needed at any given time. We knew that Parsel was going to be processing potentially sensitive documents (financial documents, initially, then expanding from there).

In this post, we hear from the head of Parsel's data science team, Daniel Vliegenthart, about the technical architecture under the hood of Parsel and what that means for handling large document processing workloads without any performance degradation.įrom the moment we first started thinking about Parsel as a product, we had three adjectives in mind for its technical architecture: secure, scalable and supple.

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