Enter [Documentor] our very latest smart tool

Over the years, through generations of successive systems, we built up extensive experience in data processing and document handling. We took that deep well of expertise and extracted something brilliant - what could be the most innovative document processing solution this side of the pond.

By leveraging our hard-earned lessons and proven innovative capabilities, we've engineered a truly transformative new approach. One born from relentless tinkering, disruptive thinking, and more late nights than we'd like to admit. RobotCode's solution is here to change the document processing game.

Intrigued? You should be. Let me take you through the details...

Having spent my career fixing inefficiencies, I've seen how much time is wasted on manual data entry - time that could be better spent innovating. I knew there had to be a better way. Enter generative AI - the new kid on the block, sometimes overhyped, but here we found a perfect use case. With our software and a reliable, secure AI platform, we have a winning recipe.

We looked far and wide for the best tech stack for our discerning clients, and the overwhelming winner in this category is undoubtedly the latest AI services platform from Microsoft Azure. In addition to OpenAI's models, they recently added Mistral's "Large" language model (and Azure AI now offer the same service across the board for other open-source models as well, such as Llama 2, etc.).

Here's how it works:

RobotCode has developed a templating solution, whereby clients can upload various predefined data schemas to our document processing server. These schemas allow you to define templates tailored to your specific document types and data needs.

Our service exposes an API that allows you to upload documents to a processing queue. Once in the queue, documents are analyzed using a combination of pattern and token techniques along with generative AI models from Microsoft Azure.

While processing is underway, you can poll the queue to check the status until it is complete. When finished, data results can be delivered in your preferred format - via text paging or queried data output.

A major advantage is that this service can handle any number of predefined schemas you provide. This flexibility ultimately allows you to process any type of PDF document, as long as an appropriate schema is predefined.

Throughout the entire process - including processing, in-memory storage, and data transit - your information will be securely encrypted using industry-standard practices. The processing itself takes place via the Microsoft Azure Cloud platform, which prioritizes encryption, access control, and security best practices.

Let's look at an example. Say you're an accountant buried in manual invoice data entry. Our solution would ingest and process invoices based on your predefined schema, extracting key details - saving you time and hassle. Your team is then free to focus on strategic initiatives, not repetitive tasks.

Any business bogged down by documents can benefit from the convenience of automated processing. It's not a perfect solution, but it aims to alleviate the drudgery of manual workflows.

Microsoft's architecture prioritizes security, encrypting data end-to-end. With a focus on confidentiality, privacy and security, precautions are taken to safeguard your information.

Put [Documentor] to the test

We're offering beta access to our partners as we ready this tool for launch. If you seek to streamline document handling, we welcome you to try it out and provide feedback.

In closing, while not a silver bullet, our solution aspires to chip away at inefficient processes through AI's potential. Join us as we work to incrementally improve productivity and agility. The future remains unwritten - let's make progress together.

Let me know if you need any other details regarding RobotCode's document processing workflow or go-to-market plans. I'm happy to expand or clarify any sections to ensure the solution is accurately positioned. The goal is to strike a balance between innovation and realistic expectations.

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This article was also published on the following social media location(s):

• - Linkedin || RobotCode
• - Linkedin || Andre Jonker