CustomerDigital GoToMarket
IndustryInformation Technology
ServiceAIML
SegmentSMB
Automating manual processes with AI capabilities for Digital GoToMarket
ServiceAIML
IndustryProfessional Services
Automating Manual Processes With AI Capabilities for Digital GoToMarket
Meet Digital GoToMarket
The Digital GoToMarket (shown as DGTM throughout this study) consulting team help companies develop digital strategies, as well as designing, developing, launching, and selling, great digital subscription products & services.
From pragmatic product management and development execution through to sales channel and marketing campaign design, their core expertise is in turning ideas into profitable revenue growth through go-to-market planning and execution.
Business challenges
Currently, the DGTM collection, and extraction of data, from the varied digitised documents, is all gathered with ‘regular expression’ – a very explicit method of finding and extracting data from the documents.
This had proven to be reliable to a point, however it did not allow for discovery of more nuanced information, and it also required a very specific set of requests be generated for documents, in each of the backed securities markets.
DGTM wanted the capability to apply a machine learning strategy to this document analysis workflow. Providing multiple benefits that included scalability and adaptability, as well as an evolving level of accuracy that can be leveraged to improve data models over time.
Why Firemind?
DGTM were looking for a partner that could help them establish a scalable environment for their internal processes. Firemind needed to build a proof-of-concept that could ensure models were trained in the right way to maximise the success and quality of data extraction.
Our solution was to build out a proof-of-concept (POC) to demonstrate the capability of AWS Textract and AWS Comprehend for a document handling and analysis pipeline. The 2 focused goals of this solution were to provide an ML ‘sandbox’ to validate and test analysis model (custom classifications) as well as an automated pipeline for document handling and model retraining.
The ‘sandbox’ is a set of resources designed to provide an automated pipeline of AWS resources and services. This allows for a batch of documents to be uploaded, processed and analysed, so that the output can be reviewed and results used to influence the training of the custom classifications.
Added value
Firemind were able to remain true to the projected timeframe of 22 days, set over 7 phases. The proof-of-concept worked to provide accurate automation of previous manual tasking, enabling an environment to start moving real data into production.
Automated processes
The POC provided an automated process for Intelligent Document processing (IDP). Saving cost in manual hosting and storage as well as time, freeing up human operators to work on other tasks.
Introduction to managed services
DGTM were now using machine learning services such as Amazon Comprehend and Amazon Textract for improved extraction and classification during the processing logic.
Reduced human input
Removing the need for staff to work on these processes enabled the expansion for edge cases and faster classifications across the entire process. Human operators were now freed to work on other areas of the business and support their customers in other areas.
Customer satisfaction
“The Firemind team were extremely professional throughout the project and were always keen and willing to respond to our needs. The quality of the completed work is very high and has allowed us to accelerate progress in our own developments very easily, without the need to go back to them (although they have made it clear that we could if we need to).”
Adrian Mathias
Chief Operating Officer - Digital GoToMarket
How can we help you?
Let Firemind help your business develop automated, smarter processes, saving you time and money.