CustomerDigital GoToMarket
IndustryProfessional Services

Automating Manual Processes With AI Capabilities for Digital GoToMarket

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 to develop digital strategies and to design, develop, launch and sell 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 digitised documents is gathered with regular expression – a very explicit method of finding and extracting data from the documents.

This has proven reliable to a point, although it does not allow for discovery of more nuanced information and requires a very specific set of requests be generated for documents in each of the backed securities markets.

DGTM would also like the capability to apply a machine learning strategy to this document analysis. This having multiple benefits that include 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.


Firemind x DGTM

We met with Adrian Mathias, Chief Operating Officer at DGTM, to look at the project’s planning, successes and ongoing benefits as it continues to scale within the cloud.

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

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