Building Software Solution for Financial Reporting

We developed a software solution that would enable retrieval of data from multiple sources from the HubSpot platform and manage its processing with the third-party tool.

Solution Highlights

  • Developed a microservice that performs data retrieval and handling
  • Ensured that the data manipulation within the microservice is flexible
  • Ensured the seamless integration of the HubSpot-based microservice with the third-party tool
  • Developed a Slack chatbot that posts the status of data synchronization
HubSpot Business Report Automation
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About the Project


HubSpot — a cloud-based CRM platform designed to drive inbound marketing and sales processes. Through a variety of built-in software solutions, it assists businesses in attracting visitors, converting leads, and retaining customers. HubSpot clients are companies from a variety of industries looking for ways to improve the work of their marketing, sales, and other departments.

Challenges & Project Goals:

The customer was looking to build a consistent and fully automated financial reporting flow that would ensure the seamless and error-free management of the activity of the sales department operating via the HubSpot platform.

The goals and challenges of the project were:

  • To achieve a consistent automated financial reporting flow and increase the frequency of reporting to provide the most up-to-date information. Minimize the involvement of manual labor in the process and make the process visible and monitorable by parties involved (Sales/Revenue Ops, Sales department, etc.).
  • To solve the challenge of managing large amounts of data for the activity of the sales department’s personnel, e.g., the number of sales, the list of workers, the number of working hours, financial and sales revenue data, etc. Consequently, calculating the amount of compensation to be paid to each worker, generating corresponding financial reports, and getting them back to the HubSpot platform also presented a problem. 
  • To address the problem of collecting and aggregating various data from different sources, both internal and external. The data was spread across a bunch of already existing IT system microservices and 3rd party tools from different teams or even departments.
  • To deal with the situation that there were a dozen of reports, some of which should be generated every 12 hours, while others, only annually. The reports that served for the calculation of the worker compensation to be paid off took into consideration revenue details, such as discounts, bonuses, etc., as well as a plan of sales for every sales representative. That made the generation of reports extensive and increased the number of variables. 
  • The IT system should be able to support the entire flow of report generating and handling automatically.
  • The team was trusted to run full-cycle development of the microservice for the automation of data handling. It included stages of planning, developing, testing, releasing, and providing technical support and maintenance. The team was also responsible for modifying already existing solutions and providing technical support and maintenance to them as well.


End-to-end development of a microservice that would enable retrieval of data from multiple sources from the HubSpot platform, formation of a report in the form of a table, uploading of it to a third-party tool for financial calculation, and then transferring the results back to HubSpot. Ensure that the system being developed is flexible enough to run distinct phases of the process and ensure the support of the already existing software solutions in the IT system as well as the maintenance and update of the new microservice.

Business Value Delivered:

The Intelliarts team ensured that the IT infrastructure behind the HubSpot platform can now support automated reporting flow. Now generation and transfer of one main and several additional monthly reports to a third-party tool and back to the platform are fully automated. It resulted in 50 hours of manual work saving per month, higher reliability of the reporting flow, and the discovered potential for second-level reporting. It can significantly streamline the management of the sales team activity, which potentially should bring positive financial results.

Location: US
Industry: Software
Partnership period: January 2018 — Now

Technology Consulting, Software Engineering


Cloud Services, Business Intelligence & Analytics, Big Data

Technologies used: Java/JavaScript, Dropwizrad/Jackson/Guice, MySql/Vitess, Amazon S3/SQS (Tq2), Kafka, Snowflake, JavaScript ES6, React/Redux, Selenium/Cucumber, PagerDuty, SignalFx/Grafana, Sentry, IntelliJ IDEA, Visual Studio Code, Github/Zenhub, Jira, Looker

Intelliarts developers have been an integral part of our engineering organization for over four years. They have been responsible for numerous releases of new product features, always on time and with high quality.

Director of Engineering @Hubspot

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Technology Solution

The Intelliarts team ensures that the resulting solution that supports automated reporting flow and has the following features:

  • Integrated microservice. This, along with other software solutions in the IT system, can perform data retrieval, transferring it to a third-party tool and then moving the processed reports back to HubSpot automatically. Engineers implemented lots of data validation and provided control access to the data. The system is designed to support restore/recovery of data in case of system outages. The team built the microservice the way its logic has the tree of dependencies. It enables running the process for data manipulation in a flexible way, for example, starting the process of retrieving data only without sending it to the third-party tool, etc.
  • Integration of the HubSpot-based microservice with the third-party tool. The tool has an artificial language in it, which allows developers to write scripts. The team wrote the script that ensures the data exchange between the microservice and the third-party tool, this way achieving seamless integration. 
  • Slack chatbot. The team developed a chatbot that posts the status of data synchronization and informs about the actions being performed over the reports. 

Business Outcomes

The Intelliarts team was able to essentially contribute to the project through the development of a software solution for report management automation. As a result, 

  • The requested microservice has been released successfully and is used extensively as of now. The project is ongoing, and the developers keep exploring ways to enhance the data management IT system even more. 
  • The team keeps providing continuous support and maintenance as well as releasing updates to the developed microservice as well as to other software solutions in the IT system.
  • Prior to the start of the project, only 1 in the dozen of reports could be generated automatically, but it still couldn’t be transferred to the third-party tool and back without manual labor involvement. As of now, the generation of half the reports is fully automated. Besides, the management of one main monthly report, which is composed of 60 entries for every distinct worker and has up to 100k records in total, and three additional monthly reports are fully automated. It took one year to achieve these results.
  • The team ensured the high performance of software solutions that were presented in the IT system prior to the start of the project. 
  • The team addressed the issue with data collection and aggregation, which required lots of communication and non-trivial engineering solutions. Team members keep working on alternative solutions for the “weak,” unstable, and error-prone parts of the existing data management flow.
  • The team is expected to add several final stages of report processing that are to be executed on the HubSpot platform. This way, automation of the second-level reporting can be achieved. 
  • The team is expected to automate other reports management as well in the near future. 
  • The team managed to reduce the involvement of human resources in the data management process, which led to in total of 50 hours of manual work saving per month. 
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