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Audit and future-proof, scaleable dataflows
Case study details
A start-up developing a pioneer Automated AI for Conversation Intelligence was hugely aware that ETL processes are the Heart of their product that can make or break its market traction.
Company’s founding idea is bold, and as remote work becomes increasingly popular, it also has a chance for a good market fit. The product’s core feature is to attend and transcribe Zoom and Google meetings automatically.
This bot can be delegated to any call as a “passive participant” and transcribe meetings for those who can’t be there.
Challenge
The company reached Addepto consultants to run the audit and design future-proof and scaleable dataflows.
Approach
The long-term plan assumes connecting conversational data collected directly by the bot with those from different systems such as CRM, marketing automation, etc.
Goal
The goal is to derive the most valuable insights and put them in the user-friendly form of dashboards or other visualizations.
Outcome
The client not only received an audit but also benefited from a consultation service.
This helped them validate the assumptions they had made at the outset in terms of best ETL practices, potentially leading to cost savings and optimization of further development.
Challenge
Given all of this, the ETL processes, which smoothly combines data from multiple sources into a single, consistent data store or another target system, had to be absolutely impeccable. The company’s managers were deeply aware of it.
The company reached out to Addepto Team to run an audit and check if their processes were indeed bullet-proof.
Instead of relying solely on in-house resources, at some point, the company decided to gain a fresh external perspective.
Approach
The goal seemed, at first glance, very typical. Addepto Team was familiar with running audits and improving ETL processes in companies across sizes and industries, so why might this time have been different?
Well, as soon as the Addepto consultants stepped into the company, it turned out that although the product strategy was well-thought, the product itself was still in the very early stage of development, when there were still many variables and unknowns.
During project development, our team worked on:
- Addepto Team decided to revamp some of the AI models in order to avoid bottlenecks that might jeopardize the whole process in the following steps.
- The start-up environment made it impossible to run the audit "by the book" by reverse-checking all the ETL processes, as not many were already set in stone.
Goal
Addepto Delivered
The company’s goal was straightforward:
The company had a great and very ambitious idea.
To transform it into a functioning product - it wanted to double-check all core elements, which were, in this case, the ETL processes.
Outcome
Outcome
After embracing the consultant approach, Addepto Team dived deep into company’s business logic. It ran through the long-term strategic plans for further development of this product to detect whether some dataflow bottlenecks might stop or slow down its different implementation.
About Addepto
We assist businesses in leveraging AI technologies, including machine and deep learning, to improve their data utilization.
Here you can learn more about the technologies used in this project:
We enable the creation of data-driven services that enhance customer satisfaction, boost revenue, and expedite internal processes.
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Edwin Lisowski
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- hi@addepto.com
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