Mimica – Saving employee time by automating repetitive processes

Mimica – Saving employee time by automating repetitive processes

COMPANY

Name: Mimica

Legal Name: Mimica

Location: London, UK

Founded: 2018

Founders: Raphael Holca-Lamarre and Tuhin Chakraborty

Website: https://mimica.ai/

Social Media Following: 190 followers on LinkedIn

Introduction

Imagine your computer learning to take care of your repetitive, administrative work for you. That’s the future Mimica is building. The company is developing a new software that learns to automate certain processes just by observing it, thus eliminating the need for developers and making the technology accessible to everyone. 

This approach dramatically broadens automation potential within a business as all the low-volume, bespoke tasks that never warranted attention suddenly become viable candidates for automation, opening up a previously untapped $5 trillion market.

The Product

The first product Mimica has brought out into the market is an automated process mapping solution. The platform’s algorithms learn by watching you work, observing clicks and keystrokes, and using machine learning to identify repetition and patterns within this dataset. 

The mapper sits on an employee’s computer and continuously records their process for 2-3 weeks. The machine learning algorithms then clean, analyze and merge the recordings into a single, elegant process map. These maps are used for RPA, time-and-motion studies, business process management and more.

Origin and Founding Team

Raphael Holca-Lamarre is Co-Founder and CSO. He holds a Ph.D. at the intersection of disciplines such as neuroscience and machine learning, developing brain-inspired learning algorithms for deep neural networks. 

Tuhin Chakraborty, Co-Founder & CEO, is a graduate from Stanford University. He comes with experience from earlier stints at LinkedIn and Pandora. 

With Mimica, the two co-founders aim to leverage their collective expertise and experiences in building enterprise applications, automation, and machine learning to help organizations move away from time-consuming and error-prone manual programming with more cost-effective solutions.

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