MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).
MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.
Jose Chan, VP of Business Development, Celect
This company was founded by Vivek Farias, whose early talk into Slice Learning I have documented. They work on inventory optimisation for retail – providing actionable insights from sparse consumer data. They answer questions in the plan, buy, fulfilment and allocation problem space – eg what to buy, where to put it and how to fulfil it.
Aaron Howell, Chief Customer Officer, Relativity6
Relativity6 looks to reactivate lapsed customers with machine learning. The lapsed customer is undervalued – 1) there is revenue associated with winning these customers back 2) there is learning about preventing future lapses. They have developed a software platform that consists of proprietary behavioural listening algorithms about what they purchased, when they purchased and which email they opened – avoiding biased data surveys. They already have a large number of customers in retail, transportation and finance (insurance).
Abhi Yadav, CEO & Founder, ZyloTech
AI powered retention marketing platform to automate customer data curation and analytics. There is a divide between big data and big insights – due to problems with requiring many data scientists, slow analytics, poor data quality leading to fragmented insights. Their solution performs data normalisation and data curation with auto-selected features, algorithms, parameters and allowing continuous learning and analysis from new data. They have multiple customers.
Jon Garrity, Founder & CEO, Tagup
Each turbine in a plane is around 16 million with 30 million contract for service. These companies can take real-time data in-flight to monitor the health of their assets and avoid down-time. Jon has been inspired by this approach and created a similar approach for other industrial machines. Eg – doing a project to monitor 20000 network electric transformers – monitoring temperature and other parameters to build health models to predict function and to prevent failures.
Rony Kubat, Co-Founder, Tulip
Tulip work on human centred digital transformation – they help manufacturers “make their stuff higher quality and faster”. The platform is a way for an engineer to create an application (without programming) to collect data from the factory floor using IoT and use that to continuously improve that line flexibly. In Tulip customers, this has lead to decreased defect rates and increased productivity.
Glynnis Kearney, VP of Product & Strategy, Gamalon
Help companies extract value from unstructured customer data including names and addresses, free text – customers use this to power marketing and customer service. They use a proprietary ML solution called “idea learning’. 80% of enterprise data is unstructured – leading to a lag or latency in using that data usefully – eg customer complaints, industry trends and news. In the past, different parts of a sentence need to be labelled by the ML, requiring huge datasets. Gamalon only requires small 100 piece datasets to do the same.
Joshua Feast, Co-Founder & CEO, Cogito
Cogito provides live guidance and real-time measurement of customer perception during calls – with the use case of conversation coaching for call centres, and enhancing agent emotional intelligence. They have a number of large customers in insurance and financial services, driving win-win-win situations for employees, consumers and companies.
Vinayak Ranade, CEO, Drafted
Drafted helps customers hire better. It scales hiring through referral networks using all possible contacts – it leverages ML and AI to find the best candidate for your vacancy.
Molly Bales, Chief Development Officer, Adappt Intelligence
Adappt Intelligence provides work space analytics. The problem is that retail space is the 2nd largest cost for an organisation but organisations have no data for analysing this – leading to space inefficiency or employee inconvenience and discomfort. The solution is 1) a desk sensor and 2) a people counting sensor – the data is then analysed real-time. They have deployed 7000 sensors over 2 years. The British bank was their first example – they gained valuable insights with a misperception of their building occupancy.
Aidan Cardella, SVP of Operations, TVision
TVision measures eyes on screen time – advertisement is big business but when and how often does the viewer actually pay attention? They have sensors and analytics to answer this question.
Matt Osman, CEO and Co-Founder, Legit Patents
Legit Patents streamline the intellectual property process using AI. Building a AI powered patent factory for enterprise. They match free text descriptions of your invention against the whole database of existing patents to 1) track invention quality in real time 2) file more valuable IP at scale and 3) identify fruitful areas of innovation 4) identify inventors who may be useful in that situation.
Anjali Midha, CEO and Co-Founder, Diesel Labs
Diesel Labs provide bid data analytics for mobile video marketers.