We used the CB Insights Mosaic score to identify promising companies using machine learning and deep learning algorithms to provide predictive insights based on IoT data.
Funding dollars to Internet of Things startups jumped 31% in the first quarter of this year, compared to Q4’15. That was the second-highest total yet in a quarter.
As industrial and business processes are more frequently mediated by the IoT, and IoT-driven analytics solidifies as a category, startups are leveraging machine learning and deep learning to provide predictive insights based on the data collected from wearables and sensors.
Just in the last quarter, companies like Tellmeplus, Neura, and Sentenai raised funds to integrate machine learning algorithms with different IoT functions, including data collection, sorting, analyzing, insights, and automation.
“A good IoT solution gives you an extraordinarily useful view of your organization’s data; a great one allows you to build algorithms that can predict what’s next…” – Microsoft IoT blog.
We used the CB Insights Mosaic algorithm, which tracks the health of private companies, to identify some early-stage startups in the seed/angel and Series A stage with traction (Mosaic has three components, which gauge a company’s health in terms of financing, industry category, and overall momentum). The list includes startups that have raised an equity funding round after January 2014, but have not yet raised a Series B.
The companies are working on applications ranging from remote patient monitoring to smart building solutions.
Majority of the companies on the list, 15 out of 17, have VC backing. While companies like Tachyus and Tellmeplus provide industrial IoT solutions, others like Building Robotics, and PointGrab focus on commercial spaces and smart buildings.
In the healthcare sector, Moov, a company manufacturing a motion-sensing wearable fitness device, announced last year that it will come with an AI coach that uses the data collected to provide personalized feedback.
Another digital health startup, Sentrian, monitors patients’ health remotely, collecting data from bio sensors.
The table below describes how each company is integrating deep learning and machine learning algorithms into their products.
| Company | Description | Funding (USD) | Select Investors |
|---|---|---|---|
| Tachyus | End-to-end solutions for the oil and gas industry, including equipment failure predictions | $20.9M | Founders Fund, Caffeinated Capital, Formation 8, Founders Fund and Streamlined Ventures |
| Sentrian | Remote patient monitoring platform that analyzes bio-sensor data; uses machine learning to send patient-specific alerts to clinicians and learn from their feedback | $15.8M | Frost Data Capital, Reed Elsevier Ventures, TELUS Ventures |
| Maana | Caims to be the first big data search engine powered by Spark; supports machine learning and data mining of massive amounts of data in industries like oil & gas | $14.1M | Chevron Technology Ventures, ConocoPhillips Technology Ventures, Frost Data Capital, GE Ventures and Intel Capital |
| Veros Systems | Uses machine learning to isolate electrical problems in motor-driven devices | $13.2M | Austin Ventures, Chevron Technology Ventures, LiveOak Venture Partners, Shell Technology Ventures |
| Neura | App that helps connected devices adapt to user behavior | $13M | AXA Strategic Ventures, Lenovo Group, Liberty Media, Pitango Venture Capital, Microsoft Ventures |
| Augury Systems | Uses signal-processing and machine learning to diagnose a machine’s health by comprehending the sound it produces | $9M | First Round Capital, Formation 8, Lerer Hippeau Ventures, Pritzker Group Venture Capital |
| Glassbeam | Glassbeam Studio attempts to automate the process of converting raw machine data into usable format | $7.98M | VKRM |
| Building Robotics | Localized air temperature regulation in commercial buildings; uses machine learning to learn people’s preferences over time | $6.64M | Claremont Creek Ventures, Formation 8, Google Ventures, Navitas Capital, Red Swan Ventures, Westly Group |
| mnubo | Data analytics platform for agriculture, smart homes, consumer and other IoT verticals | $6M | McRock Capital, White Star Capital |
| C-B4 | Uses data compression, pattern recognition and machine learning to analyze IoT data | $6M | Sequoia Capital Israel |
| PointGrab | Uses deep-learning to provide occupant analytics and insights about energy saving in IoT-based building automation systems | $5M | ABB Technology Ventures, EcoMachines Incubator, Flextronics International |
| Tellmeplus | Develops machine learning software that can be used in the IoT industry for predictive analytics | $4.7M | Runa Capital, Sferen Innovation, Soridec, Ventech, XAnge Private Equity |
| Moov | Fitness wearable with an AI-based personal coach | $3M | Banyan Capital |
| Sentenai | Cloud platform using machine learning techniques to automate ingestion and sorting of huge amounts of data | $1.8M | Flybridge Capital Partners, Founder Collective, Hyperplane Venture Capital and Project 11 Ventures |
| Imagimob | AI-based motion intelligence system | $0.37M | Stockholm Business Angels |
| Focusmotion | Applies machine learning to data from body sensors and wearables to provide intelligent analytics on human motion | $0.2M | Dodgers Accelerator, Drummond Road Capital, Scrum Ventures |
| MoBagel | Cloud-based analytics platform for IoT compaines that uses machine learning to predict product trends and forecast sales, among other things. | $0.08M | 500 Accelerator |
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This report was created with data from CB Insights’ emerging technology insights platform, which offers clarity into emerging tech and new business strategies through tools like:
- Earnings Transcripts Search Engine & Analytics to get an information edge on competitors’ and incumbents’ strategies
- Patent Analytics to see where innovation is happening next
- Company Mosaic Scores to evaluate startup health, based on our National Science Foundation-backed algorithm
- Business Relationships to quickly see a company’s competitors, partners, and more
- Market Sizing Tools to visualize market growth and spot the next big opportunity