The challenge for most companies today isn’t that they don’t understand what machine learning is, but rather that they don’t know what it’s for.
What most executives struggle with is coming up with a pilot project which uses the technology and produces real value for their organization.
Here at Silicon Valley Innovation Center, we understand that problem better than anyone else; it’s our business to help top managers connect with innovative startups and see the opportunities created by disruptive new technologies.
That’s why we’ve put together this list of some of the best and brightest machine learning startups currently operating in the Valley. We’ve grouped them by industry so you can easily see which ones are most relevant to your business.
Table of Contents:
- Manufacturing/Industrial Automation/Industry 4.0
- Financial Services/FinTech/Insurance
- Energy & Utilities
- Connected Transportation/Logistics, Drones, and Logistics
- E-commerce, Retail, & Media
- Online Gaming & IT Services
- Real Estate
Manufacturing/Industrial Automation/Industry 4.0
Sight Machine’s analytics platform is used by discrete and process manufacturers to flag critical challenges in quality and productivity. Using artificial intelligence, machine learning and advanced analytics, it has several use cases:
- Quality Management: Scrap reduction, Increase first-pass yield, Using alerts for process consistency, Elimination of non-conformance to specs
- Productivity Management: Improve OEE, increase throughput and optimize asset utilization
- Visibility: Gain real-time visibility into every machine, line and plant throughout an enterprise
Sight machine’s customers come from across the manufacturing spectrum; where some are involved in the automotive sector, others are from packaging or material handling. Whatever the industry the company believes its software can deliver deep insights into the manufacturing process, producing big cost and time savings in the process.
Mtell provides software solutions for managing the health of industrial equipment through prescriptive maintenance.
On a Silicon Valley executive visit, you’ll have the chance to see for yourself how Mtell collects data streams from machines and then uses them to predict when maintenance will be needed.
The techniques deployed to do this are a diverse range of scientific, computational and mathematical disciplines and business rules.
Prediction is only half of the innovation; Mtell’s real value is that it can use all the collected data to say exactly what maintenance is needed and when.
IoTium is a provider of managed, secure network infrastructure for the Industrial Internet of Things (IIoT). Its products have diverse range of applications including:
- Building and Industrial automation
- Oil and gas
- Smart city
“Every single industrial IoT vertical which has a legacy machine of any sort that has a proprietary protocol; to be able to connect that securely to an application that resides in a public, private or hybrid cloud would be a dilemma for most people,” says Ron Victor, founder and CEO of IoTium.
On your next Silicon Valley trip you’ll have the opportunity to learn how the company is helping oil rigs, power plants, refineries and factories with legacy brownfield machines to connect and transport data to the cloud.
Aera Technology is a platform for enterprise decision making that uses artificial intelligence, machine learning, natural language processing, data and enterprise domain expertise to produce results. It can:
- Predict outcomes
- Take action autonomously
- Make real-time recommendations
Use your next Silicon Valley trip to meet the Aera Technology executive team and learn how you can use AI to reimagine your organization’s future.
Sparkling Logic helps companies make better decisions using machine learning, business rules, and decision analytics.
Typical use cases and applications of the company’s technology include:
- Dynamic pricing to extract maximum value from customer interactions.
- Customer experience management in healthcare and financial services using the technology as a recommendation engine for online customers.
- Fraud, Risk management, and compliance in the financial services industry to manage flash fraud for tens of millions of daily transactions.
- Internet of Things in the energy and utilities industries to monitor equipment remotely via sensors.
Sparkling logic’s customers come from a range of industries including financial services, healthcare & wellness, energy & utilities and insurance. Regardless of the sector the tech company’s aims remain the same: to use data and machine learning to optimize decision business decision making.
ZestFinance provides an end-to-end machine learning underwriting platform that customers use to pinpoint more accurate credit scores. It can also be used for:
- AML (Anti-money Laundering) measures
The company’s Zest Automated Machine Learning (ZAML™) consumes vast amounts of data to more accurately identify good borrowers. This in turn enables higher repayment rates for lenders and lower cost credit for consumers. Key customers of the technology are banks and insurance companies.
Energy & Utilities
Orbital Insight is a geospatial big data company using advanced image processing and data science to understand and characterize socio-economic trends on a global, regional, and hyper-local scale. It deploys machine learning, deep learning and AI technologies to predict future events.
Typical use cases include:
- Supply chain tracking and visibility
- Demographic monitoring
- geospatial analytics at scale
It’s technology is used by customers in:
- Consumer goods
- Financial services
Connected Transportation/Logistics, Drones, and Logistics
Deep Vision states that it is on a mission to use computer vision in machines including everything from cars to robots to drones. The company boasts of a “completely new approach” and uses what it calls an “ultra low power” processor to run deep learning and other computer vision algorithms.
Neurala operates The Neurala Brain, a deep-learning piece of neural network software that mimics how the human brain works.
Key use cases of Neurala include:
- Drone inspections
- Finding and recognizing objects
- Finding and tracking
The Neurala technology is applicable in verticals such as drones, robots, consumer products, and self-driving cars. Join us for a Silicon Valley executive visit to see up close how Neurala’s machine learning and AI experts are using the technology in industries such as manufacturing, transportation and telecoms.
E-commerce, Retail, & Media
NanoNets is a Software-as-a-Service product and a machine learning API (application programming interface) for building machine learning models.
Typical use cases include:
- Tagging clothes
- Identifying animals/type of trees from images
- Identifying body parts from an X-Ray
- Identifying car types from photographs
The company’s machine learning technology has applications in e-commerce, travel and media to name just a few possible industries.
In one of the programs offered by Silicon Valley Tours you can learn how experts at Nanonets build rich representations of data that are transferable across tasks and domains. You can also explore how Nanonets can help you adopt machine learning technology for your own business.
CrowdFlower is a data mining and crowdsourcing company. Its platform is used by data science and machine learning teams to perform sentiment analysis, search relevance and business data classification.
Typical use cases include content moderation, data collection, image annotation and sentiment analysis. CrowdFlower’s clients include Intuit, YouTube, IBM, eBay and Spotify as well as others from across the software-as-a-service, e-commerce and media sectors.
Online Gaming & IT Services
Cognizant is an American multinational providing business consulting services. It has a strong emphasis on all things digital and tech. Its clients come from a diverse range of industries including:
- Banking & financial services
- Consumer goods
- Energy & utilities
Cognizant sells itself as offering “robust digital solutions” to its clients. In keeping with the latest trends, the consultancy is currently focused on technologies like blockchain, machine learning, and artificial intelligence.
Scientific Revenue helps mobile game developers get more money out of their creations. The company’s artificial intelligence reads signals from gamers and uses that data to provide dynamic pricing for in-game purchases. The company uses machine learning technology to carry out sophisticated user profiling and then produces user-specific pricing plans.
Scientific Revenue says games which use its technology have been downloaded more than 100,000,000 times. It claims to be able to boost revenues for game developers by 20% to 40%.
Amitree uses artificial intelligence and machine learning to automate and optimize the real estate industry. The company is the creator of Folio, an intelligent assistant for real estate transactions. Folio automatically organizes key transaction details for real estate agents
Typical use cases of Amitree’s machine learning technology in the real estate sector include:
- Automatically organizing transactions
- Documents and file access
- Timeline sharing
- Reminder & notes
Clients include real estate agents and companies operating in the real estate industry.
Executives can think of machine learning as a means to accelerating the digital transformation journey of their company.
Although the learning curve can be steep, interacting with companies at the forefront of the technology is one approach which can have a significant positive influence on outcomes.
The 16 companies we’ve presented here are just a fraction of the many operating in Silicon Valley which are committed to using machine learning to disrupt industries and drive innovation.
Undoubtedly, big things are expected from machine learning and AI in general. As predicted by consulting firm Deloitte, this year “the number of implementations and pilot projects using the technology will double compared with 2017, and they will have doubled again by 2020.”