Businesses are using machine learning and artificial intelligence more according to a Pew Research poll among enterprises in Asia and the USA.
Start-ups¹ in machine learning secured funding of $9.2B in 2018 attracting venture funding in early-stage, angel and seed rounds respectively. Over 9000 companies are using AI solutions and machine learning to facilitate operations and the number is growing according to Crunch Base.
C-suite executives are embracing AI in their strategic management for value addition in the competitive market. Data-driven decisions are helping the C-Suite to boost customer experiences and implementing cost reduction measures across the board. The adoption of intelligent systems² by companies heralds a digital transformation in 2020.
Machine-learning solutions and predictive analytics are transforming enterprises and driving revenue. IKEA from Sweden utilizes machine-learning solutions to understand customer behaviors and developing new products based on market changes.
Machine-learning tools at Amazon are assisting the retail giant to judge customer demand based on previous shopping experiences.
Let us explore some top machine-learning start-ups in 2020
1. A.I Reverie
This is the number one machine-learning start-up attracting attention in 2020 with applications in building and smart home solutions. Businesses face challenges using poorly trained algorithms and AI Reverie bridges this gap by boosting accuracy levels.
Machine learning algorithms³ need proper training with respect to vision APIs and AI Reverie supports industry applications. The machine-learning start-up is supporting operations with new investments of $5.6Min 2020.
Anodot is a machine-learning start-up working with enterprise clients in detecting anomalies in their AI platform. Analytics delivery from Anodot makes the ML start-up vital in the industry because of assisting companies to understand problem areas and develop solutions.
Business technology solutions fail to achieve results and real-time analytics⁴from Anodot is making the difference. Anodot secured a funding of $65M with the latest funding in 2020. This machine-learning start-up communicates incidents in real-time and adds value to enterprises.
Based on the insurance sector, Arturo is offering great solutions for players in insurance through predictive solutions from #deeplearning. With a funding of $8M, Arturo is changing the insurance industry by enabling measurement of risks, market insights, and predicting customer behavior.
Machine-learning tools from Arturo provide advanced intelligence⁵ for insurance companies looking to mitigate costs and become competitive based on data decisions.
Comet ML is changing the data science field by developing a platform for collaboration and enhancing transparency in the development of AI. Machine-learning engineers find this platform applicable because of better workflow coordination and efficiency.
The Comet ML platform reduces tedious workflows by helping data scientists to work with their preferred tools. The Bayesian hyper parameter⁶ from Comet ML supports in the tuning of models and corporate companies find value from services offered by this start-up.
This machine-learning start-up has developed tools for recruitment by matching talent with job requirements. For example, the analytics from Eightfold tracks companies in hiring mode and refers candidates with the required skills to employers.
The team at Eightfold believes that people have the right to choose jobs that suit them and machine-learning tools from this start-up makes this practical. The unemployment problem in the U.S means that machine learning companies such as Eightfold can assist in recruitment practices⁷ and supporting talent management.
Customer experiences are becoming central to the success of organizations in the digital world and Frame is enabling this transformation. Companies use machine-learning solutions from Frame to facilitate decisions about customer behaviors.
The intelligent tools from Frame detect current customer experiences and communicate trends to management for customer-based decisions. With a funding of $10M, Frame is attracting more funding in 2020 as the ML start-up develops voice solutions for customer management by enterprises.
This machine-learning start-up is gaining traction in 2020 with total funding of $2M with its mobile-based advertising. Voice technology using natural language processing from Instreamatic is changing marketing by enabling integrated solutions for businesses.
Dialog ads from Instreamatic make marketing effective for businesses by providing tools for measuring revenues from advertisements. The ML start-up is doing a great job in voice algorithms training⁸ and continues to receive venture interest.
8. Jus Mundi
Content is key when it comes to research and this applies in the legal field where AI and ML tools make this possible. By using machine learning and AI tools, Jus Mundi is accelerating legal research⁹via the search feature.
Data from legal cases, jurisdictions, and treaties around the world assembled in their database facilitates research and analysis for the legal profession.
The Jus Mundi platform combines all data that lawyers need to access in a single directory without sweating for information. Thanks to this innovative technology, this ML start-up attracted total funding of €1M.
Digital transformation has changed performance management and team coordination where companies adopt smart systems to facilitate efficiency. Kaizo is one ML start-up making progress in this space with their AI solutions to boost team coordination and output.
Customer support services use the Kaizo platform for creating effective communication channels that enable them to track feedback based on performance. The same applies to retention measures used by companies and Kaizo makes this practical with their technology tools.
Resource management and production deployment tools from Luminovo use deep learning which enables companies to scale operations. Luminovo bridges the gap between ideation, resources, and implementation, which takes a long time for companies.
Their AI solutions offer an ideal platform for coordinating operations as companies look for efficient production techniques. Deep learning solutions from Luminovo are changing operational expansion with the start-up using this technology to optimize resource management.
Clients working with Luminovo benefit from data insights that enable them to deploy processes while reducing production costs.
Bonus List of Machine-learning Start-ups
Despite listing, the top 10 ML start-ups in this space, these start-ups are contributing to innovation in #machinelearning and AI solutions:
Alation is facilitating strategic management by the use of data and AI tools. This ML start-up offers solutions for engineering and technology executives with data insights needed for decision-making. With new venture funding, Alation is transforming organizational management by using data analytics to understand market trends.
The health care industry is benefitting from patient analytics from Biofourmis for the management of care services. Health professionals use data from Biofourmis to explore patient health trends and offering solutions based on recommendations. Hospitals use data intelligent tools from Biofourmis to treat patients by predicting their health via medical records.
Every enterprise needs a smart system to oversee the IT ecosystem and machine-learning tools from Loom are enabling this experience. #Predictiveanalytics from Loom Systems is helping companies to forecast problems and offer solutions in real-time.
Tracking changes in the company information systems poses challenges to C-suite executives and this platform makes operations convenient. Enterprises using Loom Systems solutions effectively combine marketing and sales for output maximization.
The #digitaltransformation culture means companies need a data system that communicates insights in real-time and Splice Machine is making this a reality. This machine-learning start-up is changing the approach of companies in the use of AI and Ml to make decisions. With a funding of $58M, Splice Machine is building a database for the deployment of machine learning and the #internet of things.
Our last bonus entry is Wave Computing, an ML start-up developing training tools from AI for the management of data centers. This start-up acquired total funding of $205M. Wave computing works with technology companies by assisting in the development of AI solutions for hardware.
The AI inferencing component from Wave Computing has seen the ML start-up launch the TritonAI 64. Wave computing is attracting VC interest in 2020 as the start-up creates new innovative features including performance edge training.
Machine-Learning and Digital Transformation
Companies across different industries are realizing the benefits of using ML and AI solutions in their operations as digitization continues. In the United States alone, job requirements for machine learning have increased by 50% compared to previous years with skills such as #Tensorflow increasing in demand.
From customer support, predictive analytics, and team productivity, enterprises are adopting ML solutions in their workflows. #Datascientists find platforms such as Comet ML suitable for their operations because of collaborative practices and managing deployment. These start-ups are creating solutions and enabling data-driven decisions enterprises need to become competitive.
There are many machine-learning start-ups out there and the list cannot be exhausted. DataRobot, Clari, FogHorn, and Habana Labs are some other Ml start-ups rising fast in the industry with others such as Impact Analytics, Loom Systems, and People.ai developing solutions for the enterprise market.
Applications in healthcare, retail, manufacturing, and transport will fuel new machine-learning start-ups as the #fourthindustrialrevolution beckons. Machines will provide intelligent support alongside humans and these start-ups are taking us closer to this future.
¹Startups, ²Intelligent Systems, ³Algorithms, ⁴Real Time Analytics, ⁵Advanced Intelligence, ⁶Bayesian hyper parameter, ⁷Recruitment Practices, ⁸Voice Algorithms Training,⁹Legal Research