Ten of the Top Artificial Intelligence Start-Ups in 2019

Investors are falling all over themselves to become part of the artificial intelligence innovation. AI-related companies raised 72% more in 2018 than they did in 2017 and the numbers seem set to rise beyond imagination. AI is incorporated into everything today – from self-driving cars to online casino games to military equipment. Artificial Intelligence -based marketing patents are the fasting growing global category, machine learning startups are expanding and may soon become the largest start-up sector.

What are some of the top AI start ups to watch this year?

 

Cinnamon

Cinnamon integrates machine learning and AI techniques so that data extraction from unstructured documents such as invoices, financial statements, legal documents etc. Using Cinnamon.ai, a company can automate data extraction and processing tasks which reduces the speed and cost of identifying needed information.

The goal of Cinnamon is to automate and streamline finding needed information. Using AI, a user attains 85% to 100% accuracy. Presently, the company is marketing to global credit and financial services providers.

 

SymphonyRM

No one denies that the U.S. Healthcare system is complicated, broken and almost impossible to navigate. SymphonyRM is an AI/machine learning platform that allows users to identify the Next Best Action in any situation.

The platform uses predictive analysis across payer and clinical data silos so a provider’s members can manage digital and traditional touch-points proactively while exploring prescribed next best actions. Presently, SymphonyRM arrives as a monthly subscription-based managed service to Care Coordination, Call Center, Provider Marketing and Physician Teams.

 

LogiNext

Using LogiNext, users can innovate logistics and field workforce optimization, route optimization, on-demand management, resource allocation automation and real time tracking. There are also apps for long-haul tracking. last mile management, field workforce management and Reverse and On-Demand Logistics Management.

LogiNext generally serves large enterprises that have frequent movements of assets, vehicles, repair workers, field technicians or sales personnel.

 

People.ai

People.ai focuses on revenue management to help marketing, customer success and sales teams uncover all possible revenue opportunities from every customer. All customer contacts, engagement and activities are collected via real time integration. The system then analyzes the aggregated data, with the goal to solve the problem of how to get enough data on each customer and potential customer to make better sales decisions.

The system includes sales performance analytics, pipeline reviews, personalized coaching and one-on-one feedback. Marketers often use people.ai to measure marketing campaigns and fine-tune them.

 

Biofourmis

Biofourmis is a digital health tech start-up that combines AI, machine learning and real-time monitoring to reinvent remote patient monitoring. Their platform can detect personalized patterns that predict a patient’s health condition along with leading indicators of potential health deterioration. One of the Biofourmis platforms, Biovitals, offers sophisticated personalized physiological data analysis.

It tunes into human physiology to formulate personalized health models which result in accurate prediction of patient health deterioration using highly optimized post-acute patient monitoring solutions. Through the use of bio-sensors and connected devices the platform captures physiological signals to detect abnormalities. Using this technology, medical professionals can intervene before a critical event occurs.

 

Ravin

Ravin uses machine learning, AI and traffic monitoring cameras to collect continuous real-time data via life-streaming video. The data is used to analyze a vehicles’ current condition which provides greater transparency to fleet owners, used car sales networks and rental car companies.

Machine learning combines with AI to evaluate and immediately report on possible anomalies in the condition of a vehicle. The goal is to increase the level of transparency and trust in any vehicle being monitored.

 

Terramonitor

Terramonitor leverages up-to-date satellite data, AI, and machine learning through analyzing, building and organizing geographical information into actionable insights.

Using this innovative approach, satellite data processes chains, multi-source data merging and automatic image scanning. Data capture combines with machine learning analysis and advanced

AI to analyze broad geographic regions for environmental, agricultural, infrastructure and forestry-related insights.

 

CrowdStrike

CrowdStrike applies machine learning to endpoint detection of IT network threats. CrowdStrike is one of the newest, and potentially most powerful tools in the growing cybersecurity market. Their Falcon platform has garnered particular notice for its ability to stop breaches by detecting attack types. It provides five-second visibility across all past and current endpoint activities while, at the same time, reducing complexity and cost.

Via the CrowdStrike Threat Graph analysts can see real time data from endpoint events across the crowdsourcing community. This allows for prevention and detection of attacks based through patented behavioral pattern recognition technology.

 

Prowler

Prowler is an AI/machine learning platform that focuses on building autonomous agents for decision-support simulations and games. The startup is focusing on simulation and behavioral learning in virtual environments. The core intellectual property and technologies have the potential to redefine the smart city and video game simulation landscapes through the creation of collaborative bots who can, over time, mimic learned behaviors.

 

Impact Analytics

Impact Analytics capitalizes on the inherent strengths of machine learning and AI to find anomalies, trends and patterns in new data sets and legacy data. Impact Analytics makes its most significant contributions in the field of recently launched business models through marketing analytics, customer analytics, margin improvement, merchandising optimization, robotic process automation and operational improvements.

Impact Analytics is being successfully deployed across the retail industry with customer references in financial institutions and banking.

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