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10 Top Artificial Intelligence (AI) Solutions in 2022

Weekly Musings In The World Of AI
Weekly Musings In The World Of AI
AI software solutions include general platforms for supporting a range of applications and products for more narrow, industry-specific use cases. We include a sampling of both in the following representative list. With 56% of organizations adopting AI for at least one business function, there are many options on the market today.
Below are ten examples of AI software solutions available in 2022.

Google Cloud AI
Google’s dominant cloud offering includes assorted tools to support developer, data science, and infrastructure use cases. Several speeches and language translation tools, vision, audio, and video tools, and deep and machine earning capabilities bring AI functionality to skilled technology practitioners and mass consumer markets. Google was named a leader in Gartner’s Magic Quadrant for Cloud AI Developer Services in 2022. 
IBM Watson Studio
Like Google, IBM offers a platform for building and training AI software. The IBM Watson Studio provides a multi-cloud architecture for developers, data scientists, and analysts to “build, run and manage”’ AI models collaboratively. With capabilities ranging from AutoAI to explainable AI, DL, model drift, models, and model risk management, the studio gives subject-matter experts the tools they need to either gather and prepare data or create and train AI models.
Salesforce Einstein
Named a leader in Gartner’s Magic Quadrant for CRM Customer Engagement Center thirteen times in a row and the #1 CRM solution for eight consecutive years by the International Data Corporation (IDC), Salesforce provides an advanced kit of sales, marketing, and customer experience tools. Salesforce Einstein is an AI product that helps companies identify patterns in customer data. 
This platform has a set of built-in AI technologies supporting the Einstein bots, prediction builder, forecasting, commerce cloud Einstein, service cloud Einstein, marketing cloud Einstein, and other functions. Users and developers of new and existing cloud applications can also deploy the platform’s predictive and suggestive capabilities into their models. For example, at Salesforce Einstein’s launch in 2016, John Ball, general manager at Einstein, revealed that by creating Einstein, the company “enables sales professionals to find better prospects and close more deals through predictive lead scoring and automatic data capture to convert leads into opportunities and opportunities into deals.”
Oculeus provides an industry-specific solution. For service providers, network operators, and enterprises in the telecom industry that need to protect and defend their communication infrastructure against cyber threats, Oculeus offers a portfolio of software-based solutions that can help them better manage network operations. According to founder and CEO Arnd Baranowski, Oculeus uses AI and automation “to learn about an enterprise’s regular communications traffic and continually monitor it for exceptions to a baseline of expected communications activities. With its AI-driven technologies, suspicious traffic can be identified, investigated and blocked within milliseconds. This is done before any significant financial damage is caused to the enterprise and protects the brand reputation of the telecoms service provider.”
Edsoma represents another narrow use case. Its AI-based reading application software features real-time, exclusive voice identification and recognition technology designed to uncover the strengths and weaknesses in children’s reading. This follow-along technology identifies users’ spoken words and speaking speed to determine if they are saying the words correctly. A correction program helps put them back on track if they mispronounce something.
As Edsoma founder and CEO Kyle Wallgren explained, once “…the electronic book is read, the child’s voice is transcribed in real-time by the automated speech recognition (ASR) system and immediate results are provided, including pronunciation assessment, phonetics, timing, and other facets. These metrics are compiled to help teachers and parents make an informed decision.”
Appen has been one of the early leaders as a source for data required throughout the development lifecycle of AI products. This platform provides and improves image and video data, language processing, text, and even alphanumeric data. 
It follows four steps in preparing data for AI processing: the first step is data sourcing which offers automatic access to over 250 pre-labeled datasets — then data preparation, which provides data annotation, data labeling, and knowledge graphs, and ontology mapping.
The third stage supports model building and development needs with the help of partners like Amazon Web Services, Microsoft, Nvidia, and Google Cloud AI. The final step combines a human evaluation and AI system benchmarking, giving developers an understanding of how their modes work. 
Appen boasts a lingual database of more than 180 languages and a global skill force of over 1 million talents. Of its many features, its AI-assisted data annotation platform is the most popular.
Cognigy is a low-code conversational AI and automation platform recently named a leader in Gartner’s 2022 Magic Quadrant for Enterprise Conversational AI platforms. As the need for more excellent customer experience (CX) intensifies, more enterprises rely on conversational analytics solutions that dive deep into their customer’s text and voice data and discover insights that inform smarter decisions and automate processes.
Synthesis AI‘s solution generates synthetic data that allows developers to create more capable and ethical AI models. Engineers can source several well-labeled, photorealistic images and videos in deploying its models on this platform. These images and videos come perfectly labeled with labels ranging from depth maps, surface normals, segmentation maps, and even 2D/3D landmarks.
Virtual product prototyping and the chance to build more ethical AI with expanded datasets that account for equal identity, appearance, and representations are also some of its product offerings. Organizations can deploy this technology across API documentation, teleconferencing, digital humans, identity verification, and driver monitoring use cases. With 89% of tech executives believing that synthetic data would transform its industry,’s technology may be a great fit.
Tealium’s data orchestration platform is positioned as a universal data hub for businesses seeking a robust customer data platform (CDP) for marketing engagement. This CDP provider offers a tray of solutions in its customer data integration system that allows businesses to connect better with their customers. Tealium’s offerings include a tag management system for enterprises to track and unify their digital marketing deployments (Tealium iQ), an API hub to facilitate enterprise interconnectedness, and an ML-powered data platform (Tealium AudienceStream), and data management solutions.
The company recently sponsored a comprehensive economic impact study from Forrester, calculating ROI on reference customers.
Coro provides holistic cybersecurity solutions for mid-market and small to medium-sized. The platform leverages AI to identify and remediate malware, ransomware, phishing, and bot security threats across all endpoints while reducing the need for a dedicated IT team. In addition, it’s built on the principle of non-disruptive security, allowing it to provide security solutions for organizations with limited security budgets and expertise.
This cybersecurity-as-a-service (CaaS) vendor shows how AI can support higher-level services brought to lower-level business market tiers.
The wave of AI innovation
As AI-powered technologies continue to advance and more organizations adopt them, IT leaders must be sure to ask themselves how the solutions they choose fit into their goals as a business. With so many vendors riding the wave of AI innovation, buyers must select their solutions carefully. 
This Top 10 AI Solution earns to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Tweets we found interesting:
Take a look at @IQTalent’s recent blog outlining the three biggest claims advocates of #ArtificialIntelligence endorse and how they serve to ease the #RecruitingProcess:
Tom Whyman
If I know anything about AI, then 'Artificial intelligence in schools' will massively increase teachers' workloads by forcing them also to pretend the AI works while having to perform all its functions themselves.
Articles related to the topic:
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Council Post: Six AI Trends To Watch In 2022
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Weekly Musings In The World Of AI
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