In the past few years, there has been a lot of buzz over AI and how businesses and consumers can benefit from it. Many believe that an integrated AI strategy can boost customer experience and communication, strengthen brand loyalty, save time and money, reduce error, and generate better business insights. But how to find the one AI partner that will take your business to the next level? To help you with that, we present you with our list of the most accomplished AI companies.
AI Powered Augmented Analytics
Award-winning Deeper Insights is an AI company with an impeccable reputation and vast experience in Machine Learning, NLP, and Data Science consultancy. Specializing in projects such as chatbot development, prediction models, pattern recognition in Big Data, and more, Deeper Insights is the right choice for those willing to make bolder decisions. The company dives deep into the minds of your customers and competitors, reaching data others can’t, to give you context that matters.
Highlights
- Started : 2014
- Number Of Employees : 10-49
- Location : London
Cyprus-based InData Labs, which boasts its own R&D center, is a top-notch provider of AI solutions with a clear mission to bring the benefits of AI to every business. With a portfolio of over 40+ AI-powered projects, expertise in predictive analytics, forecasting, recommendation systems, text analysis, and computer vision, cognitive computing, and proprietary technologies, InData Labs truly is a leader in the extraordinary world of AI.
Highlights
- Started : 2014
- Number Of Employees :50 – 249
- Location :Nicosia, Cyprus
Diffco is a renowned and multi-award-winning mobile app development and artificial intelligence company operating in Sunnyvale, California. With over 12 years of experience in the industry and more than 1,000 successfully launched projects, Diffco’s team remains focused on developing and delivering sophisticated mobile apps and solutions for startups and enterprises powered by AI and secure architecture.
Highlights
- Started : 2008
- Number Of Employees :50 – 249
- Location :Sunnyvale, United States
Founded in 2017, KODA is a leader in automation software development with a mission to change the way communication processes work. Thanks to its automated communication management software, this AI company has so far helped numerous organizations scale their business by automating communication processes via voice and chat.
Highlights
- Started : 2017
- Number Of Employees :10 – 49
- Location :Wrocław, Poland
Headquartered in Belarus with offices in Poland, Ukraine, and Slovenia, APRO Software is a custom software development company specializing in artificial intelligence, web, and mobile applications. As one of the best AI companies, APRO relies on its superior OpenX method to simplify the development process related to artificial intelligence and deliver better communication to customers. Having completed more than 300 projects, APRO promises state-of-the-art products and services to companies of all sizes.
Highlights
- Started : 2000
- Number Of Employees :10 – 49
- Location :Vancouver, Canada
If you’re looking for exceptionally talented and experienced engineers and business analysts, Integrio Systems is where you’ll find them. As a custom software development company with more than 20 years of experience and over 200 successful projects, Integrio Systems has been helping both SMEs and Fortune 500 companies realize their goals because they excel at delivering scalable solutions for the most complex ideas.
Highlights
- Started : 2000
- Number Of Employees :10 – 49
- Location :Vancouver, Canada
Listed as one of the top 30 AI software companies and a leading chatbot development firm, BotsCrew makes chatbots and voice assistants for startups and Fortune 500 clients for faster, smoother, and more convenient customer communication. Having worked with the likes of Samsung NEXT, Mars, Virgin, and BMC, the goal of BotsCrew is to help their clients thrive by integrating their most used tools into a single, comprehensive solution.
Highlights
- Started : 2016
- Number Of Employees :10 – 49
- Location :Vancouver, Canada
Headquartered in Poland, Alphamoon is an award-winning artificial intelligence company dedicated to helping businesses across the globe improve their efficiency, reduce time and resource consumption, and have more control over their everyday processes. The mission of Alphamoon is to provide access to cutting-edge technologies and AI solutions to reduce human error and accelerate everyday, routine tasks.
Highlights
- Started : 2017
- Number Of Employees :10 – 49
- Location :Wrocław, Poland
Named a top mobile app development firm in the UK, endorsed by Time and Forbes, Poland-based Miquido is an artificial intelligence company with offices across Europe. From AI, cloud deployment, R&D to web and mobile development, Miqido will do all you need and will do it pixel perfect.
Highlights
- Started : 2011
- Number Of Employees :50 – 249
- Location :Kraków, Poland
How We Selected the Top AI Companies
With AI slowly but surely penetrating every industry, from automotive, through customer service to healthcare and science, we had to take a much broader approach in compiling our list of the best in the field. In doing so, we followed strict criteria and picked only the companies that can deliver the most challenging projects by leveraging AI. And since maturity and experience are essential, we dismissed many young outfits almost immediately. Note that our list does not include the biggest AI companies or giants like NVIDIA, Amazon, Google, or Apple.
Portfolio & Website Assessment
The secret to an outstanding AI-powered project lies in its implementation. This is why we started our evaluation with a thorough analysis of the work displayed on the websites of our targeted companies. In general, the portfolios of companies working in this field are packed with case studies describing projects from how it all started and what the client wanted to the brainstorming process and trial runs made by the team.
Since many of the top artificial intelligence companies post samples of their products, we used the opportunity to compare them to industry standards and assess the team’s capabilities and service focus. We prioritized companies that base their work on established processes and AI techniques because this is an indicator that they use thoroughly processed data to make effective decisions and deliver reliable products.
Viability & Experience
To ensure that the AI company can meet expectations, we considered each firm’s experience. Unlike the projects of web development companies that are short-cycled, artificial intelligence companies could take over a year to launch a product. This is why we selected outfits with more than five years of experience. We believe that once a company working in artificial intelligence passes this threshold, they will have become more mature and will have developed the “patience” that AI projects demand. Popular opinion is that this is the normal timeframe for a startup to work on a product, launch it on the market, acquire some customers, and be ready and well organized for growth.
AI Service Catalog
Companies developing AI offer a plethora of services and solutions. But calling something AI does not necessarily make it so. Instead, artificial intelligence is about handling big data, the output, or the findings that come from processing it. To weed out the professionals from the pretenders, our next big step was to consider the services offered and evaluate them accordingly.
Types of AI
A simulation of human intelligence processes or mimicking human cognitive abilities is at the core of AI. In practice though, artificial intelligence can be anything from machine learning, natural language processing, and automation to computer vision, speech recognition, etc. Based on how successful a machine is in doing so, AI companies distinguish three main types of AI:
- Artificial Narrow Intelligence (ANI), also known as “weak,” is the only type that has been successfully realized to date and typically performs singular tasks. This type of AI doesn’t replicate human intelligence but simulates human behavior based on a narrow range of parameters and contexts. Siri and Alexa are good examples.
- Artificial General Intelligence (AGI) or “deep” AI is when a machine has the ability to learn and apply its intelligence to solve problems. An AGI can think and act just like humans. So far, only one of the leading AI companies has succeeded in developing strong AI — Fujitsu’s supercomputer K.
- Artificial Super Intelligence (ASI) will not only mimic and understand human intelligence and behavior, but it will also surpass our cognitive performances. Although still hypothetical, an ASI would understand human emotions and have its own needs, beliefs, and desires.
Basic Functionalities and Capabilities of AI
In addition to the three types of AI-enabled machines according to how much they resemble a human mind, there is another classification based on their function and capacity. According to what needs an AI-based system covers, and its purpose, experts and companies developing artificial intelligence distinguish between:
Reactive Machines are the most basic AI systems and cannot form memories or act based on experience. These systems only react to the world they perceive around them, there is no learning process. An example of a reactive AI machine is the chess-playing supercomputer called Deep Blue. It can identify all the pawns and knows what moves are allowed which is how it makes predictions and chooses the most optimal moves. What is important here for our evaluation of AI companies, is that these models have the simplest architecture and can be downloaded, loaded into a developer’s toolkit, or traded.
Limited Memory machines can store previous data and use it to make better predictions. Self-driving cars are an excellent example as they use reprogrammed representations of the world like lane markings or traffic lights so it knows when to change lanes, avoid cutting off another driver, or being hit by a nearby car. These AI systems have more complex architecture but still, the data about the past is transient and not stored as an experience the machine can learn from.
Theory of Mind comes from psychology and refers to the notion that people, creatures, and other entities’ behavior is affected by their thoughts and emotions. Even though many of the leading artificial intelligence companies are working on developing a machine that would understand social interactions, an AI with “a mind of its own” has not yet been developed.
Self-Awareness goes beyond building an AI system that has a mind of its own into developing an entity with a consciousness of its own. But to build a self-aware and independent intelligence, AI researchers and developers must first understand consciousness. A self-aware AI would have the natural parental instincts and human-like emotions we saw embodied in the Mother character from Raised by Wolves.
AI Subsets
You might think the best artificial intelligence companies specialize in all of these subsets but unfortunately, or luckily for smaller companies, this is not the case. Given the complexity of AI processes and the many aspects of cognitive capabilities, we made our artificial intelligence company list more diverse to include a wider range of services and solutions.
Machine Learning (ML)
As an AI branch, ML enables computers to use data to self-learn and apply what they have learned without any human assistance or intervention. In other words, machines are programmed to learn from experiences. This AI subset does wonders in processing and extracting patterns from data, and it does it faster than any human would. This AI subset focuses on algorithm design and development. AI firms specializing in machine learning typically use it for risk analysis, fraud detection, GPS-based predictions, targeted marketing campaigns, etc.
Machine learning has several subtypes such as supervised learning or learning from known datasets, and unsupervised learning or training algorithms by using unlabelled and unclassified data. There is also reinforcement learning or training an AI agent based on feedback from an action performed. Deep neural learning meanwhile aims to train a machine to perform human-like tasks. For example, product and content recommendations for Amazon and Netflix are powered by deep learning.
Natural Language Processing (NLP)
The ability of computers to extract keywords and phrases, understand the message and intent of the language, and generate a response is NP. To better process unstructured speech, some AI companies use machine and deep learning methods in combination with NLP. Whether you treat it as a subfield of linguistics studying the interaction between humans and computers or the offspring of AI and human language, thanks to NLP, humans can talk to machines, with Alexa and Siri the “living proof” of that.
Expert Systems
Those are reliable and interactive AI systems that use facts and heuristics to make decisions and solve complex problems. Expert systems use human intelligence and expertise and try to copy the decision-making abilities of human experts. These AI systems possess knowledge from experts thus offering the highest level of expertise, accuracy, and imaginative problem-solving. Expert systems are widely used in medicine.
Machine Vision
AI development companies working on machine vision help a computer “see” or detect something by adding cameras analog-to-digital conversion (ADC) and digital signal processing (DSP). Machine vision is everywhere, in industrial and non-industrial applications. Thanks to this type of AI we can read serial numbers and count items effortlessly.
Speech Recognition
The ability of a machine to identify words and convert them into text is speech recognition. These AI systems recognize spoken language by breaking down the audio into individual sounds and then using algorithms, detect the word and transcribe sounds into text. AI companies specializing in this field train the system by storing speech patterns and vocabulary into it. Note that NLP and speech recognition are usually used together for developing speech analytics tools or voice assistants.
Robotics
This is perhaps the most sizzling field of AI and for the most part, it focuses on designing and developing machines to perform actions automatically or semi-automatically. As a field, robotics is tied to mechanical engineering, electrical engineering, computer science, and more. Robots are usually deployed to execute tasks that are difficult to perform consistently which is why they have applications in industries such as manufacturing, mass production of consumer and industrial goods, transport, earth and space exploration, surgery, etc.
Expertise in Relevant AI Tools
Since by 2021 a staggering 80% of emerging technologies will be based on AI, keeping pace with this trend is essential, including for marketers. Choosing one of the best AI companies out there will not only help marketers establish a more data-driven strategy but will also help them improve prioritization, personalization, and the overall content of their campaigns. To accomplish this, you need teams with relevant expertise and knowledge in AI tools.
Frameworks & Libraries
A library will give you full control of the flow of the application, similar to owning a home and going to a furniture store to buy some extra furniture that goes with your interior. A framework, by contrast, is something that is already built like a blueprint and offers very little room to plug in your own code, or to continue our metaphor, furniture piece. The most popular frameworks used by artificial intelligence companies are TensorFlow, Microsoft CNTK, Theano, Caffe, Torch, and Amazon Machine Learning. They are robust open-source frameworks with easy programming options, Python-based, and support deep learning. Some are suitable for scientific and numerical operations, data mining, and analysis, while others have image processing capabilities. For instance, Airbnb uses Google’s TensorFlow for categorizing apartment listing photos as a way to ensure it represents the apartment space accurately.
Platforms
For an idea to become a project and be seamlessly deployed, artificial intelligence companies and their developers need platforms. Whether it is the Google cloud AI platform, IBM Watson Studio, Amazon AI services, Microsoft Azure Machine Learning Studio, INTEL Nervana, or SAP Leonardo Machine Learning, AI platforms ease the work of developers, data scientists, and engineers. Thanks to AI platforms, it is possible to detect fraudulent credit cards, extract personality characteristics from text, or build conversational interfaces. Given the variety of functions these platforms can simulate, we’ve handpicked the AI technology companies that demonstrate expertise in choosing which one works best for what type of project.
Languages
And finally, since tasks and algorithms play a major role in AI, the team needs to excel in their knowledge of Python. Because of its simple syntax, it is the most widely used language. As the oldest and most effective in processing symbolic information, LISP is also a must, along with C++, Prolog, or Java.
Workflow of the Top AI Companies
From in-person meeting and gathering requirements, product development, verification, and validation, to ensuring product success, the superiority of an AI company lies in its dedication to an end-to-end process. Below are some of the steps it should adhere to.
Evaluation & Assessment of Requirements
If an artificial intelligence company complies with industry standards, they will start gathering information about the client’s idea and how they can deploy it, from the moment they get in touch with them. And since AI is usually intended for solving complex problems, for artificial intelligence companies, the initial processes are usually the most essential.
Say, the client needs an AI-powered personal assistant to perform administrative tasks like scheduling, rescheduling, and canceling meetings. To make this happen, the company must understand the client’s problems and challenges and how these could be solved, gather a list of requirements so they know what processing capabilities the assistant should have, and of course, start working on a timeline of what’s to follow.
Solution Architecture
The next step for AI companies would be to explore data and prepare the technical specifications for the initial architecture. This would entail bridging the gap between what the client currently uses, and what their business needs. However, it also includes exploring raw data to detect patterns. For maximum efficiency, experts use popular data mining tools such as RapidMiner, Orange, IBM SPSS Modeler, Knime, and Oracle. The project requirements typically dictate the tools that will be used. Once data is gathered, AI software companies must anonymize sensitive data by conducting data labeling and clean-up.
Model Development
An AI-powered file is developed as a base model to test and verify whether the solution architecture works in practice. If the tests are satisfactory, the training cycle begins. An algorithm trains the model to recognize certain types of patterns and learn from the data. Needless to say, this phase, also known as the inference mode, is when an artificial intelligence company must demonstrate absolute efficiency and patience as the process involves trial and error.
Deployment & Monitoring
If the client and AI developers are happy with the results so far, the next step is to deploy the model or rather, integrate it into an existing production environment where it can receive input and return output. The output is a practical business decision or whether the AI-enabled personal assistant from the example above, would schedule an appointment or not. Monitoring is for validating the output and it is necessary for detecting data distribution or any anomalies that might disrupt the performance of the product.
How to Choose One of the Top AI Companies
Our detailed evaluation methodology was how we compiled the list of what we consider the top companies in the AI industry. We’ve also prepared some points to help you narrow down your search for the best AI fit for your project.
Practical Use of AI for Your Business
Thanks to AI, businesses have sentiment analysis, supplier risk assessment, automated communication processes, text recognition, and many other functionalities to boost their efficiency. This is why you need to choose your AI partner by what value you hope AI will add to your businesses.
If you need AI for big data processing and identifying patterns to gain new insights and make better business decisions, then you should hire one of the AI companies specializing in analytics. Similar to analytics, there is the AI functional which also scans large data and gives recommendations but unlike analytics, it acts on it. For example, if you are in the manufacturing sector, every time the system notes a decrease in stock, it would automatically replenish it without bothering you.
Businesses in need of automating their communication processes with an intelligent chatbot or interactive mobile app should focus on finding an AI company that works with interactive AI. For projects related to speech-to-text conversion, machine translation, content generation, etc., consider AI development companies specializing in text AI. And finally, if you hope to propel your business forward by relying on visual AI to assist you in identifying, classifying, and converting images and videos into data, then look for someone with skills in this field.
Client Testimonials & Feedback
Portfolios usually contain the crème de la crème which is why you should also consider client feedback and testimonials. They can tell you a great deal more about the company and its team than any portfolio or website. So, once you’ve shortlisted the AI firms with experience in the type of AI you need, we suggest you take a deep dive into client testimonials, reviews, and feedback. But go beyond what the website has to offer and check out popular review sites so you’d gain a clear understanding of what kind of partner you are potentially getting involved with. Last but not least, pay particular attention to the frequency and means of communication used, project delivery, and client satisfaction.
Location & Offices
Many of the artificial intelligence software companies on our list have successfully implemented projects by working remotely. But remote support might not cut it for you. For instance, if you are in the manufacturing sector, the nature of the project might demand that the team of AI specialists do the data gathering on-site. And since this process could take a while, a company’s location can make a huge difference and impact both budget and timeline. Our advice here would be to thoroughly discuss all the location-related details before you seal the deal.
AI Team
An in-person meeting with company representatives is not enough because the hard work will be done by the team of AI developers. Before you start negotiating, ask to meet with the team designated for your project, discuss their working style, timeline management, reporting and communication mechanisms, etc. If for your project you need a team in charge of the entire architecture of the AI project, including data collection and preprocessing, you must be able to discuss the specifics with them and get a sense of how they roll. Small-scale projects meanwhile are unlikely to demand senior-level developers, so make sure you are not fooled by any of the AI companies you meet with, that you need more than you actually do.
Define Your Budget
With businesses worldwide expected to invest more than $100 billion in developing AI-powered solutions, the truth is, that these services do not come cheap. The price of a customized AI solution might cost anywhere between $6,000 and $300,000. AI consultants meanwhile charge $200-$350 per hour. In any case, the cost of an AI project would depend on the diversity of skills required to complete it. So, before you seal the deal with any of the AI companies you are considering, we suggest you first decide how much you are willing to spend. And finally, make sure the end product comes with a warranty and ongoing maintenance and support included in the price.
