Our Evolutionary AI Solutions: Evolutionary Computation, Deep Learning, Neuroevolution, Surrogate Optimization, Meta-learning, Trustworthy AI

Evolutionary Artificial Intelligence

Artificial Intelligence (AI) is a new technology that aims to mimic human reasoning in AI systems. We need to change our value propositions to focus on process optimization for clients. To do so, we're investing more in machine learning, AI, and deep learning capabilities, and I believe we're far ahead of the curve in terms of integrating them into our operations. Scaling the business models is the ultimate step. In industrial ecosystems that embrace the logic of digital servitization, the spread of artificial intelligence (AI) technology holds the promise of enabling fundamental transformations in products, services, innovation processes, business models, and the very character of corporate operations. The use of digital technologies such as sensors, connectivity, and analytics to generate new value-creating and revenue-generating opportunities is known as digitalization. It is a procedure that has a significant impact on the manufacturing industry. AI is the engine that propels digitalization, and businesses that can successfully integrate AI skills into their business models will thrive in the future. Every company in today's world is working on AI-driven change in some way.

Get in Touch

    Features of Evolutionary Artificial Intelligence

    Iterative tasks can be automated

    Reducing the amount of time that existing complex processes are unavailable

    Better access to deep insight data speeds up decision-making

    Simplifying multi-step procedures so that they can be run by a single person

    Advantages of Evolutionary AI

    Risk Takers

    One of the most significant advantages of artificial intelligence is this. By constructing an AI Robot that can do the risky tasks for us, we can transcend many of humanity’s risky limits.


    Round the Clock Availability
    Machines, obviously, do not grow tired. Machines, unlike humans, can work without stopping and don’t get bored performing the same thing again and over.


    Human Error Reduction
    Humans make mistakes from time to time, the term "human error" was coined. Computers, on the other hand, do not make these errors if they are correctly programmed. Computers, on the other hand, do not make these errors if they are correctly programmed.

    Assisting in Repetitive Tasks
    We will be doing a lot of repetitive labour in our day-to-day work, such as writing thank-you emails, double-checking documents for flaws, and so on. We can use artificial intelligence to efficiently automate these monotonous chores and even remove “boring” duties from humans' schedules, allowing them to be more creative.


    Evolutionary Computation

    In contrast to deep learning, which focuses on modeling known behaviors, Evolutionary Computation creates new solutions, by reassembling, transforming, and transforming the population over and over again. Our latest research includes finding design strategies in architecture, business, and sports, encouraging AI to find creative and novel solutions, using multiple purposes, and creating AI that can explain its decisions in terms of rules.

    Deep Learning

    Deep learning is another foundation for AI research with the Evolutionary AI team. The main focus of our recent research is to improve deep learning of operational properties and cost calculations, using multiple data sets by learning multiple functions and finding useful neural network building blocks.


    Neuroevolution is a powerful way of combining evolution with deep learning: evolution is used to automatically develop deeper learning structures, namely topology, components, parameters, and weight limits of sensory networks. To put it another way, AI designs AI. Our latest work focuses on neural architecture research, improving the state of the art in several machine learning benchmarks.

    Surrogate Optimization

    The idea is to start building a domain model by e.g. In-depth Learning, then use the model as a substitute to improve interaction using Evolutionary Computation. We have used this development method e.g. agricultural growth recipes, animal behavior agents, and non-pharmacological interventions in the COVID-19 epidemic. In this way, it is possible to get smart and effective decision-making strategies safely and effectively.


    Modern models of deep learning have many features that need to be adjusted by hand, a tedious process that requires specialized technology. Metalearning is a family of strategies that allow for structures, loss functions, hyperparameters, opening functions, and other automated functions, leading to more efficient models.

    Trustworthy AI

    To trust the predictions and instructions of the AI ​​system, it needs to show how certain it is, it needs to allow testing of other solutions, and in some cases, it needs to explain its behavior with clear rules. The LEAF platform incorporates technologies developed specifically for these three principles.

    Why Mobiloitte for Evolutionary AI Application Development?

    Scalability and Maximum Security
    For protection against new malware and threats, state-of-the-art data encryption is combined with high-security plugins.

    Result-Oriented Approaches
    Our AI-powered tools and software are designed to give actionable results in a short amount of time.

    Experts with Years of Experience
    We provide unrivalled AI application development services to global clients, backed by a robust team of seasoned AI developers.