AI Consulting

AI Consulting Company

Guiding Your AI Future: Elevate Possibilities with Expert AI Consulting Services.

Business benefits

Artificial Intelligence – consulting in the field of AI solutions

AI Consulting Services
AI Strategy Consulting
Our team

What AI consulting services can you expect?

Dot Labs offers unique AI consulting services that will help you realize how many opportunities come from implementing AI solutions into your business.

Artificial Intelligence influences most industries, among the most popular are: retail, eCommerce, manufacturing, finance, healthcare, marketing, and gaming sector.

Dot Labs may offer to you a variety of AI services, starting from an AI strategy roadmap to building a scalable AI infrastructure and production-grade AI solution deployment.

  • AI Strategy Roadmap – validate feasibility of using AI in your company, analysis of available data and data monetization potential
    AI proof-of-concept projects – test assumptions and hypotheses. We are delivering fast and reliable MVP solutions in 4-6 weeks.
  • Production grade AI implementation – implementing algorithms and models to support your business’s production systems and deliver insights in real-time
  • Support – we help our customers in model validation, quality control and system stability
  • Post-implementation warranty – we guarantee that our AI algorithms will bring you value and high accuracy

AI strategy is a comprehensive plan developed by organizations to leverage artificial intelligence (AI) technologies effectively for their goals and objectives.

An AI strategy outlines how AI will be integrated into various aspects of an entity’s operations, innovation, decision-making processes, and overall business or societal objectives.

Aligning an AI strategy with a broader business strategy is essential to ensure that the integration of artificial intelligence supports and enhances the organization’s overall objectives.

Developing an AI strategy involves understanding your business goals, whether they involve increasing revenue, improving customer satisfaction, optimizing operations, or expanding into new markets, and determining how AI can directly contribute to achieving them.

Not all AI applications will be equally beneficial to your business. Prioritize AI use cases based on their potential to generate value and align with your business goals.

Our team develops customized AI solutions based on recent technologies.

We implement solutions based on high-tech solutions such as Computer Vision, Natural Language Processing, Predictive analytics, Image Recognition, Recommendation Engines, Smart Search Engines, and many more.

Dot Labs uses advanced AI algorithms, such as Random Forest, XGboost, Support Vector Machines (SVM). For tasks including Image or Text processing – Deep Learning algorithms are now very successful. Some of them are Convolution Neural Networks and Recurential Neural Networks.

Thanks to automatically choosing the most important features, AI Solutions can help solve the most difficult challenges of your business.

The biggest advantages of AI are self-learning capabilities and scalability.

It gives SaaS applications the ability to use algorithms for thousands of customers.

Due to the fact that AI learns the history of all users, it gives amazing opportunities for the Marketplace. One of the examples is using a recommendation system based on the preferences of each individual person.

More than 9 in 10 leading businesses have ongoing investments in AI.

At Dot Labs, our AI consultants stay in touch on a daily basis with our clients.

This way you can be sure that your project is our top priority.

Our AI experts will help you to:

  • solve complex business challenges using analytic algorithms and AI
  • design, build and deploy predictive and prescriptive models using statistical modeling and optimization
  • use structured decision-making to complete projects
  • manage an entire AI project from business issue identification, data audit to model maintenance in production.

AI as a Service

Discovering client’s needs

First, we do our best to understand our customers and their needs. We analyze where there is room for improvements and discuss various high-tech solutions that would be the most effective.

Feasibility study

This is a stage in which we closely cooperate with our client’s team, get access to crucial data and exchange information on a daily basis.

We want to make sure that the project we are working on together is going to be an investment that will quickly pay off and will keep on bringing additional value in the future.

Building a prototype

At this stage, we already have reached an agreement and we now focus on making an idea come true. Our team prepares a complex plan, divides tasks and creates a timetable. Then, we build a prototype that resembles our main goal and analyze it with our client to agree on details.

Once everyone is satisfied with the prototype, we start working on the agreed solution.

Integration into the existing system and production deployment

Dot Labs team implements custom-made solutions into existing systems. Our team of experts runs multiple tests to make sure that everything works smoothly.

Our AI consultants are always available to answer any questions.

Final results / Transformation of your organization

Now, your company can take advantage of the most recent technological solutions and observe how advanced algorithms improve their business outcomes.

Why work with us

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We’ve helped a leading manufacturing company enhance management efficiency

All thanks to the implementation of an automated reporting and demand prediction system with predictive maintenance capabilities.

Dot Labs AI consultants have developed and created a system that helps managers and operation leaders to make the right decision on the costs and demand planning. Predictive maintenance solution is predicting when a particular production machine needs to be checked and potentially replaced.

Benefits include one integrated data platform and yearly savings of around 10m $ on right demand planning and inventory management. Continues production process and prevention from machine failures which are resulting in millions of dollars in costs.

We’ve helped one of the global retail & eCommerce companies to optimize advertising processes using AI, ML, and ad targeting

We increased the effectiveness of the operational activities using image recognition.

Using advanced AI technologies our consultants created algorithms that help to find the best time to spend, identify the right channels and slots, and automate bidding for ad space. Image recognition and computer vision technologies were used for planogram execution, signing detection, and inventory automation using shelf analysis.

Benefits include 60 hours of labor saved each month. 30% advertising cost decrease and improving conversion rate by 5 p.p (from 16% to 21%) that led to the sales increase in around hundred of thousand dollars.

We’ve helped a technology company specializing in intelligent shipping and logistics solutions

We implemented solutions based on the latest advances in machine learning services and artificial intelligence.

We implemented AI algorithms to provide multivariate analysis of the most valuable logistic indicators, we created a notification system for enhanced user experience and improve the interactions between departments, which helped in the daily work of employees and successfully optimized the business decision-making chain.

It enabled the company to bring shipping and logistics into the digital age and keep logistic cost optimization

We’ve helped a financial service company to optimize its pricing policy using the classification model

The model takes into consideration customers’ behavior and adjusts pricing depending on individual financial profiles.

We created an AI-driven recommendation engine that analyzes a huge amount of transactional and customer behavior data to increase sales, overall business performance, and client engagement as well as satisfaction.

This solution was used to support up-sell and cross-sell campaigns.

Finance & Insurance

Tools and frameworks for AI solutions

Programming languages




Python – Python is considered the most popular programming language in the Data Science area mostly because of its quite straightforward and easy-to-read syntax. Still, the benefits of using it in building Machine Learning solutions are numerous. This language has a large and active community that develops and maintains a wide range of libraries and frameworks specifically for Machine Learning and Artificial Intelligence, which provide pre-built algorithms and tools for building and training models. Python is a versatile and flexible language; it can be used in scientific computing and web development, which makes it a great choice for building ML models, often requiring a mix of programming, data analysis, and visualization.


R – With built-in statistical functions, R was made specifically for machine learning applications. This language also has an extensive library of data visualization tools, which makes it easy to create charts, graphs, and other visualizations of data. Moreover, R has an interactive console that allows users to explore data and experiment with different analyses and models in real time, enabling Data Scientists to test different models and approaches. R - as well as Python - can be easily integrated with other tools and languages, such as Python, SQL, and Hadoop.

PySpark – PySpark – used to transform data. It enables you to run AI applications on billions of data on distributed clusters 100 times faster than the traditional python applications.

Hadoop – Hadoop – is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power, and the ability to handle virtually limitless concurrent tasks or jobs.


TensorFlow – TensorFlow is an open-source machine learning library developed by Google Brain Team, used to build and train machine learning models, including deep neural networks. It provides high-level APIs such as Keras that make it easy to build and train models without needing to write complex code, visualization tools, and pre-built models and datasets.


PyTorch – PyTorch is also an open-source machine learning library, yet it is was developed by Facebook's AI Research team. PyTorch allows Data Scientists to prototype and deploys machine learning models using Python. It is used in various applications such as computer vision, natural language processing, and reinforcement learning.

Key benefits

Artificial intelligence can improve your business in
many ways

Reducing human labor

Using AI leads to reducing human labor, especially in handling repetitive tasks.

Cost savings

A one-time investment in AI will be more cost-effective than hiring a full-time worker, as AI can automate labor-intensive processes without harm to quality.

Minimizing the risk

By providing the ability to analyze various unstructured data, AI can identify patterns related to past incidents and predict future risk factors.

Real-time decision making

Artificial Intelligence increases the efficiency of decision-making processes as it constantly evaluates data coming from multiple sources, providing stakeholders with precise and real-time insights.

All you need to know about AI consulting

What is artificial intelligence?

Artificial Intelligence (AI) is an area of computer science that focuses on the creation of intelligent machines which “think” and react like humans.

The main goal of AI technology is to imitate the behavior of an intelligent human being.

How does artificial intelligence work?

Computers need to learn how to respond to particular actions with the use of algorithms and historical data. Then, artificial intelligence creates a propensity model which starts making predictions.

44% of organizations have reported cost savings as a result of AI implementation.

How to prepare for AI implementation?

  1. Take the time to understand what artificial intelligence is.
  2. Analyze what problems your company is facing, which could be solved with the help of AI technology.
  3. Use AI consulting services to analyze your ideas and choose the best AI solution to solve your problems
  4. Prepare your company details

What business problems could we solve with AI?


The threat of cybercrime is becoming more and more dangerous every year as customers use digital transactions. It is an opportunity to steal their financial information as well as personal information. The more transactions are carried out on a daily basis, the more difficult it is for companies to ensure the security of every single transaction. AI solutions can help you solve this problem.

Customer service

Artificial Intelligence technology is widely used in customer support to offer customers the best service. Thanks to artificial intelligence, your company can be available to customers 24 hours a day, 7 days a week, without the need for human assistance. Customers have a better experience and your business saves valuable time.

Personalized experience

Personalized shopping is one of the most important aspects that increase customer loyalty. AI technology has found a solution to offer a personalized approach to customers who shop online. Product recommendation engines are one of the many AI-driven solutions that can help you retain customers and increase your revenue.

Data analysis

Today, companies collect more data about their customers than ever before. Unfortunately, it doesn’t make sense without data analysis. AI-based software can help your business process unstructured data and turn it into useful information about current trends, customer needs, etc.

How will artificial intelligence change the future?

Intelligent Process Automation

A new emerging trend that will be a game-changer in the future is IPA (Intelligent Process Automation). What is this?

IPA is a technology for automating business processes that enables the automation of individual tasks using artificial intelligence. This solution is a similar, more advanced version of RPA (Robotic Process Automation).

Essentially, IPA will enable us to use more machine learning algorithms to sort data and implement AI technology to recognize valuable information. So IPA is definitely a topic that we will hear more about in the future.

Which programming languages are used to build AI solutions?

There are numerous different programming languages that could be used to build AI solutions.

The most popular ones are Python, Java, Prolog, C++, Lisp.

What are various commercial applications of artificial intelligence?

AI-driven prediction and decision making

Given the economic situation that has changed so rapidly in the world as a result of the pandemic, entrepreneurs will be even more interested in AI-based forecasts and decision-making.

It is safe to expect that the main areas that will particularly benefit from AI-driven business forecasting are sales departments, medical diagnostic applications, inventory optimization, and demand and workforce planning.

With AI-driven tools, businesses can make effective decisions based on accurate, data-driven information. Entrepreneurs can better identify business opportunities and understand customer needs and behavioral patterns.

AI-powered chatbots

Chatbots are already a technologically advanced solution that most of us use or at least notice every day. Conversational AI (in other words, AI-based chatbots) will take the next step in the nearest future.

What are the main advantages of AI chatbots? In short:

  • personalized customer experience,
  • better range,
  • increased responsiveness,
  • significant improvement in the automation of customer service.

Conversational AI uses machine learning and NLP (Natural Language Processing) to:

  • Understand what we (humans) are saying.
  • Give us the support we need to communicate on a human level that feels almost natural.

  • How to integrate artificial intelligence solutions with internal systems?

    If you don’t have your own team of AI experts, leave that to the specialists. AI consultants will integrate AI solutions with your internal systems and make sure everything works perfectly.

    Which data is used by artificial intelligence and what databases I can connect?

    AI technology uses both structured and unstructured data. Artificial Intelligence database is a combination of data warehousing, advanced analytics, and visualizations in an in-memory database.

    AI databases have incredible abilities, they can ingest, explore, analyze, and visualize fast-moving, complex data at the same time within milliseconds. Connecting particular databases depends on particular situations – for more information contact an AI consultant.

    What does an AI consultant do?

    The role of an AI consultant is complex. AI consulting includes many tasks faced by data scientists and more. AI consultants need to help in creating an overall system based on different requirements necessary for successful implementation.

    Moreover, they are responsible for managing AI-driven projects as well as are considered experts by DevOps teams who support them in capacity building making sure that internal resources are supporting code and artificial intelligence infrastructure.

    What are the 7 stages of artificial intelligence?

    Let’s take a look at different forms of AI systems. We can divide them into seven stages.

    Stage 1: Reactive machines

    This is the oldest form of artificial intelligence systems. It has very limited capabilities – one of the reasons for that is their lack of memory-based functionality. It means that they don’t have the ability to “learn” from their actions.

    Stage 2: Limited memory machines

    This AI system has the functionality of a reactive machine and additionally is able to learn from historical data. This way, it can make accurate decisions. Most existing AI applications known today are under this category.

    Stage 3: Theory of mind

    Theory of mind AI is a work in progress. Researchers are working on this next level of AI systems that will be able to truly understand human needs. How? Thanks to analyzing human needs, emotions, beliefs, and thought processes.

    Stage 4: Self-aware AI

    It is a stage of AI development that for now is only hypothetical. The main concept behind it is artificial intelligence that has evolved to be so similar to the human brain that it has developed self-awareness.

    Stage 5: Artificial narrow intelligence

    This type of AI represents all of the existing AI. Artificial narrow intelligence can only perform a specific task autonomously using human-like capabilities. These machines can do only what they are programmed to do.

    Stage 6: Artificial general intelligence

    This stage presents an ability of an AI to learn, perceive, understand, and function exactly like a human being. Once we reach this stage, we will be able to significantly cut down the time needed to train models.

    Stage 7: Artificial superintelligence

    That would be the peak of AI research. Artificial superintelligence would become the most capable form of intelligence on earth. It would not only replicate the intelligence of humans but it would be better at everything because of overwhelmingly greater memory, faster data processing and analysis, and decision-making capabilities.

    But so far, we have nothing to worry about. Artificial superintelligence is only an idea at this point.

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