Reshape your business horizon with artificial intelligence solutions

Check how AI can help you solve key business problems

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Accelerate business transformation with AI technology solutions

Utilize the potential of artificial intelligence solutions to solve business problems, automate tasks, and serve your customers better. Capable of adapting and evolving alongside your organization, Ai-based solutions cater seamlessly to both small businesses and large enterprises, navigating the dynamic landscape of the digital era.

Drive and deliver innovation fostered by artificial intelligence

Strengthening your business landscape with extensive benefits of AI-based solutions

  • Create your AI strategy. Gain actionable insights from data scientists, product practitioners, and business leaders to make informed decisions about adoption of AI-powered solutions.
  • Find a suitable AI solution. Conduct an in-depth comparison of potential AI solutions and craft a robust data governance framework, pinpointing potential risks, and setting up a monitoring strategy.
  • Assess data-based feasibility. Assess and address potential risks associated with data and technology during actual development.
  • Scale a prototype to production. Improve an existing ML model in terms of speed, prediction quality, cost-effectiveness, or any other aspect so it can be deployed into production.
Let’s talk about your project!

Netguru - Artificial Intelligence solutions provider

Why to choose us as your AI partner?.

Businesses across size and industries are rapidly investing into AI solutions development into their workflows. Making the shift to AI isn't just an option — it's an urgency. Start your AI journey with Netguru today.

  • Practical AI Focus: We specialize in translating tech trends into practical and commercially viable AI applications.

  • Diverse AI Team: Our team includes a diverse group of experts, including researchers, product managers, and data engineers, ensuring comprehensive solutions.

  • Industry Experience: With extensive experience in Fintech, Retail, Proptech, and Healthtech, we understand the unique challenges and opportunities in these sectors.

  • One-Stop Partner: We provide a comprehensive range of services, including AI based solutions, design, mobile, web, and more, ensuring that all your technology needs are met efficiently under one roof.

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Step into the future of innovation with our bespoke AI solutions. From preliminary exploration to full-scale implementation, we're committed to your successful AI transformation journey.

  • AI Primer Exploration Workshop. Free 6-hr AI exploration workshop: Analyze your business, explore AI applications, get personalized insights & adoption roadmap.
  • AI Solution Design Sprint. Intensive 2-day workshop that will help you translate concepts into implementable AI solutions with integration plans, data governance, risk mitigation
  • AI Proof-of-Concept. Our service ensures structured AI validation, managing risks, reducing financial burden, and accelerating ML projects with proof-of-concept and detailed recommendations.
  • AI MVP Implementation. Our implementation practice for machine learning models ensures a smooth transition from prototype to to a fully developed solution ready for production.
Let’s talk about your project!

Bringing the Salon Home: COSMO Group's NEONAIL Virtual Manicure App

Deploying augmented reality and machine learning for an authentic salon experience.

Key challenges: Bringing the in-store nail product try-on experience to online shoppers

AI solution: COSMO Group collaborated with Netguru to create NEONAIL, a virtual try-on app for manicures. Utilizing advanced AI and augmented reality technologies, the app provides real-time, lifelike 3D effects of colored nails, enabling customers to test and purchase products with confidence.

Outcomes: This resulted in a substantial increase in online sales, an enhanced user experience, and a revolutionary tool available on various platforms that pushes the boundaries of the nail styling and care industry.

Read the case study
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Your company’s AI journey

Working with AI is a step-by-step process that includes domain understanding, business case definition, feasibility checks, implementation, and ongoing model optimization. Our process caters to clients at different stages in their AI journey, whether they are newcomers or tackling intricate challenges. It's important to comprehend their unique circumstances to effectively present our offering. Keep in mind that these circumstances may differ among various departments or units within the client organization.

  1. Discovery & design. Outline your business objectives and identify potential AI solutions through brainstorming and analysis.
  2. Build data foundations. Establish the necessary data infrastructure and protocols required for your AI solution with data engineerings.
  3. Proof of concept building. Develop a proof of concept to test and validate the feasibility of your AI solution.
  4. Deploy and optimize. Implement the AI solution into your operational workflow and optimize for peak performance.
  5. Monitor & improve. Continually monitor the performance of your AI solution and make necessary improvements to enhance its effectiveness.

Impact across a broad range of industries

As an artificial intelligence solutions provider, our profound industry-specific understanding and expertise have led to the delivery of revolutionary AI solutions.
  • Retail. We’ve powered retailers to predict trends, personalize customer experiences, and manage inventory with unparalleled precision.
  • Finance. We’ve deployed tools for enhanced risk management, fraud detection, and customer service.
  • PropTech. We’ve built solutions that streamline property management, optimize space utilization, and improve energy efficiency.
  • Healthcare. We’ve enabled providers to predict patient needs, improve treatment plans, and optimize administrative tasks.

Reimagining online shopping with a virtual dressing room

AI-enhanced shopping experience reduce returns and boosts conversion rates.

Key challenges: The client, a German quick-commerce retailer, wanted to address the limitations of their ecommerce platform, particularly the difficulty in determining the right fit and size, uncertainty in visualizing the final look, and high return rates due to limited product knowledge.

AI solutions: We developed new features for a personalized shopping experience, including clothes selection based on specific body types, matching items and offering recommendations, and allowing users to upload personal photos to visualize the outfits.

Outcomes: The client experienced a reduction in returns, increased conversion rates, unlocked upselling opportunities, and expanded brand reach.

Read the case study
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AI development: All your questions answered

Not sure how AI solutions can deliver business value to your organization? Check out some of the most common questions asked by our clients.

How do you estimate an AI project?

Providing a rough cost estimate for an AI-infused enterprise software development project is often challenging.

Factors influencing the estimation include the challenges your company seeks to address, the most appropriate AI tools and solutions, and your expectations for accuracy, among others.

For a detailed estimate, it's best to engage with AI solutions development company, who can guide you through the suitable AI options and provide a cost projection for AI services based on a thorough analysis of your specific needs.

We recommend initiating with a proof of concept or a small project, as machine learning is a highly iterative process. This approach often proves more beneficial than launching a long-term project filled with uncertainties.

When should you use AI?

Artificial intelligence solutions, when deployed appropriately, can significantly boost customer base, sales, and cost-efficiency. However, improper usage could potentially result in customer churn, financial losses, and reputational damage.

In AI, unlike traditional software development, the crux lies not in the algorithm but in the data the model learns from. Generally, when there's more data than a human can process, machine learning becomes a viable option. AI solutions find broad applications across business sectors and can aid in problem-solving in numerous ways.

  • Classification leverages machine learning to categorize distinct items into predefined groups based on certain characteristics. For instance, it can be used to detect fraudulent credit card transactions or identify spam emails. Its power lies in its ability to differentiate and classify objects — such as customers or products — into two or more specific categories.
  • Clustering is a machine learning technique that uncovers hidden patterns within seemingly chaotic data. It draws connections between data points, grouping similar ones into clusters without the need for predefined classifications. Its ability to identify similarities within vast datasets makes it a powerful tool for discovering underlying trends and groupings.
  • Regression operates like a forecast for the future, using machine learning to predict the most likely numeric outcome of a specific factor based on dataset input. This method could be utilized to anticipate fluctuations in stock or real estate prices, predict customer behavior, or determine the degradation rate of a piece of equipment in your company. Regression stands out for its ability to project future trends and outcomes based on existing data.
  • Generative AI represents the cutting-edge of AI technology, with models such as ChatGPT and StableDiffusion capable of generating realistic text or images. When used judiciously, these models can augment manual tasks, like providing high-quality automated customer service by handing off only the more complex cases to human agents. However, it's essential to remember that while these AI models are powerful, they aren't yet capable of replacing humans for tasks that necessitate multi-step advanced problem-solving.

There are, of course, many more applications of AI. As the AI field continues to evolve at a rapid pace, new methodologies emerge regularly, and staying updated is crucial.

What data can you use for building AI solutions, and how do you do it?

For developers seeking to build AI solutions, training algorithms on a wide-ranging set of data is crucial.

This data may take various forms, such as images, text, or specialized information like financial transactions or customer engagement patterns. Acquiring the right data is vital.

It can be purchased prepackaged, sourced from public crowdsourcing initiatives like Amazon's Mechanical Turk, or collected and labeled by private data science specialists when handling sensitive data.

Training datasets should encompass ample positive and negative examples for effective learning. To illustrate, if an algorithm is to recognize cranes in images, it should be exposed to pictures both with and without cranes.

Developers and data scientists may experiment with diverse algorithms before selecting the best fit. Additionally, a test dataset is provided to evaluate, analyze, and refine the model developed from the training data.

When are you better off avoiding AI solutions?

AI solutions, while potent, are not always the optimal choice. In some situations, traditional software methods are preferred, such as when:

  • You don't have enough data: AI solutions are designed to work with huge amounts of data. If the training dataset is too small, then the system's decisions will likely be biased. However, what amounts to a large enough data is highly dependent on the industry or subject matter. For example, 100,000 payment transactions might be considered a small dataset, but 1,000 MRI scans are a huge dataset in the medical field.
  • Data is too noisy: "Noise" in AI is the irrelevant information in a dataset. If there’s too much of it, the computer might memorize the noise. Although there are specialized techniques to address these kinds of problems, it’s not easy to decide beforehand if there’s too much noise.
  • You don't have much time (or money): The implementation of AI solutions requires considerable time and resources. The process begins with data scientists assembling and refining a dataset, followed by the computer's learning period. Then, AI teams perform tests and tweak the algorithm, a step that often demands repetition to achieve optimal results. The cycle of learning, testing, and adjusting is iterative and can extend over an extended period, escalating the overall costs as AI specialists devote more time to the project. However, the silver lining lies in the process's flexible nature, which can be halted at any point if the constraints become overwhelming.
  • Simpler solutions available: If a problem can be readily solved using regular programming or pre-existing tools, there's no need to force an AI solution.

In essence, while AI is potent at finding patterns within large, complex datasets, it is not always the go-to solution, especially when constrained by time, data volume, or data quality. If you have any doubts, reach out to us, and one of our AI experts will get in touch with you.

How much does an AI solution cost?

The cost of implementing an AI solution can vary significantly depending on several factors, making it important for businesses to consider their specific needs and objectives. AI solutions offer a competitive advantage in today's rapidly evolving business landscape by addressing various business challenges through their scalable artificial intelligence capabilities.

The cost of an AI solution is influenced by the complexity of the task it needs to perform, the sophistication of the AI system required, and the scale of implementation within an organization. Enterprise AI solutions, designed to cater to large businesses, often involve more significant investments due to their robust features and scalability.

To determine the cost of implementing an AI solution for your business, it's crucial to engage with AI service providers or consultants who can assess your unique requirements. They will consider factors such as data volume and quality, the complexity of AI algorithms needed, and the integration with existing systems.

Furthermore, the ongoing costs of maintaining and improving AI solutions should be factored into your budget. Regular updates, data management, and monitoring are essential for keeping your AI system effective and competitive.

In summary, the cost of an AI solution is not fixed and varies based on specific business needs, enterprise AI capabilities, and scalability requirements. Investing in AI can provide a significant competitive advantage by addressing business challenges and leveraging the power of AI systems to enhance various aspects of your operations. To get an accurate cost estimate, it's advisable to consult with AI experts who can tailor a solution to your organization's unique needs.

 

Our partners on working with Netguru

  • My experience working with Netguru has been excellent. Outstanding software teams are resilient, and our developers at Netguru have certainly proven to be that. Our Netguru friends have become as close to team members as possible, and I am grateful for the care and excellence they have provided.
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    Gerardo Bonilla

    Product Manager at Moonfare
  • Netguru has been the best agency we've worked with so far. Your team understands Kelle and is able to design new skills, features, and interactions within our model, with a great focus on speed to market.
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    Adi Pavlovic

    Director of Innovation at KW
  • Working with Netguru has been a fantastic experience. We received a lot of support in terms of thinking about how we track metrics, how we design this properly, and how we build the architecture. We are extremely grateful for making our platform what it is today.
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    Manon Roux

    Founder at Countr

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