Generative AI Development

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Unlock Limitless Possibilities with Our Cutting-Edge Generative AI Solutions

We specialize in a variety of AI technologies, such as deep learning, machine learning, natural language processing, reinforcement learning and computer vision. Our team produces robust Generative AI models and creates solutions with integration ChatGPT and other tools.

Portfolio nextrope

  • Alior Bank
  • Kinguin
  • Codez
  • Wear
  • Dript
  • Soil
  • Chia
  • Goldex

Alior Bank: a durable medium solution developed with Ethereum public Blockchain.

Alior Bank SA is a universal bank and the 10th largest financial group in Poland with more than 6 000 employees and over 108 mln PLN net income for Q1 2021.

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Kinguin: One of the World’s Leading Gaming Marketplace

Kinguin is a leading worldwide video game marketplace with the purpose of improving players' experiences. With over 13 million registered users, the marketplace includes over 90,000 digital items listed

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Codez: Optimizing Blockchain development with the power of Visualization and AI

Codez is a comprehensive tool that allows whole web3 organizations to manage, visualize, and monitor smart contracts faster and more conveniently.

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WeAr: Where Fashion Meets Blockchain - Our NFT Initiative x Tommy Hilfiger

WeAr is the leading global B2B magazine for fashion & footwear published in 8 language versions. It is distributed to over 50 countries on all 5 continents. As WeAr is not only a source of information but combines art with fashion and couture.

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Dript: The Future of Secure Luxury Shopping

Dive into the Next-Gen of Luxury Shopping with Dript's Unique Verification Process

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SOIL: Secure returns on stablecoins backed by Real World Assets

Soil is a blockchain-based lending protocol that bridges the gap between traditional finance and the crypto world, reshaping corporate debt and fixed-income investments.

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Chia: Staking solution on the ‘green’ Blockchain – Chialeaf

EcoWay is a platform that allows users to access Chia farming profits without building their own mining infrastructure.

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GOLDeX: The Easiest Way to Own Gold

GOLDeX is Gold Backed Digital Currency redeemable by physical gold. You can Use it to Buy, Sell and Send Gold instantly.

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AI models we work with

Bring your ideas to life and progress

  1. GPT-3

    A powerful language model known for its impressive natural language understanding and generation capabilities.

  2. GPT-3.5

    An intermediate version between GPT-3 and GPT-4, offering enhanced performance and capabilities.

  3. GPT-4

    Our latest and most advanced language model, providing unparalleled language understanding, generation, and context-awareness.

  4. DALL-E

    A groundbreaking AI model that generates high-quality images from textual descriptions, revolutionizing the field of creative design.

  5. Whisper

    An advanced automatic speech recognition (ASR) system that accurately converts spoken language into written text.

  6. YOLO (You Only Look Once)

    A real-time object detection system that can detect and classify objects in images and videos with high accuracy and speed.

  7. BERT (Bidirectional Encoder Representations from Transformers)

    A powerful language model developed by Google that has achieved state-of-the-art results in various natural language processing tasks, including question answering and sentiment analysis.

  8. DQN (Deep Q-Network)

    A reinforcement learning model that uses deep neural networks to learn optimal policies for decision-making in complex environments.

  9. Embeddings

    Techniques for representing words, phrases, and other data in a continuous vector space, enabling efficient similarity and relationship analysis.

  10. Stable Diffusion

    A state-of-the-art generative model that creates high-quality images and videos through a diffusion process.

  11. GANs (Generative Adversarial Networks)

    A class of deep learning models that can generate realistic images, videos, and other data by learning from a training set of examples.

  12. Midjourney

    A powerful AI model for predicting and optimizing user engagement and retention in digital products.

  13. Bard

    An AI-driven storytelling model that generates coherent and engaging narratives based on user inputs.

  14. Moderation

    AI models designed to automatically detect and filter inappropriate content, ensuring a safe and respectful online environment.

  15. LLaMA

    A multilingual AI model that enables seamless translation and understanding across a wide range of languages.

AI models for a wide range of sectors

Generative AI solutions can be applied across a wide range of industries, including but not limited to

What is the Generative AI development process?

  • 1

    Identification of your business needs

    To identify your business needs, start with defining the goals and objectives of your generative AI project. Ask yourself what problem you're trying to solve, what kind of output you're looking for, and who your target audience is. We can also help you with this process.

  • 2

    Discovering data sets

    To maximize the value of data, it is essential to analyze both current and future data sources available. This task involves identifying different sources of structured and unstructured data that can be gathered. Our team of specialists will then evaluate and prioritize these sources to quantify their significance.

  • 3

    Choosing appropriate tools and frameworks

    We are offering a wide set of tools and frameworks which next we will adjust directly to your needs and project.

  • 4

    Fine-tuning or training a generative AI model

    Fine-tuning and training are both effective methods for improving the performance of generative AI models. Fine-tuning involves adjusting an existing model to better suit a specific task, while training entails starting from scratch and building a model for a specific task.

  • 5


    After training the AI model, testing it is necessary to ensure that it generates the desired output. Subsequently, it is crucial to evaluate the quality of the generated output and make adjustments to the model as needed.

  • 6


    To deploy a generative AI model, one must train it with a dataset, optimize its performance, integrate it into an application, and consider ethical and legal obligations.

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