Generative AI Development for brave pioneers

Use the potential of Generative AI development to boost your business's productivity, performance and reduce operational costs. Also, design a pioneering AI strategy, develop your own suitable to your company’s needs, make it secure, safe, and implement it to achieve competitive advantage.

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Large Language Models

Large Language Models (LLMs)

Imagine you can save hours on extract and expand information from different sources with new way of semantic search approach, creating documentation. At the same time, develop your company’s brain that knows your industry’s specification and is trained on your data, or simply implement existing solutions to your systems.

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LangChain is a new Python

LangChain

Let's make LLMs simple! LangChain is a new Python framework designed to simplify working with Large Language Models.

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NLP development company

Natural Language Processing

Natural Language Processing (NLP) is a fascinating intersection of artificial intelligence and linguistics that enables machines to understand, interpret, and generate human language. It's the driving force behind voice assistants, chatbots, and many text analysis tools. Through NLP, computers can interact with us in a more human-like manner, making technology more accessible and intuitive.

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Text-to-image generation

Image Generation (Text-to-image)

Imagine bringing your product catalog to life with vivid, AI-generated images, or transforming your social media presence with bespoke visual content, or replace packshots with just few clicks using AI. To sum up, all these and more could be done with Image Generation AI, using Stable Diffusion.

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Our Generative AI development services

Let’s dive into it. In our services, you will find integrating AI application discovery, Proof of Concept, Prompt Engineering, and AI model training.

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Explore our E-book!

AI application discovery

We dive deep into your business operations, identify areas where Generative AI can add value, and outline a tailored adoption strategy. Whether it's automating repetitive tasks, generating unique content, or predicting market trends, as a result we'll find the right AI solutions that drive growth and innovation.

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Proof of Concept

We assist in translating your unique AI opportunities into a tangible and functional prototype. We test the viability of AI applications in your specific business context, mitigating risks and ensuring seamless integration. By building a Proof of Concept, we'll demonstrate the real-world impact of AI in your operations, providing a clear path for full-scale implementation. Let's bring your AI vision to life, proving its potential before you make a significant investment.

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Prompt design and engineering

We tailor AI prompts to your business needs compatible with your custom AI solution. By fine-tuning your AI's communication, we help you leverage AI technology for better business performance and accuracy. Don't just use AI; speak its language.

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AI model training

Create your company’s Virtual Brain by designing your own unique main future asset. We train your AI model with your company’s data and specific to your industry, to understand the business context, industry, and country’s specification better. Benefit from our expertise to make your AI work harder for you.

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From Zero to AI Hero. An ultimate guide to Generative AI

From zero to al hero

Generative AI in your startup & business

We’ve seen many entrepreneurs with amazing ideas struggle when it comes to implementing Generative AI in their ventures. With AI evolving rapidly, it’s essential for startups to understand its potential. All, for the purpose to stay competitive and innovative.

That’s where this ebook comes in. We’ve created this guide to help you make the most of generative AI in your startup and business. To sum up – our goal is to provide you with practical advice, real-life examples, and a step-by-step approach.

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Large Language Models

Discover practical applications and use cases of Large Language Models

Semantic search is all about making search results better. It does this by trying to understand what the person searching is really looking for. It chec the meaning of the words they use. This way, it doesn’t just look at the words themselves, but also a that specific context. This approach can be used either on the internet or within specific systems to provide more accurate results.

Semantic translation is like translating the meaning, not just the words. It looks at the context and the language details of the original text. It uses that to create a translation in the target language that conveys the same overall sense or idea.

Understanding and connecting intricate scientific data from unstructured text can be tough.  Especially for those who aren’t familiar with natural language processing. But, it’s crucial for accurately retrieving valuable records of intricate scientific knowledge. This method offers an easy, effective way to transform vast amounts of unstructured text into structured knowledge databases.

Document Automation is about using AI models, like deep learning, to automatically comprehend documents. Exactly the way humans do but in various languages. It can then suggest actions based on what it understands. This way, we can use language-learning models to simplify.  We  speed up tasks that involve a lot of documents, saving time and effort.

A business might employ a Large Language Model (LLM) to automate its customer support.  It is done by training it on the company’s data. This AI solution can handle customer queries in real-time. It may understand the context of the problem, and provide accurate responses based on past data. This not only speeds up response time but also reduces the workload on human support agents. Over time, the LLM learns and improves its answers, leading to a more efficient and cost-effective customer support service.

LLMs can be used to personalize messages or replying for marketing campaigns. It can generate interview questions, engage customers, develop interactive content materials or recommendation. They can help craft personalized messages and responses based on the user’s queries, interests or other data provided.

Image Generation (Text2Image)

Discover practical applications and use cases of Image Generation (Text-to-image)

Businesses involved in product design and manufacturing could use Text-to-3D AI to create detailed 3D prototypes from textual descriptions. This could streamline the design process, reduce costs associated with physical prototyping, and increase speed to market. A product manager could input “a compact, ergonomic wireless mouse with two buttons and a scroll wheel,”. As a consequence, AI would generate the 3D model.

A business in the e-commerce sector could use Image Generation technology like Stable Diffusion to ideate or customize product visuals. By training the model on existing product images and customer preferences. it can generate new, customized visuals of products. Even before they are physically produced. This can help businesses visualize different variants of a product, test market reactions, or offer personalized products to customers. As a result, it enhances the overall shopping experience and potentially boosts sales.

With the power of AI and technologies like Stable Diffusion, businesses can automate the creation of  graphic designs. AI can be trained to generate graphics that align with a company’s brand aesthetics and message. This provides businesses with a rapid method to produce a variety of design options. Without the need for extensive design resources. Plus, AI-generated graphics can offer a unique, cutting-edge look that sets a business apart in a competitive market.

Business can leverage Stable Diffusion technology to automatically generate eye-catching and customized graphic designs. By training the AI model on various branding styles, color palettes, and design elements, it can produce a range of promotional materials like banners, flyers, or social media posts. This not only accelerates the design process but also ensures brand consistency across all marketing channels. The ability to generate multiple design options can help businesses in A/B testing to identify which visuals perform best, ultimately improving the effectiveness of their marketing campaigns.

Text-to-3D AI could revolutionize interactive learning in education. Students could generate 3D models based on textbook descriptions, allowing them to better visualize and understand complex concepts. For example, a biology student could generate a 3D model of a cell based on a textual description. Thereby improving comprehension and retention.

Generative AI Development Project Cycle

An AI project management life cycle consists of 5 distinct phases.  Starting from conceptualization, design, and planning, through implementation and deployment. Finally, there is maintenance and optimization.

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 Conceptualization: This is the initial stage where the project’s vision and goals are defined. For example, tt involves identifying the project’s key objectives. It outlines what problems the AI will solve, and defines the scope of the project. This stage is also where stakeholder requirements are gathered and initial feasibility studies are conducted.

Design and Planning: In this stage, the detailed planning and design of the AI system takes place. This includes selecting suitable Generative AI techniques, defining the architecture of the AI system, and planning the resources and timeline for the project. This is also the stage where potential risks are identified and mitigation strategies are planned.

Implementation: This is the stage where the actual coding and development of the AI system take place. This includes data collection and preparation, model training and tuning, and integration of the AI system with other systems. Regular testing and quality checks are conducted to ensure the system is functioning as expected.

Deployment: After the AI system is developed, it is deployed into the production environment. This includes setting up the necessary infrastructure, migrating the AI system to the production environment, and carrying out user acceptance testing. This stage also involves monitoring the Generative AI system to ensure it’s performing as expected and making any necessary adjustments.

Maintenance and Optimization: This is the final stage of the lifecycle, where the AI system is regularly reviewed and updated to ensure it remains effective. This includes ongoing monitoring, fine-tuning the model as needed, updating the system to adapt to changing requirements, and addressing any issues or problems that arise.

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Why Choose Us

Partnering with Vstorm offers distinct advantages for your GenAI journey:

Full control, transparency and predictability

You pay just for time and resources used on the project, so it is appropriate for flexible administration of various sorts of projects long and short-term.

Scenario-based Generative AI development

Using scenario-based methodology, project management and outsourcing of complex IT projects become effortless, predictable, and autonomous. When compared to pure waterfall or pure SCRUM, the scenario-based methodology performs better.

Reliable tech stack

Benefit from our team of experienced professionals who possess deep expertise in Generative AI and a commitment to deliver..

Transparent communication

Count on our transparent and reliable communication throughout our partnership, fostering trust and establishing a strong foundation for success.

Generative AI Development Success Story

AI Chatbot Fit for a Job

AI Chatbot Fit for a Job

In an increasingly competitive job market, making an impactful first impression is crucial. An essential component of this is a well-crafted cover letter, tailored to the job description. This was the challenge faced by a U.S.-based client looking for a way to make this process efficient and effective. Their goal was to create a strong Proof of Concept, for future product development and launch in SaaS model.

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AI

Evryface, an AI-powered solution for professional photoshoots

We have technically and strategically supported the recently launched new product called Evryface. The product is an AI-powered solution.  It enables users to create professional photos, avatars, and headshots of themselves without ever leaving their homes. The platform allows users to upload their photos and receive studio-quality photos within minutes. It offers a range of customization options to suit their preferences.

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Interio AI, an AI-powered solution for professional interior design

The AI-powered interior design startup was looking to develop a cutting-edge interior design assistant that would use artificial intelligence to create personalized recommendations for users. However, they lacked the necessary expertise and resources to develop such a complex system on their own. That’s where Vstorm, a strategic startup advisory and technology development company, came in.

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Talk to a real person and book free AI Generative AI consultation!

Antoni Kozelski CEO & Co-founder

Key concepts

As you embark on your entrepreneurial journey, it’s essential to keep up with the latest technologies, concepts, and applications to stay ahead of the game.  Let’s check the generative AI glossary that can help skyrocket your startup.

ChatGPT-4: an advanced conversational AI model that offers startups and SMBs a powerful tool for seamless customer interactions and streamlined operations. With its sophisticated natural language processing capabilities, ChatGPT-4 enables businesses to enhance customer support by efficiently addressing queries, providing personalized recommendations, and nurturing leads. Additionally, it empowers internal teams by handling administrative tasks, facilitating collaboration, and offering data-driven insights. By customizing ChatGPT-4, startups and SMBs can optimize their resources, improve productivity, and deliver exceptional customer experiences, ultimately driving growth and success in an increasingly competitive business landscape.

Stable Diffusion is an open-source text-to-image model developed by Stability AI. It uses advanced technology called latent diffusion models (LDMs) and pretrained autoencoders to generate detailed images based on text descriptions. This model offers accessibility and improvements over previous models by incorporating variational autoencoders, U-Net architecture, and a text encoder for conditioning. It supports both creating images from scratch and modifying existing images through techniques like inpainting and outpainting. Stable Diffusion’s open approach challenges the control of major companies in the field and has sparked debates about moderation, content filtering, and ethical concerns.

Synthetic Data Generation is a technique that involves creating artificial data that mimics real-world data. It is increasingly being used by startups and SMBs to overcome data limitations and drive innovation in various applications. Synthetic data offers a solution when real data is scarce, sensitive, or not readily available. By generating data with statistical characteristics similar to real data, businesses can perform testing, research, and development without compromising privacy or relying solely on limited datasets.

Startups and SMBs can leverage synthetic data to train machine learning models, validate algorithms, improve product development, and enhance decision-making processes. It provides an opportunity to address data limitations, mitigate bias, and explore new possibilities in machine learning applications. As the synthetic data market continues to grow and new startups emerge in this field, businesses have access to a range of providers and tools to support their synthetic data needs. Embracing synthetic data generation can unlock new opportunities and enable startups and SMBs to thrive in a data-driven world

  • Text-to-Speech (TTS)

Ever asked Siri a question or had Google Maps tell you where to turn? If you have, then you’ve interacted with Text-to-Speech technology. Simply put, TTS converts written text into spoken words. It’s what allows our devices to talk to us, making technology more accessible and interactive.

  • Audio AI Generation

Next up, we have Audio AI Generation. This tech takes Text-to-Speech a step further by synthesizing realistic sounds and voices. From creating voiceovers for animations to generating music, Audio AI is the maestro behind the scenes. It’s even been used to create entire albums and soundscapes – pretty cool, huh?

  • Video AI Generation

Last but certainly not least, we’ve got Video AI Generation. This is the big league, folks! Here, AI takes audio or text inputs and creates corresponding visual content. It can be used for everything from deepfakes (please use responsibly!) to making alterations in existing videos, and even creating new visual content from scratch.

Imagine a toddler learning to walk. They stand, wobble, fall, stand again, and with each try, they get a little bit better. That, in a nutshell, is Reinforcement Learning (RL). RL is an AI technique where a model learns to make decisions by trial and error, gradually improving over time.

Think of RL as your startup’s personal optimization guru. Whether you’re managing inventory, scheduling tasks, or figuring out the best way to allocate resources, RL can crunch the numbers, try out different strategies, and find the most efficient way forward.

It’s like a virtual game of ‘hot and cold’ – the AI gets feedback (reward or punishment) based on the actions it takes, nudging it towards the optimal solution. Over time, it learns to make better decisions, helping your startup become more efficient and competitive.

Ever wish you could teach your computer to understand human language? With Natural Language Processing (NLP), that’s possible! NLP is a branch of AI that helps machines read, understand, and make sense of human language.

Imagine the possibilities: You could analyze customer reviews to identify common pain points, automate content moderation on your platform, or even use it to analyze market sentiment on social media. The applications are nearly limitless.

NLP can turn a mountain of unstructured data into valuable insights, helping you understand your customers better and respond to their needs more effectively. And the best part? It can do all of this in real-time, giving you the insights you need when you need them.