Generative AI to Propel Your Business Forward

Generative AI technology has taken the world by storm, following in the footsteps of its AI predecessors. In this age of constant connectivity, it’s rare to find someone who hasn’t heard of AI or even sought advice from tools like ChatGPT.

At NIX, we stay up-to-date with AI advancements and help businesses capitalize on the creative possibilities of our generative AI development services. We seamlessly integrate AI technology to streamline knowledge management and content generation across various media formats, including text, images, audio, and code. Leveraging over a decade of expertise in AI, ML, deep learning, and generative AI, we help businesses foster innovation, improve efficiency, and deliver personalized customer experiences, ensuring they stay ahead of the competition.

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Key Benefits of Generative AI Development Services

20-25%

revenue growth reported by businesses using generative AI within two years.
(Deloitte)

94%

of business leaders consider generative AI critical to their strategic goals.
(Deloitte)

86%

of IT leaders expect AI to play a major role soon.
(Forbes)

60%

of companies plan to significantly boost investments in generative AI over the next three years.
(Deloitte)

67%

foresee increased AI investment, with many allocating 20%+ of digital budgets.
(McKinsey)

50%

of enterprises are projected to fully integrate generative AI into their core operations by 2026.
(Deloitte)

Explore How Generative AI Can Benefit Your Business

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Generative AI Development Services We Provide

Generative AI Consulting

Our seasoned experts provide generative AI consulting services to help you assess the transformative potential of generative AI within a specific context. Through rapid evaluations and in-depth technical expertise, we identify high-impact, actionable use cases and develop a strategic roadmap for AI implementation to accelerate your competitive advantage.

Generative AI Model Integration

Our data scientists seamlessly integrate out-of-the-box generative AI solutions into your IT infrastructure to boost productivity, build differentiated experiences, and accelerate innovation. We help you streamline workflows, create unique user experiences, and elevate customer satisfaction through increased engagement.

Model Fine-tuning and Maintenance

We provide comprehensive model maintenance and optimization services to maximize the performance of your generative AI models. Our proactive approach utilizes automated monitoring and data updates, along with infrastructure optimization, to ensure peak efficiency and minimize manual intervention at any scale.

Cloud and On-premise AI Model Deployment

We offer comprehensive AI deployment services for generative AI solutions, tailoring our approach to your specific needs and infrastructure preferences. Whether you opt for the scalability of cloud-based platforms or the enhanced control of on-premise setups, our team of experts ensures optimal performance, scalability, and security throughout the entire deployment process.

Generative AI Product Development

At NIX, we provide comprehensive generative AI development services tailored to your needs. Our process begins with a meticulous assessment of your business objectives, ensuring alignment between your goals and our technical approach. From there, we select the most fitting AI model and fine-tune it to match your specifications. Finally, we seamlessly integrate generative AI solutions into your product roadmap, ensuring maximized efficiency.

Leverage Gen AI for your business

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Our Generative AI Solutions

01/

AI Agents

Deploy tailored AI Agents that seamlessly integrate into your systems to automate complex workflows and enhance decision-making. We utilize advanced techniques, such as RAG and multi-agent architectures, to ensure you gain actionable AI insights and fully operationalize AI within your business.

02/

LLMs

Harness the reasoning power of large language models (LLMs) to automate sophisticated tasks, from advanced data summarization and code generation to deep domain-specific querying, thereby improving decision-making and operational intelligence. These capabilities are built upon powerful natural language processing foundations.

03/

Audio, Video, and Image Generation

Accelerate content creation by leveraging generative AI models to autonomously produce high-quality, custom audio, video, and image assets, transforming creative workflows and significantly reducing production time and costs.

04/

Conversational AI

Leverage NLP-powered conversational gen AI solutions, such as chatbots and virtual assistants, to enhance interactions by accurately interpreting user requests across platforms like Slack and Messenger. These generative AI systems optimize business operations by processing vast linguistic data with speed and consistency, allowing you to reallocate human resources and reduce costs.

05/

Multimodal AI

Expand your AI’s capabilities by integrating our Multimodal AI solutions, which process and generate content across different formats simultaneously (text, image, audio), allowing for richer, more human-like interactions and complex data analysis.

06/

RAG Fine-tuning

Drive quality and efficiency across your entire architecture by grounding LLMs in real-time data using RAG and applying advanced fine-tuning, such as PEFT, to optimize any model, ultimately reducing overhead and maximizing potential.

Industries Leveraging Generative AI

  • Icon Healthcare

    Healthcare

    • Drug discovery and generation
    • Claims assistant for patients
    • Automated regulatory compliance
    • Synthetic MRI image generation
    • X-ray image enhancement
    • Genetic data analysis
    • Treatment response prediction
  • Icon Retail

    Retail and e-Commerce

    • Virtual voice customer assistants
    • Product Issue troubleshooting
    • Conversational chatbots
  • Icon FinTech

    Financial and Banking

    • Contract and SoW creation
    • Algorithmic trading strategies
    • Predictive market analysis
    • Anomaly detection in transactions
    • Enhancement of encryption protocols
  • Internet Services and Computer Software

    • AI-driven code review and generation
    • Documentation automation
    • Automated testing and QA
    • Intelligent debugging
  • Marketing and Advertising

    • Personalized sales and marketing assistant
    • Research-based report generation
    • Predictive trading algorithms
    • Virtual influencer marketing
  • Enterprise

    • Business process automation
    • Content generation
    • Compliance report generation and analysis
    • AI-powered user care chatbot operational optimization
  • Human Resources

    • Personalized onboarding
    • Candidate screening
    • Custom career plan generation
    • Performance evaluation assistance
01

Explore How Generative AI Can Benefit Your Business

Talk to an Expert   

NIX LLM Expertise

As a part of gen AI development services, NIX tailors large language models (LLMs) to your unique business requirements through a range of adaptable methods. We collaborate with you to determine the most suitable approach, ensuring the generative AI solution aligns perfectly with your specific goals and objectives.

01/

Prompt Engineering

A streamlined methodology for agile LLM adaptation, allowing you to harness the power of LLMs without extensive AI training or infrastructure investments. By strategically crafting instructions within the model context, prompt engineering facilitates efficient and cost-effective AI adoption, particularly suited for tasks such as:

  • Content creation
  • Data extraction
  • Text formatting
  • Summarization
Prompt Engineering
02/

Retrieval-Augmented Generation (RAG)

A strategic hybrid approach combining information retrieval and text generation, empowering LLMs to leverage your specific business knowledge for precise, accurate responses. While requiring well-prepared data for optimal retrieval, RAG enhances LLM capabilities without extensive retraining, making it impactful for tasks like:

  • Custom Q&A chatbots
  • Knowledge retrieval
  • Customer support
  • Medical diagnosis support
Retrieval-Augmented Generation (RAG)
03/

Parameter-Efficient Fine-Tuning (PEFT)

In contrast to RAG and prompt engineering, PEFT necessitates a prepared dataset due to its training of the LLM. This method is the most resource-efficient, minimizing cloud computation expenditures. Moreover, PEFT consistently delivers results comparable to prompt engineering/RAG while adeptly handling complex LLM behavior and scenarios, consequently ensuring heightened robustness in real-world applications. Key applications include:

  • Chatbots with domain-specific terminology
  • Enhanced performance on specialized data
  • Task-specific adaptation
  • Multi-task learning
Parameter-Efficient Fine-Tuning (PEFT)
04/

Full Fine-tuning

For applications where utmost accuracy and domain expertise are paramount, full fine-tuning of LLMs emerges as the preferred solution. Full fine-tuning distinguishes itself from PEFT by adapting all model parameters, leading to unparalleled task-specificity at the cost of higher computational demands and a larger, meticulously prepared dataset. This methodology is ideal for:

  • Sentiment analysis tailored to niche markets or industries
  • Adapting models to new regulations or compliance standards
  • AI-powered content creation in specialized domains like scientific writing
  • Mastering complex tasks requiring in-depth knowledge
Full Fine-tuning

Image Models Expertise

  • Text-to-Image Generation
    • Prompt Engineering: Craft detailed and precise textual prompts to guide the AI in generating specific images.
    • Conditioning: Use additional input data such as sketches, masks, or other images alongside text prompts to refine the output.
  • Image-to-Image Translation
    • Style Transfer: Apply the style of one image (e.g., Van Gogh’s painting style) to another image while preserving its original content.
    • Image Editing: Modify specific aspects of an image based on other image inputs, such as changing colors, textures, or objects within the scene.
  • Inpainting and Outpainting
    • Inpainting: Complete or restore missing or damaged parts of an image by using the surrounding context as a guide.
    • Outpainting: Expand an image beyond its original borders to create new content that seamlessly integrates with the existing visuals.
  • Super-Resolution Enhance the resolution of an image by generating higher-quality details from a lower-resolution input.
  • Data Augmentation Create artificial images to augment training datasets, improving the performance of other machine learning models.
  • Generative Adversarial Networks (GANs) Employ a two-network system (generator and discriminator) where the generator produces images, and the discriminator assesses them, leading to enhanced quality in generated images over time.
  • Diffusion Models Gradually remove noise from an image to generate high-quality results, often used for more stable and realistic outputs compared to GANs.
  • Model Fine-Tuning Adjust pre-trained models on specific image datasets to improve performance for particular applications.

Our Generative AI Development Process

We offer an integrated approach to implementing generative AI solutions that consolidate tailored industry-specific expertise, diverse technical capabilities, a robust partner network, and responsible design principles.

Requirement analysis

Planning and data preparation

Model training and fine-tuning

Implementation and adoption

Maintenance and upgrade

Schedule a Discovery Call with a NIX AI Expert

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Our Expertise with Generative AI Models

  • OpenAI ChatGPT 4.0
  • Llama 3 logo
  • Claude AI logo
  • dalle2 logo
  • whisper ai logo
  • stability ai logo
  • microsoft Phi-2 logo
  • Google Gemini logo
  • Mistral_AI_ logo
  • bloom logo
  • Midjourney_l logo
  • Google bert logo
  • roberta logo
  • flux logo

Relevant Case Studies

We really care about project success. At the end of the day, happy clients watching how their application is making the end user’s experience and life better are the things that matter.

View all case studies

AI Agent for Enterprise-grade Device Management

Internet Services and Computer Software

Manufacturing

Success Story AI Agent for Enterprise-grade Device Management image

Cloud-based RPA Enterprise Solution

Internet Services and Computer Software

Success Story Cloud-based RPA Enterprise Solution image

AI Web Platform for Reproductive Science

Healthcare

Success Story AI Web Platform for Reproductive Science image

Voice Recognition Platform for Feedback Exchange

Oil & Gas

Mining

Success Story Voice Recognition Platform for Feedback Exchange  image
01

What Our Clients Say

Buzz Sharifi photo

Buzz Sharifi

Account Manager at TransGrade, CRM

Matthew Brown photo

Matthew Brown

VP of Engineering at Elsevier

Christian Rohner photo

Christian Rohner

Project Manager at Information Products AG

Jeremy Barron photo

Jeremy Barron

Senior Director of Engineering at Premier

Craig Burris photo

Craig Burris

Director of Operations at CarSoup

Jason Scalvini photo

Jason Scalvini

Senior VP of Technology

Ilya Kottel photo

Ilya Kottel

VP R&D at HumanEyes

Noam Shalit photo

Noam Shalit

COO at SafeRide Technologies Ltd

Steve Berardelli photo

Steve Berardelli

Sr. Director of Engineering for MindTap

Moody Heard photo

Moody Heard

Co-Founder at Buildforce

Mike Ortner photo

Mike Ortner

President at Ortner Enterprises DBA North Two Five

Mark DeJarnatt photo

Mark DeJarnatt

Chief Technology Officer at Sparkle Stories LLC

Eric Spear photo

Eric Spear

SVP of Engineering at Cengage

Jeremy Reither photo

Jeremy Reither

Consultant & Advisor at DemandSide

Eve Epstein photo

Eve Epstein

CEO/Founder at SoleVenture, Inc.

David Stutzman photo

David Stutzman

President of Conspectus, Inc

Dave Kochalko photo

Dave Kochalko

Co-Founder & CEO at ARTiFACTS

Kevin Lee photo

Kevin Lee

Co-Founder

Norman Thiem photo

Norman Thiem

Owner, N2 Plus

Ariel Orbach photo

Ariel Orbach

Co-Founder & CTO

Anonymous photo

Anonymous

CTO, Real Estate Firm

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Anonymous

Founder & HOP, Fitness Space Rental Platform

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Anonymous

CTO, Color My Life, Inc

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Anonymous

Department Head, Fignum Limited

Why Choose NIX for Generative AI Development

  • Rapid Deployment and Seamless Maintenance

    We ensure seamless integration and minimize post-deployment challenges by providing timely maintenance.

  • Robust Security

    We prioritize your data’s protection through robust security measures, including encryption, access controls, and vigilant monitoring. To ensure resilience, we conduct regular audits, bias and ethics checks, and adversarial testing. Confidentiality is assured through strict NDAs.

  • Seasoned Expertise

    Our team comprises seasoned ML engineers, data scientists, and domain experts experienced in building generative AI models. We leverage the full power of generative AI to create dynamic, relevant solutions that propel your business goals forward.

Generative AI Development Technology Stack

Max Ushchenko

Max is our senior practice leader and evangelist for the “big triad” of machine learning, data analytics and data engineering, with a vast background in AI, BI services, and product management.

Head of Data and AI Practice at NIX

Max is our senior practice leader and evangelist for the “big triad” of machine learning, data analytics and data engineering, with a vast background in AI, BI services, and product management.

Eugene Rudenko

Yevhen, a seasoned AI consultant with 10+ years, delivers expert-level software optimization and business automation through strategic implementation of cutting-edge AI solutions.

Applied AI & Data Science Solutions Consultant

Yevhen, a seasoned AI consultant with 10+ years, delivers expert-level software optimization and business automation through strategic implementation of cutting-edge AI solutions.

01

FAQs

01/

What is generative AI?

Generative AI generates new content, such as text, images, and audio, by learning from existing data. Unlike traditional AI, it doesn’t just analyze; it generates original output. Generative AI consulting services can help businesses apply this technology for innovation.

Here are some examples of generative AI:

  • Generative adversarial networks (GANs) for creating realistic images
  • Large language models (LLMs) like GPT-4 for generating human-like text
  • Diffusion models for creating art from text descriptions

02/

How does generative AI work?

Generative AI works by learning patterns and structures from vast amounts of data. It then uses this knowledge to create new, original content, including text, images, and synthetic data generation. This process is driven by complex neural networks that are trained similarly to how a human learns a skill by studying examples and then producing something new. Generative AI development services help you apply these techniques for various needs.

03/

How much does it cost to develop generative AI solutions?

The cost for generative AI services depends on project scope. Factors influencing the final cost include solution complexity, specific customization needs, the effort required for data availability and quality (collection/labeling), and essential ongoing maintenance and support. Our generative AI services provide a transparent cost estimate based on the scope and complexity of your project.

04/

What are the benefits of using generative AI in my business?

Generative AI services can offer significant business benefits, ranging from enhanced productivity to improved customer experiences. Adopting generative AI can lead to increased efficiency and innovation across various business functions.

  • Enhanced Productivity: Automate repetitive tasks and streamline workflows, freeing up your team to focus on strategic initiatives.
  • Innovation and Creativity: Use AI to generate new ideas, designs, and content, driving creativity within your business.
  • Improved Customer Experience: Deliver personalized content and offer round-the-clock support with AI-powered chatbots and assistants.

05/

What industries can benefit from generative AI solutions?

Generative AI solutions are revolutionizing operations and creating new business growth opportunities across many industries. Working with generative AI development companies, businesses are applying this technology for diverse applications, from automating drug discovery in healthcare and enhancing fraud detection in finance to generating product descriptions in retail and automating content creation in media and entertainment.

06/

How can generative AI enhance customer experience?

Generative AI can revolutionize customer experiences by providing personalized interactions, round-the-clock support, and empowering self-service. This includes utilizing AI to create personalized recommendations, AI chatbots for ongoing support, and engaging content that genuinely resonates with your audience. As a generative AI development company, we help you implement AI solutions that align with your goals.

07/

How long does it take to develop generative AI solutions?

The timeline for developing generative AI solutions varies, typically taking a few months to over a year. Key factors influencing this include the project’s complexity (e.g., a simple chatbot versus a complex image generator), the availability of high-quality data for training, and the resources available, such as skilled AI engineers and computational power. We offer generative AI consulting to help businesses streamline the generative AI development process by providing hands-on expertise.

08/

What’s the difference between AI, machine learning, and generative AI?

Artificial intelligence (AI) is the umbrella term for any technology that mimics human intelligence and reasoning. Machine learning (ML) is a subset of AI that uses algorithms to learn from data and make predictions. Ultimately, generative AI is a specialized type of machine learning that focuses on creating novel data and content, rather than merely analyzing it.

09/

Can generative AI integrate with my existing systems?

Yes, generative AI can be integrated into existing systems, often through APIs, which act as a bridge between the AI model and your current software. The ease and cost of this process depend on your system’s architecture; modern, cloud-based systems with well-documented APIs are generally more straightforward to work with than older, legacy systems. For more complex or legacy systems, a custom generative AI development approach may be required to build specialized connectors and data pipelines that enable communication between the new AI model and your existing infrastructure.

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