abcloudz
Generative AI (GenAI) Development Services

Generative AI (GenAI) Development Services

Reinvent your business operations with generative AI solutions to outpace competition.
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Adopt generative AI with proven experts

While the field of Gen AI has only recently begun to significantly impact real-world business, we recognized its potential early on. Our team of engineers has already gained substantial experience and expertise with GenAI through real-world projects. We offer consulting and development of Generative AI services, built on our team’s world class software development background. 

Our generative AI development services

Consulting and strategy

Consulting and strategy

Custom RAG-based solutions

Custom RAG-based solutions

LLM integration & deployment

LLM integration & deployment

Fine-tuning AI models

Fine-tuning AI models

Vector search integration

Vector search integration

Post-production support

Post-production support

AI models we utilize

Large Language Models (LLMs) are sophisticated AI systems trained on extensive datasets. They excel in understanding and generating human-like text, making them suitable for various applications. We have frequently worked with these LLMs: ChatGPT 3.5, 4, and 4o; Anthropic’s Claude 2 and 3 families; Amazon’s Titan family; Meta’s LLaMA 2; and Google’s Gemini. Below is a comprehensive list of the LLMs we have worked with.
OpenAI

OpenAI

We have extensive experience with the entire ChatGPT family, including versions 3.5, 4, and 4o. We also use OpenAI’s embedding models for text vector representations.
Amazon Bedrock

Amazon Bedrock

Our team has the expertise to work with all the LLMs provided through Amazon Bedrock, including AI21 Labs, Titan, Anthropic Claude, Cohere, Meta Llama, Mistral AI, and Stability AI. We also offer comprehensive model evaluation and implement guardrails for Amazon Bedrock.
Azure AI Language

Azure AI Language

We work with various LLMs supported by Azure AI Language, including GPT-4o, GPT-4, GPT-3.5, Llama 2, Mistral Large, and Hugging Face models, enabling us to handle diverse natural language processing tasks and customize models for specific needs.
Gemini

Gemini

We can fine-tune Gemini 1.5 for your specific needs, integrate it seamlessly with Google Cloud, and leverage its advanced multimodal capabilities for a wide range of applications.
Open-source

Open-source

Our team is experienced in working with open-source large language models, including Meta’s LLaMA 2, Salesforce’s XGen-7B, Falcon Models, among others, accessed through platforms and projects like LangChain, providing a broad range of options for developers.

We offer out-of-the-box RAG AI chatbot solution

Imagine you could add a smart chat box to any of the knowledge sources of your business: Word or .pdf documents, database, website or mobile content, Excel sheets, etc. That’s exactly the solution we’ve built for our needs and now offer to all our customers. 

You can leverage a ready-made framework, designed to connect to any client knowledge base in various data formats and deliver relevant responses powered by AI. This solution can be swiftly customized to meet the unique needs of each client, ensuring rapid deployment and seamless integration into various platforms such as websites, mobile apps, and other customer support systems.

What it does:

Our RAG-based AI chatbot enhances user interaction by providing accurate, context-aware responses using the latest information from various knowledge sources.

It bridges the gap between users’ queries and relevant data, making it ideal for applications in customer support, information retrieval, and personalized user experiences.

Key features and advantages:

  • 1

    Accuracy and relevance

    By integrating real-time data and domain-specific context into the prompts, our chatbot delivers precise and up-to-date answers, surpassing the capabilities of standard language models.
  • 2

    Modular architecture

    The solution comprises loosely coupled modules, each optimized for specific tasks such as data extraction, vectorization, and response generation. This design allows for flexible customization and scaling.
  • 3

    Multi-platform Integration

    The chatbot can be embedded into websites using Node.js and ReactJS or integrated into mobile apps through frameworks like Swift, Kotlin, React Native, and Flutter. It can also be incorporated into other customer support platforms.
  • 4

    Versatile knowledge bases

    Our solution leverages both vector and graph databases. PostgreSQL with the pgvector plugin and Neo4j are used to store and retrieve data efficiently, enabling the chatbot to understand and respond to complex queries
  • 5

    Advanced admin tools

    The admin panel offers comprehensive management features, including Q&A database customization, document verification, session chat logs, chatbot testing, and system settings.

Customization options

Our AI chatbot solution is designed for rapid customization to fit your specific business requirements. The system’s modular nature allows us to adapt each component to handle your unique data sources and business processes efficiently.

Technology stack of the solution

Large language models

Flexible integration with various LLMs including OpenAI’s ChatGPT, Amazon Bedrock, Azure AI Language, Google’s Gemini, and open-source models like Meta’s LLaMA 2, Salesforce’s XGen-7B, and others.

Frontend

Node.js, ReactJS for web integration; Swift, Kotlin, React Native, Flutter for mobile applications.

Backend

PostgreSQL with pgvector plugin for vector databases, Neo4j for graph databases.

Data processing

OpenAI and Amazon Bedrock for content vectorization, adaptable to other embedding services like Word2Vec, GloVe, FastText, and ELMo.

Learn more

For a detailed exploration of our RAG-based AI chatbot solution, including technical specifics and cost considerations, read our comprehensive blog post here.

Contact ABCloudz today to discuss how our AI chatbot solution can be tailored to meet your business needs and drive growth.

Our approach to generative AI development

1

Consulting and strategy

We start by defining the project scope, objectives, and team roles. We also gather and understand your specific requirements and expectations.
2

Design and MVP development

Our experts design a custom architecture for your Generative AI solution. We then implement an MVP (Minimum Viable Product) to validate its efficacy. This involves integrating the LLM into your environment, creating a simple prototype, conducting initial testing, and collecting feedback to understand user perceptions and performance as you try out the MVP version.
3

Full-scale development

Based on the feedback collected from the MVP phase, we develop and integrate various components. This includes setting up environments, extracting and indexing metadata, prompt engineering, LLM tuning, chat service development, UI implementation, and front-end and back-end integration in a cloud environment.
4

Testing and improvement

In this phase, we conduct extensive unit, integration, and system testing to identify and fix issues. We also perform user acceptance testing (UAT) to gather real-world feedback. Based on test results, we iteratively refine the Generative AI system, adjust parameters, and optimize performance using advanced debugging and automated testing frameworks.
5

Beta launch and handover

We finalize all components, perform comprehensive testing, and prepare the solution for deployment. We then launch the Beta version and hand over the solution to your team, providing full documentation and support.
6

Post-production support

Our commitment doesn’t end with deployment. We provide ongoing post-production support, offering flexible upgrade and maintenance services. Our team proactively monitors the system to swiftly detect and resolve potential issues, ensuring your solution continues to meet evolving business needs.

Technology Stack

Other AI services

Explore our comprehensive AI services beyond generative AI, designed to enhance capabilities in IoT, video quality, model fine-tuning, text classification, computer vision, and more.

Natural language interface for data platforms

AI text classification and recommendation

Integrating AI into IoT

AI video enhancement

AI-powered computer vision

AI-powered image editing

AI-powered smart interfaces

Embedded AI voice recognition

Get started today

Let us help you discover how Generative AI can transform your operations and drive growth.

 

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