Upscale your business with some of the best AI Agents in the marketTechnologies that help us deliver premium RAG service

Our updated tools and technology kits help us refine your digital integrations

01.

NLP Library & Frameworks

Choose the right technology to build a resilient RAG system
NLTK
SpaCy
Hugging Face Transformer
TensorFlow

02.

Vector Database

Improve output accuracy with the fitting vector database
Faiss
Annoy
Milvus
Elasticsearch

03.

AI Models

Resolve all the business complexities with the ideal AI model
GPT-3
GPT 4
Stable Diffusion

04.

Cloud Storage

Centralize data storage for easy access and flexibility with reliable cloud platforms
AWS S3
Google Cloud Storage
Azure Blob Storage

05.

Database Management System

Choose an apt DBMS or its combination for effective data structuring & management
PostgreSQL
MySQL
MongoDB

06.

Containerization

Easily deploy and manage the RAG solution with an ideal containerization tool
Docker
Kubernetes
Amazon ECS

What are the benefits of RAG implementation?

01.

Enhanced Accuracy

RAG in LLM models helps it access the current, more refined datasets, thus improving the overall quality of output

03.

Improved Services

Power chatbots with RAG software to make the conversation more case-specific and streamline the overall experience

02.

Better Contextualization

RAG implementation allows context-driven, relevant response generation even in complex conversations

04.

Easy Upscaling

RAG fosters faster scaling and expanding by substituting model fine-tuning with external source access when needed

Our well-defined approach to RAG implementation

We ensure seamless RAG integration into your existing system
01

Requirement Identification

Assess both RAG implementation opportunity and data quality for retrieving and generating relevant information

02

Data Gathering & Structuring

Collect suitable data from multiple sources and convert it into an easy-to-access and search format

03

Select Retrieval & Generative Model

Choose an ideal retrieval model based on your primary requirements and a generative model per your usage

04

Combine The Two Models

Build an effective system to process queries, contextualize, and generate relevant output by merging retrieval and generative models

05

Evaluate & Refine

Utilize key metrics to understand how the RAG solution is performing and refine it accordingly

What makes JBTech a reliable RAG development partner

Our team offers premium-quality services to optimize your workflow
years of delivering quality solutions
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Happy Clients
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AI Experts
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Successful Projects
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Client Retention
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Client Focus Services

We streamline collaboration, simplify communication, and strategize the whole process, keeping client’s requirements as a central priority.

Technical Adeptness

Our team has a strong understanding of AI, its related services, and RAG techniques. We design progressive solutions that ensure long-term success for our clients.

What Our Clients Say About Us

Their collaborative approach fostered a sense of partnership and trust, where our voices were heard and our vision was respected.

Rosanna Turk

Co-Founder

Working with JB Tech made everyone enjoy being part of the project. It never felt like two separate teams, but just one big team. Everything felt natural, easy, even when there were challenges.

Heather Read

Head of Systems Integration

JB Tech successfully delivered a working prototype of the dashboard, meeting our expectations. The team responded quickly to requests and modifications, and they were hands-on, knowledgeable, and receptive throughout the project.

Geir Arne Evjen

CTO

Working with JB Tech was a pleasure. The relationships that we build, quite quickly, led to a really lovely experience. The whole team was highly efficient, creative and tactical.

Toby Lewis

Senior Manager, Collaboration Strategy

JB Tech work has lowered our system downtime and fastened the turnover of tickets on the help desk. The team has executed updates correctly and maintains communication via emails and messages. JB Tech Co-CEO participation in the project has been crucial.

Tom Blades

Head of Systems Integration

Our Most Recent Blog Posts

When our collective minds come together, remarkable things unfold. Poke around in our latest thoughts, tinkerings and breakthroughs in the realm of all things digital.

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Frequently asked questions about AI Agents

Augment digital solution integration with more clarity on the technology
What are AI agents?
An AI agent is a smart computer program that automates and resolves complexities while reducing the dependencies on human resources. The expectations are set manually for the agent, but the agent itself determines the best possible route to reach the goal.
While the best tool depends on your requirements and minute project details, some popular AI agent tools are Jupyter, Google Colab for development, Dilogflow and RASA for designing a conversational chatbot, and Caffe2 or PyTorch as ML platforms and more
Yes, you can do it by consulting with an AI agent development company. The best route for non-technical industries is to consult professionals to build you a custom AI solution with optimal performance and all the required features.

Yes, indeed. Businesses can choose based on their requirements, though AI agents offer much better functionalities, such as handling complex tasks, generating valuable insights, autonomous decision-making, and more.

We offer regular post-deployment maintenance and support to improve the AI agent’s performance and functionalities and ensure optimal utilization of its advantages.

Get In Touch

Have a project in mind? No need to be shy, drop us a note and tell us how we can help realise your vision.


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