From Legacy to Lightning-Fast: How PeerIslands Transformed Telco’s Platform

In this case study, a leading Telco faced scalability challenges with legacy technology. An optimized MongoDB data processing pipeline, leveraging Confluent Kafka, Kotlin, and Spring Boot, delivered impressive results. The solution scaled seamlessly, achieving faster processing, and ensuring 99.999% uptime.

Reshaping Software Development powered by PeerAI

PeerIslands combines proven expertise with an efficient platform, optimized for MongoDB. Their collaborative approach, top-notch experts, and focus on customer fulfillment make them a valuable partner for businesses seeking to innovate and improve using AI.

Extending OpenAI GPT-4 using LangChain and Pinecone for Q&A over your own content

Curious about supercharging language models? Look no further! This article spills the secrets of enhancing Large Language Models (LLMs) like OpenAI’s GPT-4. By leveraging LangChain and Pinecone, you can improve accuracy and reliability in your AI-powered Q&A systems. Give your chatbot a PhD in understanding context and providing spot-on answers.

Future of GenAI Applications: From RAG to Multi-Agent Collaboration

Intrigued about the future of AI and how it may be used to combine the abilities of multiple GenAI Agents through collaboration? This article looks through the different types of GenAI Applications and innovative design patterns like Agentic Workflows and Multi-Agent Collaboration, in order to create LLMs capable of human-like decisioning. The future of AI is bright, and with the tools we have available to us, the potential is limitless.

Time Series data in MongoDB

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PeerIslands Announces New CEO

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Enabling Virtual visits for Leading Urgent Care Provider 

In this case study, PeerIslands assisted a urgent care solutions provider by designing a front door solution, utilizing MongoDB charts to deliver operational analytics and develop a custom telemedicine solution to enable virtual visits.

Modernization at a Leading Australian Bank

PeerIslands worked with MongoDB and Google Cloud to accelerate modernization using Generative AI. Bank’s legacy application were built on legacy Java, Stored Procedures in SQL Server and IBM Message Queues.