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In-depth research reports, performance benchmarks, and scalable AI infrastructure architecture from the Acadify engineering team.
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Optimizing Enterprise AI with Cloud-Native Architecture: A High-Performance Engineering Guide
Introduction As enterprise AI continues to grow in importance, organizations are looking for ways to optimize their AI workloads for high-performance engineerin…
End-to-End Guide to Setting Up vLLM with Ray on Multi-GPU Clusters
Architecture Overview & Prerequisites To set up vLLM with Ray on multi-GPU clusters, you will need: A multi-GPU cluster with at least 4 GPUs Ray installed on e…
Real-Time Multi-Agent Customer Routing for Fintech Enterprises: A Scalable Solution
The XYZ Fintech Enterprise is a leading provider of financial services, with a large customer base and a complex system for routing customer inquiries to the ap…
Unlocking Real-Time Multi-Agent Customer Routing with Fine-Tuned Nemotron Models and 90% Cloud Cost Reduction
A leading insurance company faced significant challenges in their customer routing system, which was experiencing latency spikes and high cloud costs. To addres…
Building Scalable Production AI with Hybrid Chunking & Reranking
Executive Problem Statement & Financial/Operational Risk As AI adoption continues to grow, enterprises face increasing pressure to deploy high-performance AI mo…
AWQ vs GPTQ vs FP8 Quantization Accuracy Degradation: A Critical Showdown
In this critical showdown, we pit AWQ, GPTQ, and FP8 against each other in terms of quantization accuracy degradation. Our benchmark test environment consists o…
Unlocking Long-Context Retrieval Precision with Hybrid Mamba-Transformer MoE Architectures
Abstract & Executive Synthesis This research report explores the use of Hybrid Mamba-Transformer MoE architectures for long-context retrieval tasks. We investig…
Building Scalable Enterprise AI: A Cloud-Native Architecture for High-Performance Engineering
Introduction Building scalable enterprise AI requires a cloud-native architecture that can handle high-performance computing, reduced latency, and increased thr…
End-to-End Guide to Setting Up vLLM with Ray on Multi-GPU Clusters
This guide provides a step-by-step walkthrough of setting up and optimizing vLLM with Ray on multi-GPU clusters for high-performance enterprise AI applications.…


