We Architect, Optimize,
and Scale Production-Grade
AI Pipelines.
Helping mid-market enterprises cut compute costs, eliminate RAG hallucinations, and safely deploy custom fine-tuned LLMs.
Standard RAG Stack
Unoptimized PipelineArvento Optimized Stack
vLLM Speculative Decoding$ profiling active... waiting for query request.Our Capabilities
Custom LLM Fine-Tuning & Quantization
Domain adaptation, LoRA/QLoRA training configurations, weight quantization (GPTQ/AWQ/FP8), and open-source model hosting deployment blueprints.
Production-Grade RAG Architecture
Sparse/Dense Hybrid Search implementation and Cross-Encoder Re-ranking optimization alongside advanced semantic chunking.
LLMOps & Cost Optimization
High-throughput vLLM orchestration, speculative decoding integration, cold-start mitigation, and cloud GPU cluster resource balancing.
Autonomous Agentic Orchestration
Hierarchical multi-agent planning frameworks, secure runtime tool execution, state-machine conversational memory, and self-correcting logic flows.
Infrastructure Optimization & Compute Savings Calculator
Simulation Parameters
Monthly Compute Projections
Proof of Work
Fine-Tuning Llama 3.1 8B for Custom Style Transfer
A deep dive into dataset curation bottlenecks, QLoRA rank adapters selection, and serving high-throughput inference using vLLM speculative decoding.
Speculative Decoding: 3x Throughput Improvement
Implementing Llama 3.1 1B draft model speculation validation cycles inside vLLM clusters, scaling tokens generation throughput and dropping memory bandwidth latency.
Hybrid Vector Search & Cross-Encoder Re-Ranking
Replacing standard embeddings search with dense vector HNSW retrieval and Elasticsearch BM25, optimizing retrieval relevance using Cross-Encoders.
Engineering Standard
We select a limited number of high-impact infrastructure optimization projects per quarter.
We do not build simple MVPs or write generic prompts. We engineer low-latency, hardware-optimized pipelines designed to scale to millions of requests without inflating cloud GPU bills.
Engaging with Arvento
Architecture Discovery
We analyze your production pipelines, measuring time-to-first-token, query paths, retrieval accuracy, and cluster utilization under load.
Optimization Blueprint
Our consultants deliver a detailed system design report outlining exact bottleneck remediations, quantized models, and host specifications.
Production Integration
We deploy the optimized pipelines in your VPC, aligning LLMOps logging with standard monitoring (Prometheus/Grafana) and training adapters.
Audit Your AI Pipelines.
Schedule an infrastructure audit with our engineering team. We will analyze your compute logs, pinpoint bottlenecks, and draft an optimization route.