Insights · Tag
AWS
9 articles tagged AWS.
Articles
Multi Tenant AI SaaS Architecture on AWS and MongoDB (A Practical Guide)If you are turning an AI workflow into a SaaS product, the hardest parts are usually tenancy, security, and operations. This post outlines a practical multi…Audit Logging and Provenance for AI Workflows (AWS and MongoDB Patterns)If an AI system affects legal, financial, or compliance outcomes, you need to answer: what happened, when, why, and who approved it. This post outlines audit…Cost Optimization for AI Document Pipelines on AWS (A Playbook)AI document pipelines can get expensive fast if they are built like prototypes. This post covers practical levers to reduce cost without sacrificing…Human in the Loop Document Review UI (Architecture on AWS and MongoDB)Fully automated document extraction is rare in real operations. The difference between a pilot and a production system is usually a clean human in the loop…Edge Computer Vision on Jetson with ONNX and TensorRT, Managed by AWS IoTEdge deployment is often the right choice when bandwidth is limited, latency must be very low, or data cannot leave a site. This post outlines a practical…AWS Kinesis Video Streams and Real Time Computer Vision Architecture (What to Build First)Real time computer vision projects often fail for non ML reasons: stream reliability, buffering, latency, and alert routing. This post outlines a praAWS Step Functions Patterns for Reliable Document Automation (Retries, Idempotency, and Audits)Document automation is a long running workflow: ingest, OCR, validate, route, and generate outputs. AWS Step Functions is a strong orchestrationMongoDB Atlas Vector Search RAG for Document Workflows on AWS (A Practical Blueprint)Retrieval augmented generation (RAG) is most valuable when it is attached to a real workflow: intake, search, extraction, and decision support. This postAWS Textract vs Open Source OCR for Production Doc AI (Accuracy, Cost, and Architecture)Who this is for If you are building document automation that has to work in production, not just in a notebook, this guide compares AWS Textract with l
Bring the messy version
One workflow.
A better way to run it.
Show us the tools, the handoffs, and the part that keeps slowing your team down.
---
title: "AWS"
description: "Insights tagged AWS. Lid Vizion: practical AI implementation, connected tools and custom software."
url: https://lidvizion.ai/tags/aws/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---
[Insights](https://lidvizion.ai/blogs/) · Tag
# AWS
9 articles tagged AWS.
[Let’s map your workflow](https://lidvizion.ai/contact/) · [All insights](https://lidvizion.ai/blogs/)
## Articles
- [Multi Tenant AI SaaS Architecture on AWS and MongoDB (A Practical Guide)](https://lidvizion.ai/blog/multi-tenant-ai-saas-architecture-aws-mongodb/): If you are turning an AI workflow into a SaaS product, the hardest parts are usually tenancy, security, and operations. This post outlines a practical multi…
- [Audit Logging and Provenance for AI Workflows (AWS and MongoDB Patterns)](https://lidvizion.ai/blog/audit-logging-and-provenance-for-ai-workflows-aws-mongodb/): If an AI system affects legal, financial, or compliance outcomes, you need to answer: what happened, when, why, and who approved it. This post outlines audit…
- [Cost Optimization for AI Document Pipelines on AWS (A Playbook)](https://lidvizion.ai/blog/cost-optimization-for-ai-document-pipelines-on-aws/): AI document pipelines can get expensive fast if they are built like prototypes. This post covers practical levers to reduce cost without sacrificing…
- [Human in the Loop Document Review UI (Architecture on AWS and MongoDB)](https://lidvizion.ai/blog/human-in-the-loop-doc-review-ui-architecture-aws-mongodb/): Fully automated document extraction is rare in real operations. The difference between a pilot and a production system is usually a clean human in the loop…
- [Edge Computer Vision on Jetson with ONNX and TensorRT, Managed by AWS IoT](https://lidvizion.ai/blog/edge-computer-vision-aws-iot-onnx-tensorrt-jetson/): Edge deployment is often the right choice when bandwidth is limited, latency must be very low, or data cannot leave a site. This post outlines a practical…
- [AWS Kinesis Video Streams and Real Time Computer Vision Architecture (What to Build First)](https://lidvizion.ai/blog/aws-kinesis-video-streams-and-realtime-cv-architecture/): Real time computer vision projects often fail for non ML reasons: stream reliability, buffering, latency, and alert routing. This post outlines a pra
- [AWS Step Functions Patterns for Reliable Document Automation (Retries, Idempotency, and Audits)](https://lidvizion.ai/blog/step-functions-patterns-for-reliable-document-automation-on-aws/): Document automation is a long running workflow: ingest, OCR, validate, route, and generate outputs. AWS Step Functions is a strong orchestration
- [MongoDB Atlas Vector Search RAG for Document Workflows on AWS (A Practical Blueprint)](https://lidvizion.ai/blog/mongodb-atlas-vector-search-rag-for-document-workflows-on-aws/): Retrieval augmented generation (RAG) is most valuable when it is attached to a real workflow: intake, search, extraction, and decision support. This post
- [AWS Textract vs Open Source OCR for Production Doc AI (Accuracy, Cost, and Architecture)](https://lidvizion.ai/blog/aws-textract-vs-open-source-ocr-for-production-doc-ai/): Who this is for If you are building document automation that has to work in production, not just in a notebook, this guide compares AWS Textract with l
Bring the messy version
## One workflow. A better way to run it.
Show us the tools, the handoffs, and the part that keeps slowing your team down.
[Let’s map your workflow](https://lidvizion.ai/contact/) · [Read our approach](https://lidvizion.ai/approach/)