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PRANINNOVATIONSProduction Specialists

Insights

Guides written from measured work

No thought leadership. Numbers, methods, and the things that didn't work.

report10 min read

What It Cost to Serve One Million Citation-First RAG Requests on GCP

Measured Cloud Run and Cloud SQL retrieval latency, failures and cost across one million public-edge requests—with the LLM boundary made explicit.

report9 min read

Object Detection Resolution vs Latency: What Our 5,000-Image Test Found

Measured YOLO11 accuracy and p95 latency at 320, 480 and 640 pixels on Apple M4 Pro, plus Cloud Run L4 deployment evidence.

guide9 min read

Why Vision Projects Fail on the Floor, Not in the Model

Six ways industrial vision deployments fail after a successful proof of concept — lighting, mounting, class definitions, changeovers, integration and ownership — and how to catch each one during the survey.

guide8 min read

Edge or Cloud: How to Decide Where Vision Should Run

A decision framework for where inference belongs — latency budget, connectivity, data-movement restrictions, camera count and maintenance burden — with the questions that settle it.

guide7 min read

How Many Images Do You Actually Need to Train a Defect Model?

Why the honest answer is a range, what drives it, and how to build a usable dataset when the process rarely produces the defect you need to catch.

guide8 min read

Getting Vision Results Into a PLC Without Upsetting Controls

How to integrate a vision system with plant control equipment: interface design, network segmentation, fail-safe behaviour and the conversations to have with the controls team first.

guide7 min read

Noticing a Vision System Has Got Worse, Before Quality Does

Deployed vision systems decay quietly as products, lighting and cameras change. What to monitor, how to sample ground truth affordably, and when retraining is actually warranted.

article6 min read

What Actually Happens During a Vision Site Survey

The two days that determine whether a vision project succeeds: what we measure, what we photograph, who we talk to, and the findings that most often change the plan.

Start with a call, then a costed plan

Thirty minutes on the problem, the site and the constraints. If it looks like a fit, the next step is a four-week AI Pilot at a fixed price, with acceptance criteria signed before any code is written.