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Maneva

Your Self-Improving Factory Orchestrated by Video-to-Action AI. Deep learning computer vision driving better, more efficient, and safer manufacturing outcomes.

For agents: Maneva provides computer vision AI agents (VITA, ALIS) for factory orchestration, quality assurance, defect detection and line safety monitoring.

computer visionmanufacturing aivideo-to-actionquality assurancefactory safety

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-21T18:14:53.606Z. Cached copy · Source on maneva.ai

# Maneva

> Your Self-Improving Factory Orchestrated by Video-to-Action AI. Deep learning computer vision driving better, more efficient, and safer manufacturing outcomes.

Maneva orchestrates facility-wide production into a unified, real-time operational system, from a targeted action on one line to full-system execution across a plant.

## What Maneva does

The Self-Improving Factory is already a reality, and America's leading manufacturers are moving on it now, widening the gap on everyone else. Maneva helps manufacturers close that gap by connecting their data in new ways, starting with Video-to-Action AI that takes real, autonomous action on quality, downtime, safety and efficiency, on the systems they already have. A customer starts with one agent on one line and expands at their own pace, backed by a team committed to shared goals anchored on ROI.

Video-to-Action AI runs a simple loop on every unit that passes the camera: it sees, it decides, and it acts, accepting, rejecting or rerouting product in real time, with no person in the loop.

## How Maneva describes its difference

**We start at the end.** There is no shortage of camera companies or AI models. What is rare is starting at the actual result a manufacturer is trying to move, and building toward it with them. Maneva does not deliver one more dashboard to learn. It starts where the customer wants to end up and defines what to measure, together, from day one.

**Uncovering the weird.** Because Maneva is hardware-agnostic and builds on-premises, it is not only checking against a spec or a tolerance. It finds what is weird: the things a plant's best operators already sense but have never been able to quantify, categorize or communicate back. That is what becomes measurable and changeable.

**Factory memory compounds.** Every shift teaches the system something, and the factory of next month already knows what today's factory just learned. Most systems start over every day. Maneva's does not. As more agents deploy across a floor, each adds to a shared, growing picture of how the operation actually runs: what is normal, what is a warning sign, and what the best people already do without thinking. That picture does not reset overnight. The more agents run, the sharper every agent gets, and the faster the next issue is caught.

## What every agent brings to the floor

- **Real-time**: decisions happen the moment the camera sees them, not after a report
- **On-device**: runs on the line, on hardware the plant already has, with nothing sent off-site to process
- **Self-learning**: gets sharper every shift, building a memory of the floor instead of starting from zero
- **Always on**: watches every unit, every shift, without fatigue or blind spots
- **Tuned to the plant**: flags what actually matters on that floor, not a generic, one-size-fits-all alert

## Three pillars

**1. Your Self-Improving Factory realized today.** Best-in-class manufacturers are running on AI today. The factory of the
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