About EPOVIS

For everyone accountable for quality in the field.

EPOVIS is mobile AI visual inspection software for large assets and distributed sites, connecting iOS field capture, AI-assisted analysis and Web task management.

Why we are building EPOVIS

Quality context is often lost in motion, even when the issue was seen.

Across large assets, images sit in camera rolls, standards stay in documents and follow-up lives in chat. After a shift change, teams must reconstruct where it happened, what was seen and who owns the next step.

Larger objects and distributed points amplify that break. One detection is not an answer. Discovery, judgment, resolution and reinspection should all return to the same evidence.

We want people who know the field to feel more certain—not software that merely looks more intelligent.

The EPOVIS team

What we believe

AI should extend professional judgment, not bypass it.

Models can organize evidence, compare standards and surface signals. Qualifications, field judgment and organizational accountability remain human. Smarter systems need clearer boundaries.

Capture is not acceptance
Repair is not independent reinspection
A handover draft does not transfer responsibility

What we are building

One work chain from the field to delivery, always grounded in evidence.

Each endpoint does what it is best at. This is the collaboration model, not a disclosure of our internal architecture.

iOS · Field execution

Capture location and evidence beside the asset.

3D point and viewpoint guidance supports capture, field judgment, repair records and independent reinspection.

Field facts begin here

Agents + models · Organized analysis

Bring evidence, standards and context together.

Within approved scope, AI assists analysis, follows open work and organizes conclusions while returning uncertainty to qualified people.

Assistance, not transferred accountability

Web · Coordinated management

See the whole operation and return to source evidence.

Review data, track progress, manage projects, prepare shift handovers and produce verifiable deliverables.

Manage process and outcomes

Where we start

Start where broken context is hardest to hide.

Large targets and distributed sites magnify problems in location, capture, coordination and handover. Solving them well creates a foundation for more field scenarios.

Large asset

Humanoid robots

Complex structures, many points and strict viewpoints. A single photo cannot prove that an inspection is complete.

Connect every point, viewpoint and evidence item

Distributed site

Power-plant piping

Long routes, broad areas and multiple shifts. Progress and unresolved work should not disappear during handover.

Keep areas, assets, issues and handovers continuous

How we work

Put our commitments into product decisions.

We do not measure progress by feature count, but by whether field work becomes clearer, more traceable and more accountable.

01
Go to the field
Understand the object, route, roles and constraints before proposing technology.
02
Evidence first
Every conclusion should return to a location, image, standard and process.
03
Clear accountability
AI assists; people and organizations retain judgment, confirmation and delivery.

Bring one real problem. Let us talk.

Tell us what you inspect and where context gets lost. We will prepare a substantive conversation around your field reality.