Lifagora — The lifecycle intelligence layer for industrial operations

The problem

Factories scrap good parts to be safe.

When an inspection is uncertain, the safe decision is to reject. Nobody gets fired for scrapping a good part — but every false reject is material, machine time and margin, thrown away. The data exists upstream — the inspection decision rarely sees the whole story.

5–15%

good parts falsely rejected on traditional rule-based inspection

under 2%

achievable when the decision sees the full context — without missing real defects

context carried from one stage to the next today

Industry benchmarks (AOI / vision inspection). Your line, your numbers — we prove the figure that matters to you.

False rejects ↓·Escapes unchanged

That’s the only number we ask to be judged on — fewer good parts scrapped, without letting a real defect through. Measured on your line, in your own numbers.

How it works

Intelligence at the decision point.

Lifagora sits over the data a plant already produces. No new sensors, no rip-and-replace.

01 · MODEL

The lifecycle is the unit

Each part, asset and process gets a lifecycle: its stages, its events, its history. Context stops dying at the end of a shift.

02 · POINT

Agents plug into decision points

Where a decision is made — inspect, pass, scrap — an agent reads the full lifecycle and returns a verdict with confidence. A human confirms.

03 · LOOP

Every decision feeds the next

Confirmed decisions become history. The next decision on the next part is made with more context than the last.

Scale

One data access. Many agents.

The hard part is the access — the plumbing into plant data, the trust, the security review. You do it once. Every agent after that rides on it.

false reject

Inspection. Saves good parts that would be scrapped on a borderline measurement.

process drift

Machining. Flags a process sliding out of tolerance before it produces scrap.

tool wear

Maintenance. Predicts the tool change from the lifecycle, not the calendar.

The cost is paid once. One integration — many agents. Each new agent adds value without a new integration project.

Where we fit

Not another inspector. A layer above them.

We don’t replace the tools on your floor. We turn what they see into better decisions.

Every decision becomes memory. The layer learns and carries insight across operations and over time — not one operation, not one moment.

Lifagora— the lifecycle intelligence layer for industrial operations

sits on top of

vision / AOI

RFID / sensors

MES / QMS

any data source

Built on the floor, not in a lab

Lifagora is new. The work behind it isn’t.

For nearly two decades we’ve built industrial software on real production floors — and for over a decade, lifecycle traceability specifically. We picked it up early, working with large manufacturers just as traceability was becoming a discipline: connecting sensors, cameras and enterprise systems to follow parts and assets through their operational life.

That work taught us one thing: factories already generate enormous context. The hard part is getting the right context to the moment a decision is made.

The context was already there. The reasoning wasn’t.

Lifagora is the next step.

Trust

Reject less. Miss nothing.

A quality plant will never trade escapes for savings — and it shouldn't have to. The agent only ever recommends; a human confirms every decision.

false rejects escape rate

Own the lifecycle. Rent the brains.

We're talking to quality and production teams about one thing: how false rejects actually happen on a real line. No pitch — we want to understand the floor before we build for it.

Thanks — we'll come back to you with questions, not a pitch.

We're in discovery. We're learning how this works on real lines before we build for them.

Not the right time? Get a note when we launch · or write to hello@lifagora.com