Industrial AI is having a moment.
We've had a decade.
Founded 2015. More than a hundred projects delivered. We have walked the whole road with our customers — from prying data out of PLCs and historians, to their first machine-learning models, to thousands of computes running in parallel in the cloud, to agents reasoning over the whole plant. That road is why our projects work.
WHY CUSTOMERS CHOOSE ARUNDO
The return is high. The investment is low.
Three things keep it that way.
Disciplined ROI, dedicated experts and proven technology — delivered the way your operation already runs.
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01
Our approach
Value before build.
- The use case is chosen with you, tied to a KPI you already report.
- Validated before anything is built: can the problem be modelled, and does your data carry a solution worth the effort?
- Only then a production build, scoped to the features, models and integrations the outcome needs.
Evidence of value before investment.
How we work -
02
Our people
Deep expertise, first principles.
- Domain experts and data scientists — all STEM PhDs — dedicated to your team for the engagement.
- We start from the physics, the engineering and the operating reality, then pick the method that fits: a model, a prediction, a tree of calculations.
- Time on site with operators, learning how they work and what they need.
Solutions operators adopt.
The people who've seen it all -
03
Our technology
One foundation, fitted to each site.
- Arundo Foundation: ten years in production. ISO/IEC 27001:2022 certified.
- Reusable components speed the build; the tailoring is part of the build, not a project of its own.
- Your data kept apart — per-organisation vaults, your own database where residency requires it — and an experience fitted to each site's regulations, systems and control-room workflows.
Focused build on proven technology.
01 · 02Keeps the return high.
03Keeps the investment low.
>10× ROI within 12 months, typical. All three come from the same place: ten years on the road below.
THE LONG ROAD · 2015 → NOW
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01
Getting the data out.
Before anything could be intelligent, the data had to exist: PLCs, historians, field protocols, edge boxes on vessels and rigs beyond any network's reach. We built that plumbing when it was unglamorous — and learned every way industrial data lies.
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02
The first models.
Condition monitoring on pumps, fouling on exchangers, physics fused with machine learning — and the harder lesson underneath: a model is worthless until an operator stakes a decision on it.
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03
Scale that pays for itself.
From one model to thousands of computations running in parallel in the cloud — orchestration engineered for speed and cost, because plant-wide reasoning is only real if it's affordable to run continuously.
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04
One model of the whole plant.
The Domain: assets, sensors, models, and documents in one connected graph — the step that separates islands of analytics from an operation that can reason about itself.
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05
And now, agents.
LLMs and AI crews arrived to find our customers ready: a decade of data discipline, a graph to ground them, and an open MCP door to whichever AI the world builds next.
Every AI company can demo.
Ten years in production is harder to fake.
Most industrial AI projects fail.
Ours don't.
Not because we're lucky — because we've already made the mistakes the industry is about to make, years ago, and built the method that avoids them.
We wrote the manual.
When "autonomous operations" needed a definition, we wrote it — The Six Levels of Autonomous Plant Operations (Arundo 2026) — and placed our own customers on it honestly. That is what leading expert means here: not the loudest claim, but authorship of the standard the industry will be measured against. Level 2 runs at our customers today; Level 3 is being built with them; the road to Level 5 is drawn.
The six levelsThe people who've seen it all.
Industrial engineers, data scientists, and software builders who have spent ten years where industrial AI actually gets hard: sensors that lie, historians with holes, unit conversions that cost millions, alarms nobody trusts anymore, and integrations abandoned by vendors long gone. That scar tissue is the product. It's why we prototype with first-principle physics, build software that survives operations, and put your operators in the room from day one.
The method is problem-first: one solved problem in weeks, then the next, the platform accruing underneath.
How we workWhat we don't do.
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01
No year-long platform projects.
Value in weeks or we have failed.
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02
No dashboards as deliverables.
A screen that displays a problem is not a solution to it.
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03
No solution we can't tie to a number.
The ROI target is agreed before anything is built.
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04
No walled garden.
Your plant works with the AI your teams already trust — Claude, ChatGPT, any MCP client.
One word: autonomous.
Everything above serves a single destination — the plant that runs itself, with your people setting the objectives. We are the autonomous operations company, and we've spent a decade earning the right to say so.
ISO 27001 CERTIFIEDGDPR COMPLIANTSTANFORD STARTXMIT STEX25FOUNDED 2015