ABOUT SHORELINE AI
More than 85% of energy assets are still unmonitored. Conventional online condition monitoring reaches only the most critical machines — under 10% of an operator’s installed base — because it is complex, expensive and difficult to set up. Everything else is the long tail.
Manual inspections and reactive maintenance result in
Increased unplanned downtime
Higher maintenance costs
Longer time to repairs
Lost production and revenues
Reduced equipment efficiency and lifetime
That is not a technology failure. It is an economics failure. Traditional asset performance management was built around a site survey, field cabling, a gateway, an integration project, and a reliability engineer to configure and interpret it. For the highest-criticality machines, that cost is worth absorbing. Applied to the mid-tier compression, engines, motors, pumps, fans and artificial lift that make up the rest of an operator’s asset base, the arithmetic never worked.
So those machines are managed by monthly rounds, calendar intervals, or failure. Shoreline AI was founded to change the arithmetic.
OUR VISION
A world where every machine critical energy infrastructure depends on is monitored, understood, and maintained before it fails — not only the small fraction that could justify the cost of monitoring it.
OUR MISSION
To drive asset performance for every asset in the energy value chain, by making Physics Informed AI simple enough that a field mechanic can deploy it in thirty minutes and accurate enough that a reliability engineer trusts what it tells them.
WHAT WE BUILT
A complete asset performance management solution in which the hardware and the software are designed as one system. Smart sensors are self-installed by non-experts, connect directly to the cloud, and auto-provision the right models the moment an asset is identified. The output is a precise diagnosis with root cause, delivered into the systems your teams already use.
It lets Oil & Gas and power generation operators monitor machine health remotely, improve asset performance, efficiency and asset lifetime, and increase uptime and production — with a payback period of less than three months.
Proprietary smart sensors
Six sensing functions in one device, edge analytics on board, direct-to-cloud cellular. No gateways, no cabling, no power drops.
A vast library of Physical AI models
More than 30,000 pre-built models covering the rotating, reciprocating and stationary assets energy operations depend on.
Predictive and agentic AI
Physics-informed detection rather than pattern matching, so the platform is useful from the first week rather than the second year.
Actionable insight, not anomaly scores
A named failure mode, its location on the machine, a severity, and deep root cause analysis a planner can act on.
Cloud portal and mobile apps
Dashboards, alarms and workflow in the browser, with iOS and Android apps for the people standing next to the machine.
Open APIs into your enterprise systems
Two-way exchange with CMMS, EAM, historian and SCADA, so findings become work orders without anyone rekeying them.
No site survey, no contractor, no hazardous-area electrical permit, no vendor engineer. A mechanic with a phone and a mounting kit. This is what determines whether a programme reaches forty assets or four hundred.
Commercially deployed across upstream, midstream, downstream and power generation with major North American operators — covering reciprocating compressors and engines alongside motors, pumps, fans and blowers, for both critical and balance-of-plant assets.
Because the models derive from how each machine is built rather than from its operating history, they produce diagnoses without a training period and without needing examples of the failure you are trying to prevent.
Software, cloud & hardware
Industrial operations and reliability
Shoreline was founded on a specific bet: that this problem needed consumer-scale software engineering and deep industrial machine modelling in the same room, and that most attempts had only one of the two.
Our founders have run P&L and business units across IoT, wireless networking, software and semiconductors, and have designed the AI, cloud, embedded and robotics platforms behind more than 100 million connected devices.
Beside them sit reliability and customer-success leaders with 25 years inside oil and gas, power generation, petrochemical and manufacturing plants. The installation experience is designed like a consumer device; the diagnostics are built on decades of rotating and reciprocating machinery expertise.
Software, cloud & hardware
Industrial operations and reliability
Apple
Bently Nevada
Honeywell
Intel
GE
Marvell
Whirlpool
AMD
Uptime AI
Shoreline was founded on a specific bet: that this problem needed consumer-scale software engineering and deep industrial machine modelling in the same room, and that most attempts had only one of the two.
Our founders have run P&L and business units across IoT, wireless networking, software and semiconductors, and have designed the AI, cloud, embedded and robotics platforms behind more than 100 million connected devices.
Beside them sit reliability and customer-success leaders with 25 years inside oil and gas, power generation, petrochemical and manufacturing plants. The installation experience is designed like a consumer device; the diagnostics are built on decades of rotating and reciprocating machinery expertise.
Bring a compressor, engine or pump you already have questions about. A Shoreline reliability analyst will walk you through what the model sees and why.
Shoreline AI, 1671 Dell Ave, Suite 208, Campbell, CA 95008
info@shorelineai.us
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