Shoreline AI provides an out-of-the-box Asset Performance Management (APM) Platform for industrial machines, utilizing Predictive and Generative AI. It is a purpose-built software with integrated hardware and a SaaS platform.
Shoreline AI's mission is to provide cost-effective, infinitely scalable solutions that enable customers to achieve optimal asset reliability and operating performance.
Shoreline AI focused on Energy and Manufacturing verticals with a marquee customer portfolio in these areas. Specific industries include Oil & Gas, Power Generation, Infrastructure, Appliances, Chemicals & Plastics, Pulp & Paper, Pharma, Building & Construction Materials, Food Processing, Auto, and Steel. They also target Data Center Cooling.
Shoreline AI addresses the challenge that 90% of machines are still inspected manually, and current APM solutions are often too complex, expensive, and difficult to set up and use, thus addressing less than 10% of highly critical assets. This leads to lower profits and productivity due to limited data and analysis, increased unplanned downtime, higher maintenance costs, longer repair times, lost production and revenues, and reduced equipment efficiency and lifetime.
Shoreline APM is an out-of-the-box SaaS Platform for 24x7 Machine Health Monitoring and Predictive Maintenance. It is an affordable and scalable platform that delivers immediate ROI for all assets.
The platform aims to improve asset reliability by reducing maintenance costs by ~30-50% and eliminating unplanned downtime. It also optimizes production and operations by extending asset life by 20-40% and improving efficiency by 5-15%. Additionally, it helps reduce the carbon footprint by monitoring and reducing energy waste and detecting methane emissions
Key features include 30,000+ pre-built Asset Physics Models, 100% plug-n-play self-deployment by non-experts, AI/ML powered pre-built Physics models for machine-specific predictive analytics, 10X lower cost than alternate solutions, and fast time to value. It offers direct sensor-to-cloud connectivity without gateways, power, or cables. The platform includes an analytics engine with Predictive & Generative AI, dashboards & alarms, a Physics Models Asset Library, and integration with CMMS & 3rd Party Apps.
The platform can ingest data from Shoreline Smart Sensors, Open APIs, Connectors for SCADA and PLC systems, Historians like OSI Pi and IP21, and optional 3rd Party Sensor Data.
The Shoreline Portal offers complete visibility of asset health 24x7 through Machine Health Dashboards, Alarm Management, Workflow, and AI Analytics & Trends.
The Asset Physics Models Library contains 30,000 components and fully automates asset configuration & settings without expert help. It auto-generates and tracks machine baselines and accelerates AI/ML model training, eliminating the need for historical data.
The platform supports a wide range of rotating and stationary assets across various industries. This includes electric motors, fluid power systems, couplings, belts, chains, gears, drivers, intermediate drives like blowers, compressors, and fans, rolling mills, mixers, pumps, heat exchangers, furnaces, reactors, storage tanks, and dynamic assets. It also supports Balance of Plant equipment in power generation like fans, chillers, blowers, pumps, cranes, and conveyors.
The platform boasts a "Plug and Play Setup" and is 100% self-installed by non-experts, fully cloud-managed and provisioned. Online configuration and installation take less than 15 minutes per machine. It requires no new IT infrastructure at the site.
You can see the installation video here
No, the platform is designed for non-expert users, and it automates asset configuration and baseline generation. The platform includes advanced analytics tools such as vibration analysis, anomaly configurator and workflow for experts to do their own root cause analysis if they desire. The platform subscription includes expert analysts' concierge services.
The platform offers an Open API and connectors for integrating with SCADA, PLC, Historians (OSI Pi, IP21, etc.), and CMMS & 3rd Party Apps. It can ingest and visualize data from all sources.
No, the platform's proprietary Physics Models Library automatically generates and tracks machine baselines and accelerates AI/ML model training, eliminating the need for historical data.
The Shoreline Portal offers complete visibility of asset health 24x7 through Machine Health Dashboards, Alarm Management, Workflow, and AI Analytics & Trends.
70% of Shoreline customers are on primarily or 100% on Azure cloud. Shoreline solution DOES NOT run in the customer's AWS/Azure cloud account. We do not require the customer to even have an AWS account. Our multi-tenant SaaS application runs in Shoreline's AWS account and we pay for all cloud consumption to AWS and not our customers.
Nothing, Shoreline’s APM SaaS subscription includes everything needed to complete the setup. This includes :
Ease and simplicity is key to Shoreline’s onboarding process. Typically it takes 3-4 weeks to complete the onboarding setup i.e. installing the sensors, baselining the assets and visualizing data in the cloud and mobile app.
The sensors may be installed while the machine is in operation provided the installer is safe and the machine isn't vibrating so much that the puck is constantly moving around while being glued.
The acrylic adhesive curing is accelerated by heat. We apply the activator to the surface and to the puck, and put the adhesive on the puck then press onto the machine.
Management (APM) and Predictive Maintenance (PDM) market? Shoreline AI competes with Legacy APM/PDM Vendors and other cloud-based vendors.
Legacy solutions are typically:
Shoreline AI is significantly more affordable. It offers a 10X lower cost than alternate solutions and is priced at a 10x reduction to legacy solutions. The cost is approximately 90% lower than existing solutions. Shoreline AI operates on a 100% SaaS subscription model with Zero Capex and no new IT infrastructure required.
Shoreline AI offers high ease of use and a fast time-to-value. The system is 100% self-installed by non-experts within minutes (setup in 5-10 minutes per sensor). It is fully cloud-managed and cloud-provisioned. There is no new IT infrastructure, no wires, no conduits, no gateways, and no external power required.
Similar to legacy systems, many previous generation cloud-based vendors require gateways. They often require experts for setup and have a long time-to-value. Some are limited to machines in light manufacturing use cases, and their operations can be capital intensive. Vendors like Augury and AssetWatch failed to meet Oil & Gas specifications and were rejected by major O&G operators, focusing instead on light industrial manufacturing. They often lack a physics model asset library, leading to more manual work and longer time to value.
Shoreline AI's differentiation includes:
Shoreline AI utilizes a 100% SaaS subscription model with Zero Capex. This is a departure from legacy models which often require significant upfront investment in hardware, software, and services.
Shoreline AI is purpose-built for Energy & Manufacturing verticals, including Oil & Gas, Power Generation, Infrastructure, Chemicals, Plastics, Pulp & Paper, Pharma, Food Processing, Auto, Steel, and Data Center Cooling. Unlike some previous generation cloud vendors who focus on light industrial manufacturing, Shoreline AI is suitable for process manufacturing industries like Oil & Gas and Chemicals.
Shoreline AI ensures data is owned by the customer and provides the ability to auto export high resolution data and analytics to 3rd party Apps. It offers Open API access and API integrations with existing plant software like CMMS, Historians (OSI Pi, IP21), SCADA, ERP, EAM, and Data lakes. Legacy systems often have data integration issues.
Shoreline AI utilizes a Smart AI Sensor which is a 6-in-1 device. It includes an ultra-high resolution triaxial accelerometer, two acoustic microphones (sound & ultrasound), two temperature sensors (surface & ambient), and humidity. It also has external input ports for ingesting data from 3rd party sensors. The sensors have built-in edge analytics for anomaly detection and send tagged and raw data to the cloud. They feature multiple long-range wireless connections, including long-range cellular radio (LTE-m & NB-IoT) up to ~25 miles, BLE, and WiFi. They have a 5-year battery life (field replaceable) and are IP67 rated and Class 1 Div 2 certified for hazardous locations. Legacy sensors often only measure vibration and temperature, lack edge analytics, use older technology like WirelessHART, and require external power.
Shoreline AI utilizes a combination of pre-built machine Physics Models, Predictive and Generative AI. A core component is their proprietary 30,000+ pre-built Physics Models which kick start and accelerate AI/ML learning and deliver fast time-to-value within the first few weeks. These hybrid Physics + AI/ML models allow for highly accurate predictions without historical data. Shoreline provides advanced diagnostics and predictive maintenance action recommendations. Their Generative AI, including a conversational bot (Virtual Assistant) and Co-pilot, analyzes both structured and unstructured data (like CMMS history, analyst notes, and equipment manuals) to provide richer insights, accurate diagnoses, and specific repair prescriptions. Legacy and some previous generation cloud systems often lack advanced AI/ML and struggle with generating highly specific prescriptions or leveraging unstructured data.
Shoreline AI offers 24x7 AI/ML-driven leak detection. It can instantly detect large leaks from specific assets like slop tanks, compressors, and PRVs with pinpoint accuracy. This provides immediate alerts, unlike waiting for monthly aerial surveys or manual inspections. It delivers AVO-like observations 24x7 using multi-sensory data (Audio, Vibration, Temperature) and process signals. Shoreline addresses the limitations of existing fence-line solutions by providing pinpoint source identification (whereas fence-line cannot pinpoint exact location), being highly scalable, and having a much lower cost. The sensors are self-installed, require no wires, gateways, or external power.
The platform utilizes an industry-first, fully-automated, smart-sensing, cloud-based platform with edge analytics and physics models in the Shoreline Smart Sensor. It also uses AI/ML predictive analytics.
It remotely monitors and manages industrial assets 24x7 without the need for domain experts or new IT infrastructure
You can see the 2 min video here.
It can ingest data not only from Shoreline sensors but also from 3rd party sensors and Process Data for deeper analysis.
AI/ML-based models accurately detect real-time leaks based on Audio, Vibration, Temperature signatures, and process signals. It also offers predictive analytics and a diagnostics suite.
It is 100% self-installed by non-experts in minutes. It requires no custom integration or software.
It can eliminate downtime, improve efficiency, reduce costs, and extend asset life.
No, it offers highly accurate predictions without historical data.
This kit includes 50 smart wireless sensors, sensor provisioning & virtual support, cloud portal access, end-customer training, virtual support for questions, a 12-month platform subscription, and anomaly detection using Physics and ML Models. It also includes customer training & support on alerts/alarms/diagnosis questions.
It can monitor compressors, blowers, pumps, fans, conveyors, casters, grinders, mixers, gearboxes, belts, chains, couplings, motors, engines, and heat exchangers.
It offers cellular (LTE Cat M1, Cat NB2 & EGPRS), Bluetooth® 5.1, and IEEE 802.15.4-2006 BLE/BLE LR and WiFi in new versions.
It has a battery life of up to 5 years and an optional 9-26V external industrial power source.
It is IP67 rated and has Class 1 Div 2 certifications.
It includes a MEMS Triaxial accelerometer, MEMS digital microphones (2), and Environmental Temperature/Humidity Sensor/Surface Temperature Sensor.
Yes, it has IO ports to ingest data from a large variety of external industrial sensors, with one analog and one digital sensor per port supported (4-20 mA or 0-10V). Customers can see data and analytics from both built-in and external sensors on a single pane of glass in their cloud portal or mobile app.
Sensors can operate from -40°C to 85°C (-40°F to 185°F)
Sensors are typically fixed using an industrial grade adhesive supplied with the installation kit. Magnetic mount option is available at additional cost, but not required.
You can see the installation video here.
Shoreline AI sensors employ a multi radio solution. This includes the use of Cellular IoT, LTE-m, and Bluetooth. A core aspect of their approach is built-in long range global cellular connectivity in each sensor.
Shoreline sensors use long-range Cellular Technology, specifically LTE-M (also known as CAT-M) and NB-IoT. The sensors are equipped with a Qualcomm 9205 (BG-95) Cellular Module which integrates three modems: LTE-M, NB-IoT, and GSM. This module provides a Full IP Stack & Security and supports global frequency bands for Cat M1 (LTE-M) and Cat NB2 (NB-IoT).
The sources highlight several benefits of Shoreline's chosen approach using Cellular IoT, LTE-M:
The sources provide comparative details, primarily regarding range and infrastructure:
Yes, significantly. With built-in long range global cellular connectivity in each sensor and two SIM cards pre-activated for global coverage, the customer does not need to contract with carriers. This contrasts with scenarios where customers might need to set up and manage their own mesh wireless networks. The inherent global coverage and pre-activated SIMs streamline deployment and operation from the customer's perspective.
Shoreline AI is integrating Generative AI alongside its Predictive AI within its Asset Performance Management (APM) platform. Shoreline AI is the first asset performance management company to seamlessly integrate GenAI into the platform to deliver tangible value to its end users.
The goal is to deliver highly accurate and precise insights, prescribe machine-specific repairs, and eventually act as an advisory to improve plant-wide operational efficiency and productivity. Shoreline AI aims for its platform to go beyond providing insights for predictive maintenance programs and become a reliable advisor.
Shoreline AI is developing a GenAI-based virtual assistant and an APM Copilot. They are also working on GenAI-based advanced analytics modules and a Shoreline Prescriptive LLM (Virtual Expert). This will not only offer better analytics to customers but also enable a highly capital efficient innovation engine for Shoreline.
Yes, Shoreline AI is developing a proprietary Machine LLM that is highly specialized for the industrial asset performance management use case. This is referred to as the Shoreline Prescriptive LLM.
This LLM will be trained by using 30,000 plus physics models, vibration, temperature, sound, ultrasound and terabytes of customer’s machine health data from field deployments, machine repair histories, alarms, customer event reports, end user and analyst notes in Shoreline portal and from Historians, CMMS systems, and equipment manuals.
Shoreline AI's GenAI-based virtual assistant and APM Copilot are integrated with the platform and use different foundation models in the AWS Bedrock .
The Shoreline AI Virtual Assistant is a GenAI-based assistant integrated with Shoreline's mobile app as well as the cloud platform. It allows users to converse with the APM platform to get insights. Users can ask about the machine health of all assets, see a dashboard of healthy and critical assets, and list all powertrains being monitored.
Users can ask to deep dive into specific assets, find out if there are any critical alarms, and if they click on an alarm, they can access the alarms detail page for causal analysis, notes, images, and diagnosis. The assistant can also retrieve repair history of specific assets from the CMMS system and look for equipment manuals stored on S3. Plant managers can also ask productivity-related queries, such as the average time to repair for specific alarm types or list alarms fixed in a given period.
The Shoreline APM's copilot uses AWS Bedrock LLM to replicate the workflow of an expert vibration analyst to observe, interpret, and analyze alarm events detected and then prescribe repair actions. It collects relevant data after detecting an event, including powertrain and sensor configuration and images. It generates key parameter trends and FFT charts for analysis and then sends this data to the Bedrock GenAI model. The copilot then provides a detailed report on the anomaly, including identification of significant events, harmonic analysis, detailed diagnosis, and recommendations with specific details on time to failure and timelines to initiate repairs.
GenAI, particularly the Shoreline Prescriptive LLM, aims to provide auto-elimination of false positives, accurate remaining life/time-to-failure predictions, specific prescriptions based on equipment manuals, and process advisory for OEE and Productivity. It can analyze hybrid structured and unstructured data like work order repair history, Predictive AI/ML results, and physics models to generate richer prescriptions. GenAI can analyze data like an expert, combining machine type, repair history, and sensor data for higher accuracy predictions and prescriptions.
Yes, the Shoreline Virtual Assistant can be used for dynamic report generation and users can drill down for additional information through conversational communication.
GenAI aims to reduce the involvement of vibration experts, provide improved reporting capabilities, deliver more accurate and precise insights, offer specific repair instructions, and ultimately improve plant-wide operational efficiency and productivity. It can also help in faster and easier access to information like repair history and equipment manuals.
horeline AI plans to complete the development of GenAI-based Virtual Machine Expert (VME) which will be expert on each and every machine and (non expert) end users can directly have conversation with this Shoreline VME. The VME driven by Shoreline’s Proprietary LLM Agentic models will be highly prescriptive, conversational and a GoTo expert advisor for end users. This VME approach can be applied to many other classes of assets and industrial use cases beyond Shoreline’s predictive maintenance use case.
It detects large leaks faster with a goal of keeping gas in the system, thus immediately improving customers’ top and bottom line. The platform offers 24x7 AI/ML-driven leak detection for methane and VOCs from equipment like storage tanks, pressure relief valves, and compressors. It provides real-time online alerts with pinpoint accuracy and is designed for rapid, scalable deployment without expert help at a lower cost than fenceline solutions. It utilizes the built-in acoustic and five other sensors in their smart sensors to detect leaks.
Existing solutions often struggle with pinpointing the exact location and source of leaks, detecting leaks from above-ground assets, large variance in leak quantification with high false positive rates, and being expensive and difficult to scale. Shoreline AI aims to overcome these limitations with its sensor-based, AI/ML-powered approach.
Shoreline AI has developed a patent-pending AI/ML-based multi-sensory solution to instantly detect large leaks from "bad-actors" like slop tanks, compressors, and PRVs with pinpoint accuracy. It provides AVO-like observations 24x7, alerting operators immediately about major leaks.
Shoreline AI's 24x7 Emission Monitoring platform addresses the limitations of existing continuous fence-line monitoring solutions.
Shoreline AI offers 24x7 AVO-like methane/VOC leak detection. It monitors for large leaks remotely and safely.
The starter kit includes either 10 (SKM10) or 25 (SKM25) smart wireless sensors, sensor provisioning with online support, cloud portal access, end-customer training for cloud platform usage, online support for questions, a platform subscription period, and leakage detection using AI/ML models. The SKM10 monitors 5-10 slop tanks or PRVs, while the SKM25 monitors 15-20 slop tanks or 25 PRVs. Customer training and support on alerts/alarms/diagnosis questions are also included.
The solution can be set up within minutes and is 100% self-installed by non-experts.
The solution can monitor above-ground slop tanks, compressors, and PRVs.
No, the solution requires no new IT infrastructure, wires, conduits, or gateways.
Yes, the solution is highly scalable and affordable for critical and balance of plant leaking equipment. It uses a 100% inclusive SaaS subscription model.
Onboarding includes the Smart Wireless Sensor, APM Cloud Portal & Mobile App, and everything else needed to start within the first 4 weeks.
The Smart Sensor has 6 sensors built-in, IO ports to ingest data from external sensors, edge AI/ML models to "listen" to leaks, two wireless radios & 2 SIM cards built-in, and is IP67 and Class 1 Div 2 certified. It also has a 5-year battery life with a replaceable battery and an optional mini-solar panel.
Features include equipment-specific leak detection models, leak trends, instant reporting of leaks, duration of leaks, emission dashboards, and an analytics & diagnostic suite. It also provides alarms, alerts, and a rules engine.
Shoreline AI, 1671 Dell Ave, Suite 208, Campbell, CA 95008
info@shorelineai.us
Copyright 2025 Shoreline AI All Rights Reserved.
