FAQs

Inline spectral sensors utilize spectroscopy to analyze material interactions with light at various wavelengths (UV, visible, and infrared) in real-time. They can distinguish fluids in a pipe by their unique spectral signatures to determine product type, concentration, contaminants, and quality.

Our sensors eliminate the need to stop production or take manual samples. It's widely used in food, beverage, and liquid manufacturing for process monitoring and quality control.

Conductivity probes only detect ions in solution and are useful during chemical steps. Laminar sensors analyze how light interacts with materials on a molecular level, detecting changes that conductivity meters miss entirely. Get sub-second insights on  rinse water quality, product concentration, organic materials, and transitions between different fluids. This gives visibility into rinse optimization and changeover detection that conductivity alone cannot provide.

Turbidity meters measure cloudiness and can only tell you when fluid reaches a "clear" state. Different products with the same turbidity reading look identical to a turbidity meter. Laminar's spectroscopy-based sensors distinguish between different products, measure concentration levels, and detect the exact transition between products. This capability enables changeover optimization and product loss reduction that turbidity meters cannot support.

Yes. Every product has a unique spectral fingerprint based on its chemical composition. Using PLC data, Laminar maps each product's spectra to its SKU. Get precise identification even when multiple products run through the same process line.

Yes. Laminar sensors analyze materials across CIP optimization, filtration monitoring, fermentation tracking, and more. Because the technology measures spectral properties rather than a single variable, the same sensor installation can support multiple process optimization use cases. Please note the number of sensors you need may vary depending on your CIP skid and specific use case.

CIP (Clean-in-Place) optimization is the process of improving cleaning cycles in food, beverage, dairy, and pharmaceutical manufacturing without disassembling equipment. Traditional CIP relies on fixed timer-based cycles that often run longer than necessary. Optimized CIP uses real-time data from our sensor’s spectral analysis  to determine exactly when each cleaning step is complete as well as prevent under-wash. The result is reduced water, energy, and cleaning chemical use, and reduced downtime, while maintaining or improving sanitation effectiveness.

Laminar reduces water use in food manufacturing by optimizing CIP and rinse cycles — the largest water consumers in most plants, facilities, factories, or breweries.

Key strategies include:

• Using real-time sensors to end rinse steps as soon as the ideal cleanliness condition is achieved (rather than fixed timers)
• Recovering and reusing rinse water where safe
• Optimizing and recovering chemicals
• Monitoring changeovers to minimize flush volumes and ultimately, lost product.

More complex use cases of our inline spectroscopy and machine learning models involve using data to make automated decisions based on actual process conditions.

Laminar is an AI-powered sensor and machine learning solution for liquid manufacturing across food, beverage, pharmaceutical, health, beauty, and other industries. Our proprietary Spectral Sensors use UV-Vis-IR spectroscopy to read the unique spectral "fingerprint" of products and fluids in real time.

Laminar sensor technology and ML models enable facilities to optimize CIP (Clean-in-Place) cycles, reduce changeover time, minimize product loss, and reduce water and energy consumption. Laminar installs inline and integrates with your systems without disrupting existing operations or adding headcount.

Laminar primarily serves food and beverage manufacturing, dairy processing, brewing, and pharmaceutical production. Our technology is designed for any facility using Programmable Logic Controllers (PLCs) and running CIP processes or needing real-time quality monitoring of liquid products.

Laminar’s inline Spectral Sensors measure light transmittance and reflectance across the UV, visible, and infrared spectrum. This spectroscopic approach analyzes the molecular composition of fluids in your pipes — detecting product type, concentration, contamination, and quality changes in real time.

The sensors are compact cylinders approximately 2.4 inches in diameter and 4.7 inches long. They attach to sanitary sight glasses mounted in your process piping.

Laminar supplies flow cells in outer diameters of 1.5", 2", 2.5", 3", 4", and 6" (imperial) as well as 41mm, 53mm, 70mm, and 85mm (metric). For pipes outside these sizes, reducers or expanders can be used — Laminar can help spec these modifications.

No routine maintenance is required. The CIP process that cleans your lines also keeps the sensor face clear. We recommend periodic visual inspection of the outer housing to ensure the device hasn't been dislodged or damaged. Sensors are projected to last 5 years under normal operating conditions.

All sensors receive a 4-factor calibration before shipment, correcting for variance in pipe diameter, temperature, light sources, and sensor-to-sensor differences. No calibration action is required from your team — sensors arrive ready to install.

After installation, Laminar collects approximately 2-3 weeks of passive data to train machine learning models specific to your processes. Once deployed, models first run in evaluation mode so you can validate performance before enabling automation. Many customers see projected savings within the first month of deployment.

No major changes are required. Laminar integrates with your existing PLC. The PLC retains full control — Laminar sends optimization recommendations as simple signals that your PLC acts on. You can enable or disable Laminar's recommendations at any time.

Laminar's ML models identify the earliest safe moment to advance each CIP step by analyzing real-time sensor data rather than relying on fixed timers. This eliminates unnecessary rinse time, reducing water usage and the energy required to heat that water. Facilities typically see measurable reductions in both resources while maintaining or improving cleaning effectiveness.

Over multiple washes, our sensors detect product concentration by measuring reflectance in the outlet and return lines during pre-rinse and changeover. By identifying exactly when product transitions to wash water — rather than using conservative time-based estimates — facilities can recover more product and send less to drain. The system calculates product loss volume and tracks improvement over time.

Laminar's Insights dashboard shows both projected and actualized savings. Projected savings estimate what you would save if the ML model's recommendations were fully adopted. Actualized savings reflect real reductions after automation is enabled.

Reports break down time, water, energy, and product savings per wash cycle and over time. Our customers use this data to build the most optimized version of their processes and ultimately their facility.

Unlike static CIP optimization that simply adjusts recipe setpoints, Laminar's CIP Model determines whether fluid is clean or dirty in real time. The models analyze spectral data alongside PLC signals (conductivity, temperature, flow rate) to identify the earliest safe moment to advance each step. This allows the system to adapt to varying conditions, equipment states, and products — while continuously monitoring for underwashing.

During training, models learn to associate SKU data from your PLC with each product's spectral fingerprint. Once deployed, the system detects the exact transition point between Product A, the mixed zone, and Product B. This allows precise changeover timing — advancing the process as soon as the new product is within spec, rather than relying on conservative time-based estimates.

Every fluid has a unique spectral fingerprint based on its molecular composition. Atoms and chemical bonds absorb, transmit, and reflect light in characteristic ways. Our sensors capture this data, and ML models learn to distinguish between compounds using subtle differences in their spectral signatures. The sensors are designed for sub-second accuracy to enable the differentiation between similar products that look identical to the naked eye.

Beyond CIP and changeover optimization, Laminar's platform has been successfully applied to filter aid (diatomaceous earth) dosage optimization, COD prediction for wastewater, underwash detection, and FOG analysis. The technology is highly flexible — if you have a liquid process where real-time composition data would drive better decisions, contact us to discuss your use case.

Most customers begin with a pilot deployment on one or two CIP circuits to validate performance in their specific environment. The typical process is:

(1) Discovery call to understand your processes and goals

(2) Site assessment to identify optimal sensor locations

(3) Hardware installation and PLC integration

(4) 2-3 week data collection and model training period

(5) Model deployment in evaluation mode

(6) Enable automation once you're confident in the results

Contact us at hello@runlaminar.com to schedule a discovery call to estimate ROI for your facility.

A typical pilot runs 3 months and focuses on 1-2 CIP circuits or process lines. During the pilot, you'll see projected savings calculated in real time before enabling any automation. This lets you validate Laminar's recommendations against your existing quality checks (e.g. ATP swabs, final rinse samples, equipment inspections) before turning on closed-loop automation.

Many customers see measurable projected savings within the first month of data collection, before automation is even enabled. Once our models are validated by your team and closed-loop automation is enabled, actualized savings begin to accumulate immediately. ROI timelines vary by facility, but customers with high CIP frequency, high water/energy costs, or significant product loss typically see the fastest payback. During discovery, we can model expected savings based on your specific operating conditions.

Laminar takes data security seriously. We have passed IT security reviews and penetration tests from Fortune 500 technology and manufacturing companies. Data is encrypted in transit. Laminar is SOC 2 Certified.

Yes. Laminar is SOC 2 certified.