Sound AI that protects production-line quality and public-space safety through sound.
Deeply is the only proven Sound AI on global production lines.
From vehicle assembly lines to EOL inspection, AI judgments are being made in real time at 30+ deployed sites worldwide
Defects are easy to detect in a test lab. The real challenge is detecting them on a noisy production line.
cumulative analyses on production floors
01Industrial Solution Applications0+0+Proof: Over 100 million analyses on production floors. Proven in the real world.cumulative analyses on production floorsProduction line quality inspectionProduction lineFinal inspection before shipmentEOLEquipment predictive maintenancePdM
01Industrial Solution Applications
Proof: Over 100 million analyses on production floors. Proven in the real world.
02Accuracy & Trust0.00%0.00%99.98% accuracy, proven through more than 100 million analyses. Even in extremely noisy production environments, Deeply detects signal differences as subtle as 1.77 dB SNR — so genuine defects don’t go unnoticed.SNR 1.77dBSignal difference detected99%+Connector and bolt fastening99.8%EOL Defect Escape Prevention
99.98% accuracy, proven through more than 100 million analyses. Even in extremely noisy production environments, Deeply detects signal differences as subtle as 1.77 dB SNR — so genuine defects don’t go unnoticed.
03Inspection Statistics0+0+From vehicle assembly lines to connector fastening detection and EOL inspection, manufacturers are applying Deeply AI across a wide range of manufacturing processes.100% of existing customers using motor abnormal-noise inspection are exploring expansion to additional production lines.6,000Products per hour4.3 millionProducts per month100% in-lineInspection & Detection
From vehicle assembly lines to connector fastening detection and EOL inspection, manufacturers are applying Deeply AI across a wide range of manufacturing processes.
100% of existing customers using motor abnormal-noise inspection are exploring expansion to additional production lines.
04Traditional Inspection vs Deeply AI0 hours0 hours520,000 hours of acoustic data (20 TB), collected directly by Deeply from production lines running 24/7.What would take 178 experienced inspectors an entire year to hear, Deeply has already heard.20 TBAcoustic Data Collected2 YearsOperationEquivalent to:178 InspectorsListening for a yearIndustrial consultationSee Listen AI Industrial
04Traditional Inspection vs Deeply AI
520,000 hours of acoustic data (20 TB), collected directly by Deeply from production lines running 24/7.
What would take 178 experienced inspectors an entire year to hear, Deeply has already heard.
Sound AI Solution That Captures Important Sounds
0103Diagnosing Machine Quality Through SoundListen AI IndustrialFactoryAIManufacturingAIQualityInspectionAIPLC · MESQCPredictiveMaintenanceAuditoryProcessDigitizationLearn More
0303Do You Have a Specific Sound You Want to Detect?Custom SolutionWe analyze the sounds you want, in the environments you choose, in real time.Learn More
World-Class Real-Time Sound Analysis AI
DEEPLY is dedicated to developing our own AI models and enhancing technology.We introduce world-class technical capabilities verified by various domestic and international certifications.
Various Customer Cases Utilizing Listen AI
Developing tailored sound AI solutions to fit our clients' environments and specific needs, and applying them in real-world situations.
Automotive & heavy equipment · Assembly · Connector & bolt fastening
Connector Click Sound Inspection: Verifying Fastening by Sound
Catch missed and partial fastening on the assembly line by sound instead of vision. Check whether each connector is fastened, and how many times, even at the underside where the eye cannot reach
Automotive parts · Post-assembly inspection · Motors & actuators
Motor Noise (Rotation Sound) Inspection: Judging Quality by Sound
Replace the noise judgment skilled inspectors made by ear with automatic judgment based on rotation-sound data. One consistent standard instead of one per inspector, inspected in-line without an anechoic room
Ports & logistics · Equipment operation · Crane wires & bearings
Predictive Maintenance for Port Cranes, Done by Sound
Detect anomalies in cranes and rotating equipment by sound instead of vibration sensors. Non-contact microphones monitor continuously without mounting constraints
Customers and partners leading innovation with us
DEEPLY collaborates with global tech companies and public enterprises, sharing the value of technology with the world.
Thailand Automotive Institute
Naejangsan National Park Office
Sejong Government Complex Gymnasium
Yangcheon-gu Facilities Management Corporation
Korea University Medicine
Gwangju Metropolitan City
Incheon Transit Corporation
Seoul National University
Frequently asked questions
What kind of company is Deeply?
Deeply is an AI startup founded in 2017 that delivers sound analysis solutions across manufacturing, safety, and security use cases.
What does sound AI solve on a manufacturing floor?
Sound AI automates the auditory inspection that used to rest on a person’s ears. A judgment made by ear or by fingertip shifts with the worker’s fatigue and leaves no inspection history behind as data, while Listen AI makes the same judgment from the sound signal and keeps every OK/NG result as a record. More than 60% cost reduction has been reported for large hearing inspection line operations. Accuracy and measurement range differ by inspection type, and the Listen AI Industrial page covers them per type in its own FAQ.
How is this different from vision inspection or vibration sensors?
Listen AI judges from the sound signal rather than from an image or a vibration reading. It reaches the motor and actuator defects inside a product that a vision sensor misses, inspecting every unit 24/7 at the EOL stage and blocking 99.8% of defect escapes. That figure is scoped to full inspection of motors and actuators at the EOL stage and is not combined with figures from other inspection types. Sounds too faint for a person to tell apart, such as a connector engagement click, are judged the same way.
Which processes and equipment can it be applied to?
The three core Listen AI Industrial solutions are rotating-equipment noise inspection, assembly-line connector engagement sound inspection, and equipment aging detection. On the assembly process it overcomes the high noise of an OEM assembly line and detects continuous connector and bolt fastening work in real time with 99%+ accuracy. For predictive maintenance, which watches the equipment rather than the product, it draws on a 15TB manufacturing acoustic dataset and analysis experience across more than 70 sound types to catch a fault signal early and stop downtime before it starts. Deployed cases also cover glass breakage and scratch detection, semiconductor component wear diagnosis, robot equipment aging analysis, and gas and pressure valve sound analysis.
What data or process do we need before deploying?
What it takes is the equipment to be inspected and the sound that equipment makes. Once the hardware is installed and the engagement or operating sounds of the target equipment are collected, initial evaluation can begin on top of Deeply’s Foundation Model. Within the scope of the connector engagement sound press release, this does not wait on weeks or months of site-specific defect data and changes no existing line equipment, tools, or layout, but that account assumes a Foundation Model specialized in manufacturing acoustic data, so it does not mean every deployment needs no data collection at all. Inspection history can be linked to a MES (Manufacturing Execution System) or PLC and kept as traceable data.
A PoC runs in four steps: install the hardware, collect sound from the target equipment, run the initial evaluation, then carry the result into production-line deployment. The initial evaluation starts on top of Deeply’s Foundation Model, and the PoC result is what carries into the production line. The microphone setup and the analysis server deployment are chosen against the noise conditions on site, and the Listen AI Industrial page covers the conditions per inspection type in its own FAQ.
资料来源：企业官网公司简介（复核日期：2026-10-07）。