Deeply Inc. 디플리
"We add meaning to every sound"
Industrial audio AI company developing machine-hearing technology that detects equipment anomalies and danger signals from sound for smart factories and safety.
Deeply Inc. is a South Korean audio AI company, founded in 2017 and based in Seoul, that develops machine-hearing technology to interpret the physical world through sound. Built on the team's academic and industrial experience in signal processing and machine learning, the company analyzes not only voice but nonverbal sounds such as equipment noise, ambient noise and danger signals. Its core technology covers sound event detection, voice separation and sentiment or context recognition, and is trained on a proprietary dataset of more than 14,000 GB of real-world labeled audio recorded across varied environments and microphone configurations. A distinctive element of its approach is the use of impulse-response (IR) modeling, which characterizes the acoustic behavior of a space to improve model accuracy in specific real-world settings. Deeply applies this technology to industrial and safety domains through two main solution lines: Listen AI Industrial, for real-time machine sound analysis that detects machine anomalies, monitors equipment condition and supports quality inspection in smart manufacturing; and Listen AI Safety, for monitoring risk signals in public and industrial settings.
The company positions machine hearing as a physical-AI capability that helps manufacturers improve operational efficiency, reduce downtime and enhance production reliability, and notes deployment of sound-detection technology in environments such as smart cities, factories, power plants and the military. Deeply also offers its labeled audio datasets to other organizations building production-grade sound deep-learning models. The company was founded by Han Park and Suji Lee, with Suji Lee serving as CEO.
Primary type & automation activities this supplier delivers:
Listen AI Industrial
Real-time machine sound analysis to detect anomalies and support quality inspection in smart factories.
Listen AI Safety
Sound AI that listens for risk and danger signals across public and industrial sites.
Contact Deeply Inc.
WEBSITE
https://deeplyinc.com/HEADQUARTERS
Korea, Republic of (South)
Company Facts
Founded
2017
Primary Role
Software/Algorithm
Company Size
-
Primary Region
Asia-Pacific
Annual Sales
-
Funding Stage
-
Funding Total
-
Certifications & Memberships
New 'SANDO' System Keeps UAVs Safe from Collisions in Wildfire Areas
The 'SANDO' system enhances the safety of uncrewed aerial vehicles (UAVs) by ensuring their flight paths remain collision-free, particularly in hazardous environments like wildfires. This technology is crucial as UAVs are often deployed to gather vital information in such dangerous situations, where they face risks from sudden flare-ups and falling debris. The importance of the 'SANDO' system lies in its ability to protect UAVs from potential damage during operations in uncharted territories. By avoiding collisions with obstacles such as tree branches, the system allows for safer data collection, which is essential for rescuers responding to wildfires. This advancement could significantly improve the effectiveness of UAVs in emergency response scenarios. Looking ahead, the implementation of the 'SANDO' system could lead to broader applications of UAVs in various challenging environments. As the technology develops, stakeholders will be keen to observe its impact on UAV operational safety and efficiency in disaster response efforts. No further timeline was disclosed at the time of publication.
Robotics
MIT Develops SANDO: A Collision-Free Navigation System for UAVs in Unknown Environments
MIT researchers have developed an autonomous navigation system named SANDO, designed for uncrewed aerial vehicles (UAVs) to navigate safely in unpredictable environments. This system ensures that UAVs can avoid collisions with unknown moving obstacles, which is crucial in high-risk scenarios like search and rescue missions or disaster response. The significance of SANDO lies in its ability to provide formal safety guarantees in dynamic environments, where traditional navigation systems fall short. Unlike existing planners that only work in static settings or lack formal guarantees, SANDO uses a mathematical approach to ensure collision avoidance, making it particularly valuable for applications requiring real-time adaptability. Looking ahead, the potential applications for SANDO are vast, including emergency medical supply deliveries and exploration in hazardous areas. As the technology matures, it could revolutionize how UAVs operate in complex environments, enhancing safety and efficiency. No further timeline was disclosed at the time of publication.
Research Computer science and technology Algorithms Drones Robotics Autonomous vehicles
TwelveLabs Launches Pegasus 1.6 for Enhanced Video Understanding in Physical AI
TwelveLabs Inc. has unveiled its Pegasus 1.6 model, designed to enhance video understanding for physical AI applications. This model addresses the challenge of transforming complex video footage into actionable insights, enabling robotics and AI teams to train on real human experiences rather than starting from scratch. The significance of Pegasus 1.6 lies in its ability to provide temporal context, spatial reasoning, and task completion judgment, which are crucial for machines to navigate real-world environments. According to Jae Lee, co-founder and CEO of TwelveLabs, the model allows for a more precise understanding of actions and interactions captured in egocentric video, facilitating the development of smarter robotics systems. Looking ahead, TwelveLabs aims to further refine its video intelligence platform, focusing on the video understanding layer to improve training data for robotics teams. The company emphasizes that Pegasus 1.6 can utilize existing video data and analyze still images, making it a versatile tool for various applications in physical AI. No further timeline was disclosed at the time of publication.
Artificial Intelligence Artificial Intelligence / Cognition Assembly Human Robot Interaction / Haptics Manufacturing Microprocessors / SoC
Teledyne FLIR Introduces AI-Driven Air-to-Ground Tracking Software for UAS
Teledyne FLIR OEM has unveiled Prism A-ISR, a cutting-edge software module aimed at enhancing air-to-ground detection and tracking for uncrewed aircraft systems (UAS) and airborne intelligence, surveillance, and reconnaissance (ISR) platforms. Announced on October 6, this software leverages artificial intelligence to detect, classify, and track multiple ground objects in real time, utilizing data from various sensor types including midwave infrared (MWIR) and visible electro-optical (EO) sensors. The significance of Prism A-ISR lies in its ability to perform edge processing, enabling airborne systems to analyze sensor data independently of remote computing resources. This capability is crucial for applications requiring persistent surveillance and defense missions, as it enhances long-range situational awareness while minimizing false alarms. Teledyne FLIR's advanced image processing tools, including patented denoise and super-resolution technology, further improve detection capabilities in challenging conditions. Looking ahead, Teledyne FLIR's AIMMGen synthetic model-training service allows developers to quickly adapt the software for new target classes, streamlining the creation of mission models. The software is compatible with NVIDIA and Qualcomm embedded AI platforms and several Teledyne FLIR camera modules, including the NDAA-compliant Boson+ and Neutrino thermal camera families. No further timeline was disclosed at the time of publication.
AI Applications C-UAS Defense defense Drone News
Overview AI Introduces OV Spark and OV Spark Pro AI Inspection Cameras
Overview AI has launched the OV Spark and OV Spark Pro, a new line of AI inspection cameras featuring an agentic AI layer that communicates in plain English. The cameras come equipped with 10 inspection tools, including seven deep learning AI models and three ready-to-use tools for barcodes, measurements, and color matching. The introduction of the OV Spark cameras is significant as they address the challenges of consistency in inspection processes. Christine Chacko, a technical product marketing manager at Overview AI, highlighted that the cameras adapt to the shifting and rotating parts in a robot cell, ensuring accurate inspections. This innovation aims to enhance defect detection across factory lines. Looking ahead, Overview AI's mission is to ensure that every defect is caught in every factory, with the OV Spark designed to minimize setup work. The cameras are currently available for purchase directly from Overview AI and through distribution partners. No further timeline was disclosed at the time of publication.
Artificial Intelligence Artificial Intelligence / Cognition Cameras / Imaging / Vision Design / Development Manufacturing News
Epson Showcases Color Labeling and Robotic Automation at PACK EXPO 2026
Epson has announced its participation in PACK EXPO International, scheduled from October 18 to 21, 2026, where it will demonstrate its ColorWorks® on-demand color label printers, collaborative robots, and vision technology. These innovations aim to enhance the efficiency of packaging and fulfillment operations. The introduction of ColorWorks printers allows manufacturers to produce high-quality, customized color labels on demand, addressing the growing need for flexibility in labeling processes. Coupled with robotic automation, these solutions are designed to streamline various tasks, including handling, inspection, and packaging, thereby improving overall productivity. As the event approaches, industry professionals should watch for how Epson's integrated solutions can transform labeling and packaging workflows. No further timeline was disclosed at the time of publication.
OpenAI's GPT-6 Astra Dominates SuperCLUE's Robot-Brain Benchmark with Planning Superiority
OpenAI's GPT-6 Astra achieved the highest overall score in SuperCLUE's September 2026 EmbodiedCLUE-VLA evaluation, leading with a score of 85.71 in interaction and planning. This score significantly surpasses the runner-up, Gemini-3.8-Flash, which scored 64.29, highlighting Astra's notable advantage in planning capabilities. The importance of this evaluation lies in its comprehensive assessment of ten models, which includes basic perception, visual reasoning, interaction, planning, and embodied safety. SuperCLUE's report indicates that while Astra leads in overall performance, the evaluation's fixed input/output protocol may limit the generalization of results across different tasks and protocols, making it a useful but narrow comparison of each model's capabilities. Looking ahead, the next critical aspect to observe is how these models perform in real-world scenarios, particularly in executing plans and adapting to unforeseen circumstances. The results from physical trials will be essential to determine the practical applications of these models in robotics, beyond the theoretical scores presented in this benchmark.
OpenAI China
Robotics and Physical AI Addressing Key Physical Security Challenges in 2026
In 2026, over $23 billion has been invested in enhancing the integration of robotics and artificial intelligence for physical security. This investment aims to address the increasing complexity of threats against critical infrastructure, such as data centers and manufacturing plants. The adaptive capabilities of these technologies are essential for organizations to protect their assets effectively. The intersection of cybersecurity and physical protection presents new challenges, as demonstrated by the Jaguar Land Rover incident, where cyber breaches led to significant operational disruptions. Organizations must adapt to a rapidly changing security landscape, where legacy systems can exacerbate vulnerabilities. The need for proactive security measures is more pressing than ever, particularly in critical industries. At GTC Taipei 2025, companies like Foxlink showcased innovations such as the “robot dog,” designed to enhance physical security through adaptive functions and smart sensors. This technology represents a shift towards a more proactive security environment, enabling organizations to respond to complex threats effectively. No further timeline was disclosed at the time of publication.
Artificial Intelligence Artificial Intelligence / Cognition Automotive Autonomous Mobile Robots (AMRs) Cameras / Imaging / Vision Manufacturing
Safety Considerations Will Shape the Future of Humanoid Robots
In a recent discussion, Rick Balzano, Vice President of Go-to-Market for AI Services, Safety and Robotics at TaskUs, highlighted the critical work required to make humanoid robots reliable. He emphasized that unlike large language models, which operate on digital data, humanoid robots must navigate and interact with the physical world, necessitating extensive real-world data collection and validation. Balzano pointed out that while humanoid robots are often marketed as versatile workers, they currently remain highly specialized machines disguised in human-like forms. He noted that significant advancements have been made in areas such as locomotion and perception, but the gap between demonstration and real-world application is substantial, often involving controlled environments and remote assistance. Looking ahead, the industry must focus on bridging this gap to enhance the reliability of humanoid robots. Balzano's insights underscore the importance of safety and data integrity in developing robots that can operate effectively in diverse environments. No further timeline was disclosed at the time of publication.
AI and Robotics Innovation
Ouster and Seneca Enhance Wildfire Drones with Advanced 3D LiDAR Technology
Ouster and Seneca have partnered to integrate Ouster’s Rev8 OS1 Max digital LiDAR into Seneca’s autonomous wildfire-response drones. This collaboration aims to enhance the drones' ability to perceive and navigate challenging environments, particularly during wildfires where visibility is often compromised. The integration of LiDAR technology allows Seneca's drones to create detailed 3D representations of their surroundings, improving their operational capabilities in various missions such as cargo delivery, terrain mapping, and infrastructure inspection. The Rev8 OS1 Max sensor, known for its high resolution and range, provides critical information for obstacle detection and flight path adjustments, essential for safe autonomous operations. As the demand for autonomous aircraft in emergency response grows, the partnership underscores the importance of advanced perception systems in ensuring safety and efficiency. No further timeline was disclosed at the time of publication.
News
Planning Algorithms Steven M. LaValle — RSF Specialist Shelf · Book S4 of 6
The reference that treats planning as a subject in its own right: configuration space, sampling-based methods, RRT. Free online, dual difficulty 4/5-2/5.
Introduction to Robotics J. J. Craig — RSF Top 10 Robot Education Textbooks · No. 6
Six of ten benchmark universities teach kinematics from Craig. Frames, transforms and D-H parameters: the language vendor manuals already speak.
The Association for Advancing Automation Hires Aaron Prather as Director of Market Intelligence
Aaron Prather joins the Association for Advancing Automation (A3) as Director of Market Intelligence, bringing expertise from FedEx and ASTM International to drive robotics industry insights.
The Core Components Battle of Indutrial Robot, Reducers, Servo Systems & Controllers
A technology-first analysis of the three pillars driving industrial robot capability: precision reducers, servo systems, and motion controllers. Maps the full global supplier ecosystem — Japan, Europe, and China — from component specs to product generations and integration architectures.
Boston Dynamics IPO and $100B Valuation: How It Compares to Tesla Optimus, Figure AI and Humanoid Rivals
Boston Dynamics' valuation has surged from $1.1B to a potential IPO target of $85B+. We verify the numbers, benchmark against Tesla Optimus, Figure AI and Apptronik, and explain what a listing would mean for the humanoid robotics industry.
Columbia's Emo: Solving Robot Face Problem
Columbia's Emo robot breakthrough reveals why facial biomimicry is robotics' second hardest challenge. Analysis of tech barriers and 2028-2030 timeline.
Is the NVIDIA-Siemens Partnership a Trojan Horse?
Media hailed it as a landmark alliance. But flip the view: it resembles a Trojan Horse. Siemens gains compute and world-model access; NVIDIA quietly secures control over industrial training data, model iteration, and world representation.
Flexible Machining of Large Structures (Part II)
Why mobile machining still struggles with stiffness, accuracy, and autonomy—and how hybrid robots, AI perception, and digital twins will drive breakthroughs over the next five years.
How RichTech Robotics Uses China’s Supply Chain to Compete in the U.S. Service Robot Market
How RichTech Robotics leverages China’s supply chain to scale service robots in the U.S., balancing cost efficiency, localization, and compliance.
Solar Installation Robots Reach Infrastructure Scale in 2025
Solar installation robots are scaling from pilots to infrastructure-grade automation in 2025, reshaping EPC productivity, labor economics, and utility-scale PV construction.
