
Pallon
Using machine learning to detect defects in sewer inspection videos – faster, more objective and less error-prone.
Date | Investors | Amount | Round |
---|---|---|---|
- | investor investor | €0.0 | round |
investor | €0.0 | round | |
investor | €0.0 | round | |
investor | €0.0 | round | |
investor investor investor | €0.0 | round | |
N/A | - | ||
Total Funding | 000k |
USD | 2022 | 2023 |
---|---|---|
Revenues | 0000 | 0000 |
% growth | - | 25 % |
EBITDA | 0000 | 0000 |
Profit | 0000 | 0000 |
EV | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x |
R&D budget | 0000 | 0000 |
Source: Dealroom estimates
Related Content
Pallon.com is a tech startup that operates in the infrastructure and utilities sector, specifically focusing on sewer inspection. The company leverages advanced machine learning and computer vision algorithms to detect, localize, and measure pipe defects. This technology is a game-changer for engineers who rely on it to analyze thousands of kilometers of sewer pipes, ensuring the highest coding standards.
Pallon's primary clients are engineers, city planners, and utility companies who need accurate and efficient sewer inspection data. The company's innovative approach allows for more precise budget planning, condition assessment, and overall process efficiency.
The business model is based on data analysis. Clients upload their sewer inspection footage to the cloud, and Pallon's AI analyzes the data, labeling all defects. The results are then delivered to the client, typically within a week. This model allows Pallon to provide a high-value service at a rapid pace, saving their clients significant time and resources.
Pallon's revenue is likely generated through a subscription-based model or per-analysis fee, although the exact pricing structure is not specified. The company has already gained the trust of over 150 customers, including city planners and utility companies, indicating a strong market presence and potential for growth.
Keywords: Sewer Inspection, Machine Learning, Computer Vision, Data Analysis, Infrastructure, Utilities, AI, Cloud-Based, Pipe Defect Detection, Time-Efficiency.