🔥36氪•Freshcollected in 26m
Tsinghua AI Ore Sorter Raises $28M Series C
💡$28M fund for AI ore sorters revolutionizing mining efficiency sans water
⚡ 30-Second TL;DR
What Changed
Raised ~200M RMB Series C led by招商局資本 with multiple VCs.
Why It Matters
This funding boosts AI in mining, promoting sustainable dry sorting amid 'dual carbon' goals, potentially expanding to new industries.
What To Do Next
Prototype X-ray + AI vision pipelines using PyTorch for industrial object sorting.
Who should care:Founders & Product Leaders
🧠 Deep Insight
AI-generated analysis for this event.
🔑 Enhanced Key Takeaways
- •Horist Technology's core technology utilizes dual-energy X-ray transmission (DEXRT) combined with high-speed pneumatic ejection systems, allowing for real-time mineral identification at belt speeds exceeding 3 meters per second.
- •The company has successfully integrated its sorting solutions into 'smart mine' digital twin platforms, enabling remote monitoring and predictive maintenance for mining operators in remote regions.
- •Beyond traditional mining, Horist is actively piloting its AI-driven sorting technology for industrial solid waste recycling and construction debris separation to diversify its revenue streams beyond the cyclical mining sector.
📊 Competitor Analysis▸ Show
| Feature | Horist Technology | TOMRA Sorting Mining | Steinert |
|---|---|---|---|
| Core Tech | AI + Dual-Energy X-Ray | Sensor-Based Sorting (XRT/NIR) | X-Ray Transmission (XRT) |
| Market Focus | Emerging Markets/China | Global/Premium | Global/Premium |
| Pricing | Competitive/Cost-effective | High-end | High-end |
| Key Benchmark | 99.9% Accuracy | High throughput/Reliability | High throughput/Durability |
🛠️ Technical Deep Dive
- Sensor Fusion: Combines high-resolution X-ray transmission (XRT) sensors with visible light cameras for multi-modal data acquisition.
- AI Architecture: Utilizes proprietary convolutional neural networks (CNNs) optimized for edge computing on NVIDIA Jetson or similar industrial-grade embedded platforms to minimize latency.
- Ejection System: Employs high-frequency, low-latency pneumatic valve arrays capable of millisecond-level response times to ensure precise separation of ore particles.
- Material Handling: Features modular belt designs with vibration-dampening mechanisms to maintain stable particle distribution for consistent sensor readings.
🔮 Future ImplicationsAI analysis grounded in cited sources
Horist will achieve a dominant market share in the Southeast Asian mineral processing sector by 2027.
The company's existing footprint in Indonesia and its cost-competitive advantage over Western incumbents position it to capture the rapid growth in regional nickel and copper mining.
The company will pivot toward a 'Sorting-as-a-Service' (SaaS) business model.
Transitioning from hardware sales to performance-based contracts will provide recurring revenue and mitigate the volatility of the mining equipment capital expenditure cycle.
⏳ Timeline
2018-05
Beijing Horist Technology founded by Tsinghua University alumni.
2021-09
Completed Series A funding round to accelerate R&D of AI sorting algorithms.
2023-06
Achieved significant market penetration with major deployments at Zijin Mining sites.
2024-11
Expanded international operations with first major export contracts to Brazil and Indonesia.
2026-04
Closed 200M RMB Series C funding led by China Merchants Capital.
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Original source: 36氪 ↗