by making production processes more efficient.
Reduce your
energy use
by +20%

The future is here: specialized AI agents
for industrial manufacturers
We reduce energy use & machine downtime
in production processes
Water management
Furnaces
Air compressors
Extractor hoods
Grinders
Case Studies
Automatizing operation efficiency
Real time monitoring
We built a digital twin of your devices to monitor energy consumption, key process parameters and savings.
Autonomous energy efficiency & predictive maintenance
Our AI agents:
- Learn from real-time process data, metering & actions
- Continuously identify optimal settings on machines
- Implement the improvements in production
- Prevent downtimes before they occur
SaaS aligned with your savings
- Reduce operation costs, at a time of rising input prices
- Abate carbon footprint, at a time you’re asked for more sustainable products
- Slash carbon offset costs & unlock demand-response benefits
Proud to be backed by
Meet the team
+50 years of experience in energy, engineering and data science
Bardia
Rafieian
CTO
+10 years of experience in Software engineering (Huawei) & Cloud. +5 YOE in deep tech startups.
Ph.D. in NLP (Natural Language Processing) & Artificial Intelligence (UPC, Barcelona) and Software Engineering degree (Iran).
LinkedIn
Ph.D. in NLP (Natural Language Processing) & Artificial Intelligence (UPC, Barcelona) and Software Engineering degree (Iran).
Mohammad
Peyman
RL Data Scientist
Ph.D. in Reinforcement Learning and Artificial Intelligence at UPV (Spain).
MSc in Modelling of Science & Engineering (UAB, Barcelona). Mechanical Engineering Degree in Teheran.
Yusef
Ahsini
Ouariaghli
ML Engineer
Brilliant Machine Learning Engineer with a lot of experience in developing ML models, despite of his young age. Multiple Hackathon winner while finalising his MSc in Math Research & Data Engineer at UPV.
Backend
Engineer
coming soon
Brilliant software engineer with a background in front and backend. With international experience and a Cloud based system mastery.
Óscar
Morales
Sales engineer
Process Engineer with a MSc in Energy efficiency (Univ. of Stuttgart). International experienced professional with a background in energy in EnBW (Germany) and COMSA (Spain).
María
Guasch
Morgades
Industrial Ph.D. as
RL Data scientist
Great mathematician with experience in a biotech startup. She will soon join BeChained enrolling an Industrial Ph.D. and helping us develop our trailblazing products.
Mariana
Vargas
Sales Engineer
Environmental Engineering degree in East London and international experience, she brings Technical experience in energy infrastructure and buildings.
Janne
Öfversten
Advisor
Currently Head of Digital & Sustainability Innovations at Kone in Finland. His carrier comprises two decades of experience in Nokia (across IoT, energy and power, and technology) and one in Digital Innovation at Kone.
LinkedIn
Oliver
Wolf
Advisor
Currently Customer Experience Manager at Deutsche Bahn.
He worked in the development of Long Distance Trains and different International Executive tenures at Lufthansa.
LinkedIn
He worked in the development of Long Distance Trains and different International Executive tenures at Lufthansa.
Reghu
Ram
Advisor
SVP of Fintech Products and Digitals at Deutsche Telekom.
His career comprises Executive roles in Deutsche Telekom and SAP; as well Executive education in Insead and Harvard Business School.
His career comprises Executive roles in Deutsche Telekom and SAP; as well Executive education in Insead and Harvard Business School.
Latest blog posts

🌍💡 AI Agents: The Future of Industrial Efficiency
Industrial manufacturing is at a crossroads—facing rising energy costs, inefficiencies, and stagnation. But AI-driven industrial agents are changing the game. 🚀In my latest article, I explore how BeChained is leveraging AI to optimize water management,…

Peak Shaving, Load Shifting vs. AI-Powered Dynamic Energy Optimization
(Original article from Medium) Introduction With rising energy costs, market volatility and increasing emphasis on sustainable practices, manufacturers are under pressure to optimize energy use. Traditional methods like peak shaving and load shifting have…