Data foundations
Turning fragmented operational sources into context that models and engineers can share.
Labs
Asayl Labs builds AI systems that learn from real operations, human judgment, and evidence.
We believe the next step for intelligence is not only better models, but better contact with reality: machines, measurements, constraints, failures, operators, and decisions.
We are starting in physical industry because it is where intelligence must be grounded, checked, and improved with humans in the loop.
Language models can reason over what has already been written. Physical systems ask for something harder: intelligence that can work with signals, tools, procedures, operators, simulations, and measurements.
The path to more general intelligence runs through systems that can test claims against reality.
For us, the human is not a temporary workaround. The human is part of the loop that defines what matters, catches what models miss, and turns raw prediction into trusted action.
Turning fragmented operational sources into context that models and engineers can share.
Linking signals, events, procedures, and constraints into a live picture of work.
Keeping humans, measurements, and constraints in the loop before automation acts.
Our founding team comes from ENSA Berrechid and works across ML systems, data engineering, software, product design, aerospace, robotics, and embedded systems. We have built MLOps workflows, pharma software, airport systems, product and data tools, and robotics and embedded systems.
ML systems & research engineering
MLOps at Intelcia; software at Euromodial; ENSA infrastructure.
Data engineering & software systems
Pharma software; industrial data systems.
Product design & go-to-market
Design, GTM, and data/product systems.
Aerospace & embedded systems
ONDA Casablanca Airport; embedded systems.
Aerospace, robotics & embedded systems
Royal Air Maroc; robotics and industrial automation.
We are advised by professors working across engineering, infrastructure, and applied systems.
Computer science, mathematics, PINNs, optimization, and numerical modeling
Competitive intelligence, governance, strategic management, and higher education
Statistics, probability, stochastic processes, and applied mathematics
Computer networks, cloud computing, AI, deep learning, and network security
Artificial intelligence, computer vision, machine learning, and signal/image processing
We are looking for industrial and research partners working where humans already make hard decisions around real machines: factories, engineering teams, test benches, and applied R&D groups.
A first conversation can start from a workflow, schema, sample, synthetic dataset, or controlled context.