Scientific media
Video analysis, object detection, tracking, annotation pipelines, and experiment-ready datasets.
Applied science, AI, and education
Softel Labs
Research-grade software for scientific data, computer vision, signals, language processing, and educational publishing.
Focus
Scientific tools with clear educational paths.
Softel Labs connects research software with practical learning material: readable code, reproducible experiments, technical books, and Python libraries built around scientific workflows.
Research areas
From signals to scientific video.
Language and documents
Data extraction, document analysis, sentiment models, retrieval workflows, and explainable summaries.
Signals and time series
Signal decomposition, regression, monitoring, forecasts, and pattern discovery in noisy measurements.
Learning systems
Educational notebooks, reproducible examples, and compact tools for teaching modern scientific Python.
Energy systems
Monitoring and management for renewable energy sites.
Softel Labs develops software for energy asset visibility: telemetry, performance analysis, anomaly detection, operational reporting, and management workflows for distributed renewable infrastructure.
Operational monitoring
Track production, inverter status, alarms, plant availability, and site-level health indicators.
Performance analytics
Detect underperformance, compare expected and measured yield, and surface patterns in plant telemetry.
Management workflows
Support reports, maintenance follow-up, asset views, and technical decision-making across plants.
Educational books
A library for science-first learning.
Educational books and course material are collected in the Softel Labs books index.
Python library
Sciveo brings scientific video workflows to Python.
Use Sciveo as the public package entry point for scientific video processing, visual analysis, and experimental media tooling.
pip install sciveoContact