Detect satellite anomalies before they become mission-critical failures. soppo.space uses AI to monitor, predict and respond to anomalies in satellite telemetry - in near real time.

Discuss Your Mission Scenario

Satellite missions generate massive streams of telemetry data.

We turn this data into early warnings, clear insights and actionable alerts - powered by AI.

Detect anomalies before operators notice them.

Our AI models continuously analyze telemetry data to identify abnormal patterns invisible to rule-based systems.

Turn raw satellite telemetry into mission-saving decisions.

Because losing communication should never be the first sign of a problem.

A mission scenario

See how SOPPO.Space can help save a satellite mission

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ABOUT SOPPO

SOPPO.Space is developed by SOPPO - an experienced technology partner delivering advanced digital systems since 2009.

SOPPO is a European software and data engineering company specializing in complex web and mobile solutions.
For over 15 years, SOPPO has been building high-performance platforms across AI, big data, advanced analytics and real-time dashboards for international clients and R&D-driven organizations.

The SOPPO team combines strong engineering expertise with award-winning design and deep experience in data-intensive environments - from large-scale analytics platforms to predictive systems operating in real time.

SOPPO.Space is a natural extension of SOPPO’s capabilities into the space sector, created in response to real challenges faced by satellite operators, space agencies and research teams.

Learn more at soppo.eu

Have questions?

How does SOPPO.Space handle unknown or previously unseen anomalies?

SOPPO.Space is designed to detect not only known anomalies, but also unknown and emerging patterns.
Instead of relying solely on predefined rules or thresholds, the platform learns normal satellite behavior from telemetry data and identifies deviations in real time. This makes it possible to flag anomalies that have never been observed before — often at a very early stage.

Can SOPPO.Space be adapted to different satellite missions and payload types?

Yes. SOPPO.Space is mission-agnostic by design. The platform can be configured for different satellite architectures, subsystems and payloads by adjusting data models, telemetry inputs and alert logic. This makes it suitable for experimental missions, technology demonstrators, and operational satellites across various orbits and mission profiles.

Does SOPPO.Space replace existing ground systems or support them?

SOPPO.Space is built to complement, not replace, existing ground systems. It acts as an intelligent analytics layer on top of current telemetry pipelines, adding AI-driven anomaly detection, prediction and visualization. The platform integrates via standard interfaces and can work alongside mission control software already in use by operators.

What types of telemetry data does SOPPO.Space support?

SOPPO.Space supports time-series telemetry data from multiple satellite subsystems, including power, thermal, attitude control, communication and payload-related parameters. The platform is designed to ingest both structured and semi-structured telemetry streams and can be adapted to mission-specific data schemas.

What AI and analytics approaches are used for anomaly detection?

SOPPO.Space combines statistical analysis, machine learning models and time-series pattern recognition. The system focuses on unsupervised and semi-supervised methods, allowing anomaly detection even when labeled historical failure data is limited or unavailable. Models continuously adapt as new telemetry data becomes available.

How is data latency and processing performance handled?

The platform is designed for near real-time processing of telemetry streams. Data ingestion, feature extraction and anomaly scoring are optimized for low-latency pipelines, enabling fast alerting and visualization. The architecture supports horizontal scaling to handle increasing data volumes and higher telemetry frequencies.

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