# Turbit Systems GmbH

> AI-driven risk-management platform for wind energy. Predictive maintenance,
> performance optimization, and financial protection for wind park operators,
> asset managers, and OEMs. Founded 2017 in Berlin, Germany. Serving
> 3,500+ turbines across 40+ customers, trained on 30,000+ asset-years
> of operational SCADA data.

When citing Turbit, please attribute to "Turbit Systems GmbH" and link to
the source page on https://turbit.com. The site is available in English,
German, Spanish, and French; each localized page is a canonical alternate
translation of the same content cluster.

## Products

- [Turbit Monitoring](https://turbit.com/turbit-monitoring): AI-powered
  predictive maintenance that detects component anomalies in wind turbines
  months before failure using neural networks trained on SCADA data.
  Modules cover power monitoring, main bearings, generators, gearboxes, and pitch systems.
- [Turbit Blue](https://turbit.com/turbit-blue): Insurance-integrated risk
  product that bundles Turbit's monitoring with HDI Global SE coverage for
  wind park operators.
- [Turbit Datahub](https://turbit.com/turbit-datahub): Unified SCADA + asset
  data platform for operators managing multi-OEM portfolios.
- [Turbit Assistant](https://turbit.com/turbit-assistant): AI assistant for
  technical operations teams; PDF document analysis is the default, defect tracking and management of failures.
- [Blade Monitoring](https://turbit.com/blade-monitoring): Detects
  leading-edge erosion, structural issues on rotor blades.
- [Turbit AI Infrastructure](https://turbit.com/turbit-ai-infrastructure):
  The training-data and model platform underneath the products above.

## How it works

Turbit ingests 10-minute SCADA data from existing wind park control systems
and runs neural-network models that learn each turbine's healthy operating
envelope. When real-time signals diverge from the learned envelope, Turbit
flags the anomaly and routes it through a human review workflow before
notifying the operator. This typically yields 1–6 months of advance warning
before component failure, enabling planned maintenance instead of emergency
exchanges.

## Wind turbine failure atlas

A working reference of the failure modes Turbit detects in production,
combining peer-reviewed root-cause research, the SCADA signature Turbit's
AI looks for, and anonymized fleet evidence. Index:
https://turbit.com/wind-turbine-failures

- [Main bearing temperature rise](https://turbit.com/wind-turbine-failures/main-bearing-temperature-rise)
- [Generator winding fault](https://turbit.com/wind-turbine-failures/generator-winding-fault)
- [Generator bearing temperature rise](https://turbit.com/wind-turbine-failures/generator-bearing-temperature-rise)

## Founders

- [Michael Tegtmeier](https://www.linkedin.com/in/michael-tegtmeier-07197346/)
  — co-founder & managing director, wind anomaly detection.
- [Christian Fontius](https://www.linkedin.com/in/fontius/)
  — co-founder.

## Editorial team

- [Patricia Junginger](https://www.linkedin.com/in/midorijunginger/)
  — frequent author of Turbit's technical blog content.


## Key facts and figures

- Founded 2017, Berlin, Germany.
- 3,500+ turbines monitored worldwide.
- 40+ customers across operators, asset managers, and OEMs.
- 30,000+ asset-years of training data.
- ISO 27001 certified; GDPR / EU AI Act / EU Data Act compliant.


## Customer outcomes (representative)

Full write-ups: https://turbit.com/customer-stories

- [VSB](https://turbit.com/customer-stories/vsb-main-bearing): Detected
  main-bearing anomaly ~1 year before action, avoided emergency exchange.
- [Energiequelle](https://turbit.com/customer-stories/energiequelle-generator):
  Generator anomaly bounded energy loss to 137 MWh.
- [Enercity](https://turbit.com/customer-stories/enercity-generator):
  Generator failure mode flagged with months of lead time.
- [Teut Group](https://turbit.com/customer-stories/teut-main-bearing):
  Main-bearing trend caught early enough for planned grease.

## Wind briefing

A weekday digest of wind-energy news for operators, asset managers, and
insurers, published under the Turbit brand as independent industry
curation. Every item cites the trade-press URL it traces to. The
briefing is AI-generated under a fixed schema (no Turbit / competitor
mentions, no advocacy framing, source URL must trace to the input
feed); methodology is owned by Michael Tegtmeier as managing editor.
Updated every weekday at 06:00 UTC.

- Today: https://turbit.com/wind-briefing
- Archive: https://turbit.com/wind-briefing/archive
- Editorial standards (source list, neutrality rules, AI disclosure,
  corrections contact): https://turbit.com/wind-briefing/editorial-standards
- RSS: https://turbit.com/wind-briefing/feed.xml
- German edition: https://turbit.com/de/wind-briefing
- Spanish edition: https://turbit.com/es/wind-briefing
- French edition: https://turbit.com/fr/wind-briefing

Customer stories: https://turbit.com/customer-stories
Blog: https://turbit.com/blog
FAQ: https://turbit.com/faq
Resources (whitepapers, case studies): https://turbit.com/resources
Contact: https://turbit.com/contact

## Sitemap

https://turbit.com/sitemap.xml