# Miele Venture

> Miele Venture is a VC fund backing Machine Learning, Apps and Software. See 4 investments, check sizes, portfolio. Updated Aug 2026.

- Type: VC Fund
- Total investments: 4
- Last investment: Sep 2024
- Lead investor: 0%
- Last updated: Aug 2026

Miele Venture is a venture arm of Miele Group.

## Round sizes

| Stage | Round size |
| --- | --- |
| Seed | $1.8M–$3M |

## Investment focus

### Industry

| Industry | Investments | Share |
| --- | --- | --- |
| Machine Learning | 2 | 50% |
| Apps | 1 | 25% |
| Software | 1 | 25% |
| Wellness | 1 | 25% |
| Biometrics | 1 | 25% |

13 industries tracked in total.

### Stage

| Stage | Investments | Share |
| --- | --- | --- |
| Seed | 2 | 50% |
| Pre-Seed | 1 | 25% |
| Venture - Series Unknown | 1 | 25% |

### Country

| Country | Investments | Share |
| --- | --- | --- |
| Austria | 1 | 25% |
| Denmark | 1 | 25% |
| United Kingdom | 1 | 25% |

## Investments

| Company | Description | Amount | Stage | Date | Website |
| --- | --- | --- | --- | --- | --- |
| HELLO INSIDE | HELLO INSIDE is a scientific self care company empowering people to have data-driven conversations with their bodies so everybody can unlock their best self. Our mission is to lead a new self care movement that’s data driven, truly personalized and rooted in science by building the world's leading scientific self care company. HELLO INSIDEstarts by using continuous glucose monitors to help people better understand different challenges in life as their body and health needs evolve.We at HELLO INSIDE are committed to creating a healthier and happier future for people and communities through the power of scientific self care. | $1.8M | Seed | Sep 09, 2024 |  |
| V7 | V7 is a powerful AI training data platform that enables you to annotate images, videos, documents, and medical imaging files. It is the quickest way to obtain high-quality annotated data for training your computer vision models. You can utilize auto-labeling features to accelerate your annotation projects, manage your MLOps workflows, or hireprofessional annotators for assistance. With advanced auto-labeling, quality assurance (QA), and team collaboration tools, V7 will help you reduce your data annotation time by 10x and assist you in developing more accurate AI solutions. Annotate any dataset with ease and seamlessly integrate V7 into your training data management and model development pipeline. You can seamlessly integrate V7 with your existing tech stack and import/export annotations with ease. Additionally, V7 empowers you to have complete control over your models, tasks, and datasets through the open API, Darwin-py SDK, and CLI. | $3M | Seed | Dec 18, 2020 |  |
| V7 | V7 is a powerful AI training data platform that enables you to annotate images, videos, documents, and medical imaging files. It is the quickest way to obtain high-quality annotated data for training your computer vision models. You can utilize auto-labeling features to accelerate your annotation projects, manage your MLOps workflows, or hireprofessional annotators for assistance. With advanced auto-labeling, quality assurance (QA), and team collaboration tools, V7 will help you reduce your data annotation time by 10x and assist you in developing more accurate AI solutions. Annotate any dataset with ease and seamlessly integrate V7 into your training data management and model development pipeline. You can seamlessly integrate V7 with your existing tech stack and import/export annotations with ease. Additionally, V7 empowers you to have complete control over your models, tasks, and datasets through the open API, Darwin-py SDK, and CLI. | $3M | Pre-Seed | Dec 18, 2020 |  |
| Plant Jammer | We invite ourselves into people's home kitchens, to change the food system from the front. We believe that better food habits in homes will create a more sustainable planet. We believe a sustainable food chain is plant-based and minimizes foodwaste, so we’re making the world’s best cooking assistant… that happens to be vegetarian. We are ateam of 8 software developers and 2 food scientists, and we want to be the planet’s best company at combining data science and food science. | $4.7M | Venture - Series Unknown | Aug 13, 2020 |  |

4 of 4 investments shown.

## Co-investors
- [Air Street Capital](https://shizune.co/investors/profile/air-street-capital) — VC Fund, 2 deals together
- [Amadeus Capital Partners](https://shizune.co/investors/profile/amadeus-capital-partners) — VC Fund, 2 deals together
- [Partech](https://shizune.co/investors/profile/partech) — VC Fund, 2 deals together
- [Verge HealthTech Fund](https://shizune.co/investors/profile/verge-healthtech-fund) — VC Fund, 2 deals together
- [10x Founders](https://shizune.co/investors/profile/10x-founders) — VC Fund, 1 deal together
- [DocMorris](https://shizune.co/investors/profile/docmorris) — VC Fund, 1 deal together

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### Similar industry
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### Similar stage
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### Similar country
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- [Seed Capital](https://shizune.co/investors/profile/seed-capital) — VC Fund

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## FAQ

### What does Miele Venture invest in?

Miele Venture invests primarily in Machine Learning, Apps and Software startups, most often at Seed and Pre-Seed stage. Most of the 4 investments tracked by Shizune back companies in Austria. The Investment Focus section breaks down every industry, stage and country in the portfolio.

### What is Miele Venture's check size?

Miele Venture typically joins rounds of $1.8M–$3M at Seed. These ranges are 10th–90th percentile round sizes calculated from confirmed public funding rounds, so they are a realistic guide to the rounds Miele Venture participates in.

### When did Miele Venture last invest?

The most recent investment recorded for Miele Venture closed in Sep 2024. Shizune tracks 4 investments in total for this profile, including round sizes, stages and portfolio companies, all sourced from confirmed public funding rounds and refreshed monthly.

### Is Shizune's investor data accurate?

Yes — every stat on this profile is calculated from confirmed public funding rounds monitored across hundreds of sources since 2020. This profile was last refreshed in Aug 2026 and is updated monthly. Spotted something off? Use the “Suggest an edit” link near the top of the page.

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