Exabel
The simple-to-use platform for investment professionals who want to benefit from alternative data and modern data science insight in their investment process.
| Date | Investors | Amount | Round |
|---|---|---|---|
| - | investor investor | €0.0 | round |
| N/A | €0.0 | round | |
| investor | €0.0 | round | |
| investor investor investor investor investor investor investor | €0.0 | round | |
| investor | €0.0 Valuation: €0.0 860.0x EV/Revenue -11.4x EV/EBITDA | round | |
| investor | €0.0 | round | |
| investor | €0.0 | round | |
| investor | €0.0 | round | |
| investor | €0.0 | round | |
* | N/A | Acquisition | |
| Total Funding | 000k | ||
| EUR | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|---|
| Revenues | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
| % growth | - | - | 1072 % | 363 % | 158 % | 239 % | 5 % |
| EBITDA | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
| % EBITDA margin | - | (82677 %) | (7558 %) | (1706 %) | (1373 %) | - | - |
| Profit | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
| % profit margin | - | (81886 %) | (7589 %) | (1700 %) | (1368 %) | (657 %) | (287 %) |
| EV | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
| EV / revenue | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x |
| EV / EBITDA | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x | 00.0x |
| R&D budget | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 | 0000 |
Source: Company filings or news article
Related Content
Exabel, a Norwegian financial technology company founded in 2016 by Øystein G. Meyer and Karl Oskar Teien, provides an AI and data analytics platform tailored for investment teams. The company's inception was driven by the founders' shared background in quantitative analysis and technology; Teien, the current CEO, previously held roles as a senior quantitative analyst and holds a PhD in theoretical physics, while Meyer, the CTO, has extensive experience in software engineering and data science, including a tenure at Yahoo. Their combined expertise shaped the development of a platform designed to make alternative data more accessible and actionable for financial professionals.
The firm targets a clientele of hedge funds, asset managers, and other institutional investors who are looking to integrate non-traditional data sources into their investment decision-making processes. Exabel operates within the growing market of alternative data analytics, where the challenge often lies not in data acquisition, but in its effective interpretation and integration with existing financial models. The business model is primarily subscription-based (SaaS), offering access to its platform which allows clients to blend their proprietary data with datasets from Exabel's partners.
The core offering is a comprehensive analytics platform that facilitates the entire data workflow, from organization and analysis to visualization. Key features include data modeling tools, AI-powered predictive analytics, and customizable dashboards. A significant selling point is the platform's ability to help investment teams build 'data-driven conviction' by testing investment theses against various data sets. By providing a structured environment to explore and extract insights from complex alternative data, Exabel aims to level the playing field, enabling a broader range of investment firms to leverage big data without the need for extensive in-house data science teams.
Keywords: alternative data, investment analytics, financial technology, SaaS, data modeling, asset management, hedge funds, predictive analytics, fundamental analysis, data visualization