This documentation provides detailed information about the various data fields used in the system, including descriptions, examples, and the fields' availability in CSV/Zapier and Frontend (FE) interfaces.

For each data field we provide:

  • the name of the field
  • the description of the content
  • sample data of the content
  • is it contained in our CSV download / Zapier API: Yes / No
  • is it displayed in our front end / web app: Yes / No

1. company_name

  • Field Description: Name of the company
  • Example: Swiss-Mile
  • In CSV/Zapier: Yes
  • In FE: Yes

2. description_short

  • Field Description: Different kinds of descriptions. Only one is displayed in the FE. They trump each other in this order of availability: LLM --> long --> short.
  • Example: We collect insights and ease labor by connecting AI with the physical world using autonomous machines.
  • In CSV/Zapier: Yes
  • In FE: Yes

3. description_long

  • Field Description: Detailed description of the company.
  • Example: Swiss-Mile, a deep tech spin-off from ETH Zurich, collects insights and eases labor by connecting the physical and digital worlds using autonomous machines. Mobile robots have vast potential, but many lack the ability to effectively navigate obstacles, move over large distances, and carry significant loads. Moreover, their reasoning capabilities often limit widespread adoption. Therefore, we introduce AI-driven wheeled-legged robots to bridge this gap. Our patented design combines the best of wheels and legs, allowing the transport of payloads and sensors across vast distances, even on challenging terrains. As AI advances in interpreting online content, we anticipate AI systems requiring versatile embodiments and real-world reasoning, exemplified by our robot and its autonomy in dynamic urban settings. Furthermore, we go beyond technology, integrating customer-centered services into our offerings.
  • In CSV/Zapier: Yes
  • In FE: Yes

4. description_llm

  • Field Description: LLM generated description.
  • Example: Swiss-Mile Robotics AG is a spin-off from ETH Zurich, founded in April 2023, with the vision to create an effortless future. The company focuses on developing wheeled-legged robots with embodied AI, designed for speed, efficiency, and versatility in various industries. Their solutions include the Robotic Mule for carrying and the Robotic Watchdog for monitoring, with applications in last-mile delivery, construction, and security. The technology is a result of six years of pioneering research in robotic intelligence and wheeled-legged robots at ETH Zurich, and the company is backed by a team of experienced co-founders and advisors.
  • In CSV/Zapier: No
  • In FE: Yes

5. city

  • Field Description: Company/headquarters location.
  • Example: Zurich
  • In CSV/Zapier: Yes
  • In FE: Yes

6. country

  • Field Description: Company/headquarters location.
  • Example: Switzerland
  • In CSV/Zapier: Yes
  • In FE: Yes

7. incorporation

  • Field Description: The year of the company incorporation.
  • Example: 2023
  • In CSV/Zapier: Yes
  • In FE: Yes

8. industry

  • Field Description: High-level (45 tags) and detailed-level industry categories (750+ topic tags).
  • Example: Artificial Intelligence, Content, Data and Analytics, Design, Hardware, Information Technology, Manufacturing, Media and Entertainment, Mobile, Robotics, Science and Engineering, Software, Transportation
  • In CSV/Zapier: Yes
  • In FE: Yes

9. company_followers

  • Field Description: Approximate (in brackets - exact when available) number of company social media followers.
  • Example: Over 2000 followers (2896)
  • In CSV/Zapier: Yes
  • In FE: Yes

10. company_size

  • Field Description: Approximate number of company employees (in brackets - total number of employees that we have detailed information for).
  • Example: Employee number unknown (32)
  • In CSV/Zapier: Yes
  • In FE: Yes

11. startup_rating

  • Field Description: ML rating estimating the probability of the company being a startup and not a small business.
  • Example: 79.00%
  • In CSV/Zapier: Yes
  • In FE: No

12. website

13. email

  • Field Description: Company emails.
  • Example: info@swiss-mile.com
  • In CSV/Zapier: Yes
  • In FE: Yes

14. linkedin

15. twitter

16. facebook

17. founding_team

18. investment_stage

  • Field Description: Investment stage that the company is currently in/has passed.
  • Example: Seed
  • In CSV/Zapier: Yes
  • In FE: Yes

19. funding_stage

  • Field Description: Has the company been funded and if yes, then when:
    • Funded: was funded, but we don't know exactly when
    • Funded 3 months ago: funded between 3 and 5 months ago
    • Funded 6 months ago: funded between 6 and 8 months ago
    • Funded 9 months ago: funded between 9 and 11 months ago
    • Funded 12 months ago: funded between 12 and 14 months ago
    • Funded 15 months ago: funded over 15 months ago
    • Not funded: was not funded, according to our knowledge
  • Example: Funded 6 months ago
  • In CSV/Zapier: Yes
  • In FE: Yes

20. company_highlights

  • Field Description: Various highlights that we can label a company with:
    • clients_rate_positive: when we see that a company had been saved in another client's opportunity or watchlist
    • funding_2m: total funding received is 2m-10m USD
    • funding_10m: total funding received is 10m-50m USD
    • funding_50m: total funding received is over 50m USD
    • founding_team_more_than_1: the company has more than one founder
    • has_serial_entrepreneur_founder: one of the company founders has also a track record of incorporating other startups
    • has_female_founder: when one of the company founders is female
    • only_female_founders: when all of the company founders are female
    • has_young_team: the median age of the team is under 35 years old
    • has_phd_founder: one of the founders has a PhD title
    • has_top_uni_founder: one of the founders studied at a top 100 university
    • has_strong_tech_education_employee: one of the founders or employees has a PhD or Masters in STEM subjects
    • has_strong_soft_dev_education_employee: one of the founders or employees has a PhD or Masters in Software development
  • Example: clients_rate_positive, founding_team_more_than_1, funding_2m, has_phd_founder, has_top_uni_founder, has_serial_entrepreneur_founder, has_young_team, has_strong_tech_education_employee
  • In CSV/Zapier: Yes
  • In FE: Yes

21. digest_date

  • Field Description: Which date or week we attribute the discovery to.
  • Example: 2024-01-10T22:05:53Z
  • In CSV/Zapier: Yes
  • In FE: No

22. digest_week

  • Field Description: The week of the digest.
  • Example: 2024-02
  • In CSV/Zapier: Yes
  • In FE: Yes

23. created_on

  • Field Description: Date of CSV creation.
  • Example: 7/3/2024 9:02:46 AM
  • In CSV/Zapier: Yes
  • In FE: No

24. funded_tag

  • Field Description: Repetition of funding_stage.
  • Example: Funded 6 months ago
  • In CSV/Zapier: Yes
  • In FE: No

25. Customer Problem

  • Field Description: The problem or customer need the startup plans to solve.
  • Example: Labor shortages, high costs, human safety, and mundane tasks in various industries.
  • In CSV/Zapier: No
  • In FE: Yes

26. Target Customer

  • Field Description: Description of the customer base the company targets.
  • Example: Industries looking to optimize processes, cut costs, and enhance safety through autonomous robots.
  • In CSV/Zapier: No
  • In FE: Yes

27. Business Model

  • Field Description: The company's operational model (e.g., B2B, subscription-based).
  • Example: {B2B, Manufacturing}
  • In CSV/Zapier: No
  • In FE: Yes

28. all top unis

  • Field Description: List of top universities where the founders and employees of the startup have studied.
  • Example: uni_eth, uni_tohoku
  • In CSV/Zapier: No
  • In FE: No

This documentation outlines the structure and content of the data fields used for company profiles, providing clarity on their purpose and usage in different interfaces.