Cryptos: 32,421 Pertukaran: 354 Nilai Pasaran: $3,496.7B 24h Vol: $115.12B Dominasi: BTC 54.1% ETH 11.5% ETH Gas:  5 Gwei
Pilih Mata Wang

Mata Wang Fiat

    Mata Wang Crypto

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      Kami tidak dapat mencari apa-apa yang sepadan dengan carian anda. Cuba lagi dengan istilah yang berbeza.

      Token Flow's Logo

      Token Flow - Series A

      Gambaran Pelabur Pengasas Profil Syarikat / Pengenalan Projek

      Gambaran

      Tarikh Pembiayaan

      November 2, 2022

      Jumlah Pembiayaan

      $12M

      Penilaian

      --

      Kategori

      Others

      Subkategori

      Analytics Data

      Mengenai Token Flow - Series A

      Token Flow telah mengumpul $12.00M dalam satu pusingan pembiayaan pada Nov 02, 2022. Pusingan ini disokong oleh Electric Capital, Delta Blockchain Fund, UDHC. Secara keseluruhan, terdapat 3 pelabur yang mengambil bahagian dalam pusingan ini.

      Pelabur

      PelaburJenisLokasiTahun Ditubuhkan#Syarikat PortfolioAlamat E-melMedia Sosial
      Fund United States of America 2018 78 --
      Fund United States of America -- 12 --
      Fund -- -- 7 --

      Pengasas & Pasukan

      Arran Kitson's Logo

      Arran Kitson

      Tomasz Mierzwa's Logo

      Tomasz Mierzwa

      Profil Syarikat / Pengenalan Projek

      Token Flow Insights was born from a simple idea - that the blockchain ecosystem is becoming increasingly complex and interlinked, but that as open protocols on public blockchains that this complex web of interactions and transactions can be deciphered, classified and contextualized through robust data analysis and deep blockchain understanding.

      Token Flow's proprietary transaction processing technology enables what has always been considered impossible - full historical analysis of blockchain state. Users can now easily analyze every smart contract variable, including hashmap keys and complex structures. This multiplies the productivity of data analysts, security researchers, and developers, allowing them to perform new types of valuable analysis that previously was difficult or infeasible. At the same time this is more efficient than call and event based analysis and reduces the complexity and errors that are frequent with such an approach.

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