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Logistics, Internet of Things (IoT)

XAIN

Xain - IoT network for enterprises

Rating: 3.6

Official contacts
Location: Berlin, Germany
Web-resources:   Whitepaper Website
Social networks:
Product source tracking: https://github.com/xainag
Details Description Risks Full analysis Team

Detailed review

Stage of product development
MVP and pilots for Porsche
Roadmap
December, 2018
Testnet
February, 2019
Launch of MVP (2nd upgrade)
July, 2019
Federated machine learning and Mainnet
December, 2020
Launch of MVP (3rd upgrade)
April, 2021
Launch of MVP (4th upgrade)
Token description
ICO date
TBA
Token price
N/A
Platform
XAIN
Blockchain
XAIN
Token distribution date
N/A
Consensus method
Proof of Kernel Work
Escrow
N/A
ICO currencies
USD , ETH , BTC
Bounty camping
N/A
Markets
N/A
Token functions
Payments and node reward.
Risks
MARKET

- Not deep competitors analysis but much work already done in B2B stream

PRODUCT

- MVP is not open-sourced yet

BUSINESS MODEL

- Weak token value in the network

FINANCES

- High estimated token pool valuation

- Lack of detailed financial information

TEAM

- Few team member with outstanding experience in widely known companies

Full analysis
Market

If we exclude details, XAIN appears to be an IoT blockchain network. Blockchain is rather a good fit for the growing IoT industries - it simplifies relations between devices and makes these relations more determined. A good point is that the team did not choose to promote XAIN to everyone and get focused on real testing and pilots. All the steps the team took indicate that XAIN is focused on B2B adoption on enterprises and facilities. The team won the Porsche Innovation Contest in 2017 (with 150 other participants) that helped to test the technology on Porsche's facilities. Other major partners include Porsche, Siemens, Mercedes, Infineon, DHL and NVIDIA to test the XAIN's solution (FROST network and FROST-based applications). Now the projects gathered enough data for next steps - larger adoption and further development. Also, the team provides with the competition analysis both noticing blockchain competitors and no-blockchain ones - the analysis does not clearly outline XAIN edge on competitors. Also, the team has its clear market entry strategy - reaching other enterprises, developers, signal providers and miners.

Product

The team provides with the following framework. 1) End-to-end hardware enforcement & secure delegation of access to machines in IoT networks, 2) Blockchain consensus enabling the secure delegation to actual data, 3) Federated Edge Processing contributing to the real-time decision making, 4) FROST protocol connecting the technologies above. In this way, FROST appears to be an IoT blockchain network. The consensus algorithm is Proof-of-Kernel-Work randomly selecting a committee for mining races - the team declares that this consensus will provide high scalability, sustainability. The product has been tested on Porsche facilities. The whitepaper includes deep technical details with strong ground for the implemented technical stack.

Business model

Token is used as frictionless payment for device and data access. Other nodes will be reached to establish higher decentralization in the network. The code will be open-sourced, but XAIN team will keep control under API. 

Finances

The fundraising strategy has rational ground - current fundraising round is based on previous investments been spect for testing and pilots for well-known enterprises. For now, XAIN confirms 6M USD committed (and 3.2M USD already received from VCs). According to gossips, the total token pool valuation will be over 40M USD. No other information is available.

Team

The team mainly in based in Germany, has over 30 members - 5 of them have PhD and more than the half is involved in tech. The project itself is called by the team a spinoff from Oxford University & Imperial College London. CEO - PhD in Computing, 1 year in Unicredit, 2 years in IBM (engineering), 2 years in Daimler (cryptographic engineer). CTO - 17 years of reading Computer Science and research in Imperial College. Project manager - 20 years in IT on management and analytics positions in not widely known companies. Machine Learning Lead - 9 years in Software development in not widely known companies. Other team members do not have the outstanding experience but still may be considered experienced. All the necessary streams are covered.

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