Datalatte.ai
Part 1 - Proposal Submission
Name of Project:
Datalatte.ai
Proposal in one sentence:
We empower internet users to monetize their own data and provide data scientists with access to non-identifiable users’ data using an AI Feature Store at an affordable price.
Description of the project and what problem is it solving:
In the data-driven businesses, we see two types of pain points, those which affect data producers and those which affect data consumers.
Every day, internet firms harvest and monetize their users’ data. There is however no compensation for their digital labours. Since 2018, the general data protection regulation (GDPR) gives users (data producers) the right to access their personal data on each internet platform they use. Nethertheless, internet users (data producers) are often not aware how to take advantage of GDPR’s power, accessing and monetizing their data.
Meanwhile, to acquire and retain customers, as well as to grow their business, companies need to harness insights into their customers’ data. Data scientists (data consumers) are crucial in finding reliable data and building robust AI models to capture actionable insights. However, limited access to high-quality data often constrains model performance and data insights to meet business needs.
Our Datalatte DApp aims to relieve these two types of pain points. On one hand, Datalatte can enable internet users (data producers) to access and gather their data within a few clicks. On the other hand, Datalatte provides privacy-maintaining data features for data scientists (data consumers) to consume and build AI models. At the heart of our platform are the four core pillars: trust, intelligence, community support and usability…
Grant Deliverables:
Grant Deliverable 1:
- NFT marketplace frontend
- NFT generator backend
Grant Deliverable 2:
- MVP architecture backend implementation
Grant Deliverable 3:
- Development and conduction of unmoderated online surveys for a better understanding of product requirements and customer segments
- Creation of educational content on our web3 series, short stories for non web3 natives and communicating the content through multi-channels (Medium, Twitter).
Which category best describes your project? Pick one.
Unleash data
Which Fundamental Metric best describes your project? Pick one.
Data Consume Volume
What is the final product?
Figure 1. Illustration of Datalatte DApp platform.
The Datalatte is a DApp platform with two main stakeholders (Data Producers and Data Consumers), four core Datalatte functionalities (Audit Store, AI Feature Store, Data Advisor and Datalatte Catalog) and a Data Marketplace powered by Ocean Protocol.
Data Producers (Internet Users):
We provide a permission-less DApp for any internet user with full control over their data and funds. Users can first decide whether they would like to sell de-identified raw-data or data features (data grounded by Datalatte’s AI Feature Store). Based on users’ decisions, the Datalatte Audit Store will audit the data and estimate the data value based on data quality factors (including size, types, completeness, reliability, timeliness). The users can choose to get advice from the Data Advisor (an AI agent for maximizing data value) in increasing data value or proceed to Datalatte Marketplace to sell data.
Data Consumers (Data Scientist):
For data scientists, we provide a platform which enables access to de-identified raw-data or engineered data features (stored in Datalatte’s AI Feature Store), which are ready to be used as part of machine learning pipelines. By searching a Datalatte Catalog (a NoSQL database), a data scientist can select the data item (raw-data, engineered data features or feature engineering pipelines) and pay for the item at a reasonable price in the Datalatte Marketplace.
How does this project drive value to the “fundamental metric” (listed above) and the overall Ocean ecosystem?
Metric: “$ Data Token Consuming Volume”.
Initial target audience to appeal: Netflix young users (As of 2021, 45% of Netflix users are within our target age of younger than 35 years old, giving approx 95 million users).
Moreover, there are more than 5 million monthly active users on Metamask, as potential early adopters of using web3 DApps. By bringing 0.1% of those users (5000 users) to upload their viewing history at a valuation of 0.1$ for each user’s data (affordable to a data scientist to consume), we bring 500$ of data to the data marketplace. Kaggle has 5 million registered users which appeal to a rich dataset pipeline. By bringing only 0.0008% of data scientists at Kaggle, a total transaction volume of 20K$ (buck) is generated, to provide a ROI of at least 1.
To be fair in our ROI calculation, given that our proposal in round 9 got funded, we have to bring 0.0016% of the data scientists at Kaggle to bring the total ROI for round 9 and round 10 to at least 1. We believe once our MVP is ready to launch and with careful understanding of our users with surveys and interviews, this target is achievable in Q4 2021.
Funding Requested: (Amount of USD your team is requesting - Round 10 Max @ $20,000)
20,000$
Proposal Wallet Address: (must have minimum 500 OCEAN in wallet to be eligible. This wallet is where you will receive the grant amount if selected).
0xFe6adE773ed111BF9932f0e3a6722d52cbFe16e4
https://etherscan.io/address/0xFe6adE773ed111BF9932f0e3a6722d52cbFe16e4
Have you previously received an OceanDAO Grant (Y/N)? Yes
Team Website (if applicable): datalatte.ai
Twitter Handle (if applicable): datalatteAI
Discord Handle (if applicable): datalatte.ai
Project lead Contact Email: amirmabhout@gmail.com
Country of Residence: Germany
Part 2 - Team
Core Team:
Hossein Ghafarian Mabhout (Amir), PhD
- Role: Founder, CEO
- Relevant Credentials (e.g.):
- Linkedin: https://www.linkedin.com/in/amirmabhout/
- Medium: https://medium.com/@amirmabhout
- Twitter: https://twitter.com/AmirMabhout
- Background/Experience:
- 10 years circuit & system engineer
- 10 years IEEE member, 2 years standardization member in IEEE P802.3ch task force and 2 years IEEE student branch chair
- 5 years web3 experience
Kai Schmid, MSc
- Role: Co-founder, CMO
- Relevant Credentials (e.g.):
- Linkedin: https://www.linkedin.com/in/kai-schmid
- Background/Experience:
- 2 years experience as a startup coach
- Master’s degree in technology and product management
- Experiences in UX-Design and Online Marketing
Toktam Ghafarian, PhD
- Role: Co-founder, Head of AI development
- Relevant Credentials (e.g.):
- Background/Experience:
- 8 years Assistant prof. in Computer Engineering and AI Dep. at Khayyam Uni.
- 5 years Head of Computer Engineering and AI Dep.
- Research interests: Big data, Machine learning, Cloud computing.
Lukas Könen, MD
- Role: Co-founder
- Relevant Credentials (e.g.):
- Linkedin: https://www.linkedin.com/in/lukaskoenen/
- Background/Experience:
- 4 years medical doctor at Charite, Berlin in Dep. of Otolaryngology/Head- and Neck surgery
- 2 years Machine learning in medicine
- 5 years web3 experience
Extended team and advisors:
Mezli Vega Osorno, PhD
- Role: Advisor (Visual)
- Relevant Credentials (e.g.):
- Background/Experience:
- 3 years working at Apple as creative in digital arts and user-friendly environment
- La Maison Blanche #1 Award
- Freelancer in different art projects
Juanjiangmeng Du, PhD
- Role: Advisor (Technical)
- Relevant Credentials (e.g.):
- Linkedin: https://www.linkedin.com/in/dujjm
- Medium: https://medium.com/@dujjm
- Background/Experience:
- 10 years life science experience
- 5 years of computational experience
Karolina Baltulyte, MA
- Role: Team (Content)
- Relevant Credentials (e.g.):
- Background/Experience:
- 3 years experience as social media strategist at Little Sun NGO
- 6 years editing and film making experience as freelancer
Part 3 - Proposal Details (*Recommended)
Project Deliverables - Category
We summarize the details of our deliverables under Communication and Technical categories.
Communication
Bringing web3 technology into people’s everyday life is the vision for anyone in the web3 ecosystem. With the attraction that cryptocurrencies created in media, more and more people who were not necessarily familiar with web3 capabilities, are becoming aware of this new phenomena. However, since the first attraction created by cryptocurrencies was through creating wealth and value for web3 users, the general public who did not benefit equally in asset value appreciation, are skeptical of such technology. After conducting user interviews and bringing the idea behind web3 to more people, we realized that one of main challenges is to win the general public’s trust and understand users’ concern on data monetization .
Therefore, we decided to first develop and conduct unmoderated online surveys for a better understanding of product requirements and customer segments. These surveys will be rewarded with gift cards since non-native web3 users are not yet comfortable having their crypto custodian. In the meantime, Using our Medium channel, we continue to create content around new concepts born in web3 and in a simple and interactive way for people to read.
To make our content more visual and fun, we are working with a skilled Graphical Designer in Berlin, who is actively working on converting large blocks of content into engaging graphics. An additional part of the design is a company logo and an overarching design architecture that enables us to present a uniform design as an identifier for our brand across different platforms and attract more users.
Technical
NFT Marketplace
To better attract and connect with our early users, we adjusted our development strategy and are developing a data-driven NFT marketplace for our early users.
The back-end of our NFT marketplace architecture will be on Ocean-V4 update with the introduction of ERC-721. We aim to develop an MVP using Opensea for our test run.
MVP Architecture
Figure 2. An illustrative architecture to enable data flowing from users (data producers) to data scientists (data consumers)
An overview of the technology stack
- AWS
- Athena, DynamoDB, Data Lake
- EC2, ECS, Lambda
- SageMaker
- S3 and HDFS
- Data Science
- Python, Pyspark
- Scikit-Learn, TensorFlow, Transformers
- Matplotlib, Dash, Plotly, Keras
- APIs, Dashboards, Jupyter
- Web Development
- Next.js
- D3.js
- HTML
- CSS
- Web3
- IPFS
If the project includes community engagement:
- We have 13 engaged members on our discord server. We plan to grow our community within discord and once publishing the landing page, starting our campaign on Twitter and publishing relevant content on our Medium and website’s blog.
Project Deliverables - Roadmap
- Prior work:
Our summarized prior work is in the update posted on our Round 9 proposal:
-
What is the project roadmap?
Q4 2021:
- Communication
- Start website and social media campaign
- Create content (text & graphics) to introduce our vision
- Attract potential users
- Release business lightpaper
- Technical
- Release a MVP Web application for users to manually upload data to Datalatte
- Set up an Ocean-Protocol powered data marketplace
- Collect sample data from potential users
- NFT market place
- Develop an Data Audit store PoC on AWS
Q1 2022:
- Media/Communication
- Establish partnership with Ocean Protocol and launch Datalatte marketplace
- Expand social media campaign with AMA’s
- Release technical whitepaper
- Technical
- Release a MVP Web Dashboard for Data scientist to access Datalatte resources
- Develop a Data Advisor model on AWS
- Develop an AI Feature Store pipeline PoC on AWS
- Design a Data Catalog on AWS
Q2 2022:
- Media/Communication
- Establish partnerships and collaboration in data alliances and other projects in the ecosystem
- Technical
- Design legal APIs to collect users’ accessible but not exposed data with users’ permissions
- Enable users to select crypto/fiat currency and integration of DEX Swaps Plug-ins for ease of use for user to manage funds
- Integrate data sources to improve Datalatte AI pipelines
Q3 2022:
- Media/Communication
- Grow community through social media campaigns and ambassador program
- Technical
- Develop multi-chain wallet-connect
- Develop toward cloud-agnostic strategy to switch between cloud providers or to split workload between providers
- Expanding data sources to five ecommerce and social media platforms
- Release Datalatte mobile application in iOS and android app store
