# Overview

AI has transformed how we process information, make strategic decisions, and engage with technologies.

Next Gem aspires to be at the forefront of this revolution by introducing a new era in crypto data research and analysis: We are building a set of software and tools monitored by the best curated LLM artificial intelligence to access all Web3 project data directly on their pre-launch & launch stage and providing our community efficient ways to invest in the most promising crypto projects, on any existing blockchain.

<figure><img src="https://4237869073-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F9pSU9vD3TIixHtjn35n1%2Fuploads%2FFYJzHlq0hF2BXkd4Wdjp%2FScreenshot%202024-01-24%20at%201.55.53%E2%80%AFPM.png?alt=media&amp;token=f3a0f5b9-d6f8-4651-9106-6ec69b71fb96" alt=""><figcaption></figcaption></figure>

<table data-view="cards"><thead><tr><th></th><th></th><th></th></tr></thead><tbody><tr><td><a href="/introduction/apeing-efficiently">Apeing Efficiency</a></td><td>Introduction to the core motive of the platform to make apeing/investing efficient</td><td></td></tr><tr><td><a href="/introduction/analysing-and-reacting">Analysing &#x26; Reacting</a></td><td>How the protocol &#x26; AI analyses and reacts with data</td><td></td></tr><tr><td><a href="/technology/llm-with-efficiency">LLM With Efficiency</a></td><td>Calculation of various factors and weightage by LLM to score projects appropriately and find best gems</td><td></td></tr><tr><td><a href="/technology/web-data-scraping">Web Data Scraping</a></td><td>Sourcing of data of new or existing tokens</td><td></td></tr><tr><td><a href="/technology/next-gem-ais-custom-llm">Custom NextGem LLM</a></td><td>Engage with the Custom NextGemAI LLM to inquire about specific data within the project dataset</td><td></td></tr><tr><td><a href="/technology/premium">Premium</a></td><td>Subscribe &#x26; Burn $NextGem to access to premium features </td><td></td></tr><tr><td><a href="/vision/roadmap">Roadmap</a></td><td>Vision of the protocol development</td><td></td></tr><tr><td><a href="/token-economy/usdgemai-token">Token Economy</a></td><td>$NextGem tokenomics &#x26; utility </td><td></td></tr><tr><td><a href="/token-economy/usdgemai-token-sale-and-launch-plan">Tokensale &#x26; Launch Plan</a></td><td>Plan for Fundraising &#x26; $NextGem Launch</td><td></td></tr></tbody></table>


# Introduction


# Apeing Efficiently

Web3 ecosystem moves fast, and investing in new projects is what most of us do without the correct knowledge, leading to bad decisions more often than good ones. Due diligence is sometimes complicated, especially if you are not an expert in the area of the particular gems.\
\
At the beginning of or during the bull run, everyone rushes to take entries in the most innovative, and promising projects with trending narratives. However, the smartest people have already aped in their bags during the bear market or before the hype of the project began during the bull market, and are waiting to follow the success of their entries. They are usually the most successful because they take time to analyse, deep-dive into the details of the project, and make all the necessary efforts to understand what they are getting involved in. This is what differentiates a pro from a beginner. Instead of waiting for the news to be published by the big ventures or KOLs, missing the correct timing for apeing, and losing your portfolio because of FOMO becoming someone else's exit liquidity, you need to act before and position yourself as a pioneer by correctly putting in the time and effort.\
\
Only some people can do it or have the necessary knowledge to do so, but fortunately, we do know someone who knows everything to help you: artificial intelligence. Understanding Web3 project data, looking into the details of token economics or the technical aspects like reading and understanding intelligent contracts, and knowing everything about hundreds of projects regularly is challenging and takes a lot of time. Keeping up with the latest trends and being able to follow them is rewarding for those who have the experience, even though it’s hard to get all the information from different sources. \
\
This is where Next Gem AI comes in places: we extract all information we can find on any existing or new projects that are being created in the crypto ecosystem by taking the best possible accurate data, and we feed the most intelligent AI to make that work for us, analyse and score them based on pre-existing rules (*as shown in the figure below*).

<figure><img src="https://4237869073-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F9pSU9vD3TIixHtjn35n1%2Fuploads%2FmmWkutlfBmo9ALBpwkFF%2FScreenshot%202024-01-24%20at%204.44.22%E2%80%AFPM.png?alt=media&amp;token=5662348c-907c-436b-aaa9-9b9ae89e74d3" alt=""><figcaption><p>App dashboard on <a href="https://thenextgem.ai/gems">https://thenextgem.ai/gems</a></p></figcaption></figure>


# Analysing & Reacting

Our ambition is to be the premier platform for analysis and investments, providing a rapid and reliable source of information for all current and emerging crypto projects. We aspire to be the go-to resource, similar to how CoinMarketCap is the benchmark for price tracking.

Here are some of the factors analyzed by Next Gem AI for each token:

1. **Project Documentation:** AI analyzes whitepapers and official documents to understand project objectives and technology.
2. **Market Data**: Assesses real-time market trends to gauge current performance and potential
3. **Blockchain Transactions**: Review smart contract activity for signs of security and functionality.
4. **Community Sentiments:** AI evaluates social media and community forums to measure user sentiment and engagement.
5. **Tokenomics:** Examines the token distribution, utility, and economic model to determine the project’s financial viability.
6. **Code Analysis:** Scrutinizes the Github source code to identify originality and adherence to quality standards.

\
We analyze each project’s information through the biggest LLM available networks and summarize an average score on our platform. When we have all the artificial intelligence results computed, we fine-tune our agent by sending all the information pieces treated by all the models, allowing us to directly interact with the precise thoughts and responses of each. We want to improve the quality of due diligence research by effectively summarizing the most filtered data, removing the extra noises, and giving a score note to help you on your investment journey. While our platform utilizes the most advanced technology of our time to dig potential in various projects, its effectiveness depends on proper usage and vigilant market responsiveness.&#x20;

We provide tools to filter out promising projects, but as with any powerful tool, it requires careful application and cannot guarantee success in any venture. A more concrete example, which is much harder for a human to filter and not be misled by malicious actors, concerns the authenticity of community engagement.&#x20;

The most advanced Large Language Models (LLMs) currently on the market can apply sentiment and text content analysis to provide factual information about a project’s community. They quickly help to determine whether participants in a discussion, such as in a Telegram group, are genuine humans or bots. They assess whether these members are engaged or simply waiting for an airdrop or campaign rewards and distinguish between paid individuals feigning activity and genuinely enthusiastic members who are passionate about the project; this is analyzed by Next Gem AI.


# LLM With Efficiency

<figure><img src="https://4237869073-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F9pSU9vD3TIixHtjn35n1%2Fuploads%2FD7mx3ElrGxVp5mBwflU1%2FScreenshot%202024-01-24%20at%201.54.38%E2%80%AFPM.png?alt=media&amp;token=ef8323fc-9c81-4e4f-9a75-ba0395a5a2c7" alt=""><figcaption></figcaption></figure>

LLMs, by definition, are text-based language models trained on existing data with billions of parameters. Given the current state of technology, they may not be pertinent for real-time information analysis, such as evaluating a new crypto project that emerged two weeks ago; they must be assisted or supplemented to leverage their intelligence effectively.&#x20;

All existing stored data from all crypto projects that we retrieve on the Internet is computed in the Next Gem AI MongoDB database, sent and processed by the most powerful AI models available on the market today; here is a non-exhaustive list of them: GPT4, GEMINI AI, MISTRAL AI, GROK AI. We categorize projects using these models based on defined criteria and pre-set rules trained and reviewed both by the AI themselves and experts in the crypto investing industry. Each model evaluates the overall reliability of a project and assigns a score to each one, utilizing a comprehensive data set. They are continually updated with all available information we can gather from the project’s website, documentation, papers, and more.

Our LLM back-end processes are developed in C# language or Node.JS (Typescript). We interact with the APIs of each AI company, sending them the extra data extracted from the [scrapper](/technology/web-data-scraping) (see section below): they are executed in a safe environment in cloud instances. Some extra instructions are provided to give them specific tasks, knowing what they have to do precisely: known as assistants, we use a relatively low LLM temperature to avoid creative outputs and ensure the models do as taught & instructed. The software process related to the AI's interaction waits for new projects to be sent to their execution state through internal HTTP requests for specific requests demands or select the fresh one on our MongoDB database directly by filtering projects not analyzed yet by each model we implement.\
\
To determine the final score of each project, here is a summary of the mathematical equation used to calculate it:<br>

$$
Project Score = ∑\_{i=1}^{n} ωi \cdot fi
$$

\
Where:\
• n is the total number of rules or factors (in this case 15: Team and Founders" Background, Technology, and Innovation, etc.).

• ωi is the weight assigned to the iᵗʰ factor, reflecting its importance in the overall analysis. The weights should be determined based on the relative importance of each factor to the success of crypto projects.

• fi is the score assigned to the iᵗʰ factor for a particular project, based on its performance or status in relation to that factor.

Each factor score fi is multiplied by its corresponding weight ωi, and then all these weighted scores are summed to produce the total project score. This approach allows for a nuanced and comprehensive assessment of each project, taking into account a wide array of critical success factors. The higher the Project Score, the more favorable the project is considered based on the analysis criteria.

<br>


# Web Data Scraping

<div align="center" data-full-width="false"><figure><img src="https://4237869073-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F9pSU9vD3TIixHtjn35n1%2Fuploads%2FoixsdPJvfV7ue2T93AAu%2FScreenshot%202024-01-24%20at%204.56.54%E2%80%AFPM.png?alt=media&amp;token=cd57a74b-0539-4bb0-8528-74373f90ba1e" alt="" width="302"><figcaption></figcaption></figure></div>

The initial layer compiles an exhaustive list of new and existing crypto projects. This involves parsing data from various sources, both centralized, like CoinMarketCap, and decentralized, such as newly created launchpad pools, etc.&#x20;

The first filtering stage employs complex regular expressions to extract datasets containing the essential information needed for accurate further analysis. We have developed programs in Node.JS (Typescript) that simulate a web browser environment to accomplish this. These programs navigate various website sources, seeking out new projects in real time. They also connect via RPC with blockchain smart-contract flows, such as Ethereum pre-sale launchpad smart contracts, which sometimes provide new or additional textual information that we extract. Once we’ve gathered the essential information for a new project, it’s stored in our MongoDB database and then moved to the second layer of the web data processor. With the foundational data established — the information the project team wants public — we delve deeper, extracting details like community information.&#x20;

The next step for the second layer involves going directly to the project’s website to collect all text and image information from every page, along with any documentation, GitBooks, whitepapers, and team details.&#x20;

We temporarily store all found information on our servers, then apply an algorithm known as *Levenshtein distance* to ensure the accuracy and uniqueness of the information, avoiding duplication of any data already present.&#x20;

Additionally, the roadmap is thoroughly analyzed to extract all possible milestones, assessing the ambition of the team’s vision. The token economics are also carefully reviewed, detailing aspects such as the presence of an associated token, its utility, and the circulating supply at the Token Generation Event (TGE), among other factors. We aim to extend our web data analysis to include scrutinizing the GitHub source code from the project’s public repository. By submitting samples to AI models, we intend to prevent the replication of other projects and ascertain whether a certain quality standard has been met.


# Next Gem AI's Custom LLM

<figure><img src="https://4237869073-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F9pSU9vD3TIixHtjn35n1%2Fuploads%2FlQZOfbb89NScOjuGToxm%2FScreenshot%202024-01-24%20at%204.59.45%E2%80%AFPM.png?alt=media&amp;token=7e60d428-6143-4c83-8509-1b17ad9ea500" alt="" width="375"><figcaption></figcaption></figure>

By customizing a Large Language Model (LLM), we aim to refine our initial output and enhance the value returned to our users. We store all the information processed by various AI systems in our MongoDB database.&#x20;

This allows us to create a specialized version of the LLM that is well-informed about the collective knowledge each AI has generated on specific projects. Consequently, users can access detailed insights through this customized LLM, tailored to provide precise and comprehensive project analyses. All the scores from these previous different models are cross-referenced. Our custom model will assign its score derived from an overall average score: all this data will enable us to establish a Trustability factor, allowing you to invest in any project with the best data available on the market.

We are making it by breaking down each document into smaller text segments, known as *chunks*, and then converting these chunks into embeddings. *Embeddings* are numerical representations of text that capture the essence of the information and can be processed by machine learning models.  These embeddings are stored in a vector database to facilitate efficient searching and retrieval of similar embeddings.&#x20;

When a user has a question, the system embeds it to understand its context and content. It then searches the vector database for chunks of text whose embeddings are similar to the question’s embedding. The relevant chunks contain information that can help answer the user’s question. Finally, the system sends both the original question and the retrieved chunks of text as context to an efficient language model; it then uses this information to generate a coherent and contextually relevant answer to the initial question. This process allows for a more informed and precise response by providing the language model with a tailored context extracted from our MongoDB database of text embeddings.


# Premium

Next Gem AI's Premium grants you access to more details on our platform for each project, to restricted areas such as being able to converse with our Next Gem AI, which has direct access to all the computed results contained in our private database & more. You can subscribe to NextGem Premium over three different intervals: 1 month, 6 months & one year. Discount is applied based on duration by burning an amount of $GEMAI through a transaction on the Ethereum chain, saved on a smart contract we deployed.

<figure><img src="https://4237869073-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F9pSU9vD3TIixHtjn35n1%2Fuploads%2FsvcU4yDtVYRK3Bq3C69V%2FPremium%20UI.png?alt=media&amp;token=4337815b-2c07-4d8b-b11e-38250b105aab" alt=""><figcaption><p>Next Gem AI Premium </p></figcaption></figure>

Here is a non-exhaustive list of the Premium services we plan to integrate in the future (or already present):

-> Accessing Next Gem AI to ask specific questions from our database dataset.

-> Sentiment Analysis from community member engagement and trustability score.&#x20;

-> Further details on the project info, such as direct pros and cons designed by the different AIs and resumed info on the web application on a single click.&#x20;

-> Requesting particular analysis on a specific project by providing the website link, using our LLM AI system to start a real-time analysis and provide you a note in real-time.&#x20;

-> Receive alerts based on Criteria pre-setup on our application, potentially getting info on new launches that meet your conditions over socials, emails, etc. Real-time new analysis from our system, directly shared with you without extra time.


# Supported Chains

Here is the list of currently Supported Networks on Next Gem AI:

-> Bitcoin

-> Ethereum

-> BNB Chain&#x20;

-> Cardano

-> Solana

-> Polkadot

-> Ripple

-> Litecoin

-> Chainlink&#x20;

-> Tezos&#x20;

-> Filecoin

To request support for another network, please reach out to [info@thenextgem.ai ](mailto:info@thenextgem.ai)


# Roadmap

**Q4 2023**:

* ~~Programming the first version of the Web Scrapper, analyzing extractable information on the Internet for any specific crypto-projects in NodeJS.~~
* ~~Creation and filtering of our datasets database (such as MongoDB) from projects parsed data within the scrapper framework and internal APls.~~
* ~~Writing the extended rules and weightage calculations, testing, helping the Als models analyze and score project content.~~
* ~~Back-end daemon software in continuous research for new projects datasets available on our database from the scrapper, sending processed information to all the LLM models for analysis~~
* ~~Building our web application with internal APIs to access information computed in our database, from Al result scores to private LLM content access.~~
* ~~Releasing the open-source repositories of the NextGem project on GitHub, making our scores analysis readable by anyone.~~

**Q1 2024**:

* Designing and developing the smart contracts for the $GEMAI ERC-20 token to be deployed on the Ethereum Chain.
* Burning deflationary mechanism on-chain through a smart contract associated with community users' wallets to access or revoke premium Next Gem AI's services.
* Launching the MVP first version of The Next 100x Gem online linked with our APIs, database, and information on projects (Als models scoring).
* Initiating the NextGem project across social networks to gain visibility and initiating deals to prepare the launch of the $GEMAI token with influencers and VCs.
* Deploying the Next Gem AI's custom LLM with our Premium service using the on-chain contract accessible on our online application.
* Kickstarting the Next Gem AI's token over the market by deploying it through a FairLaunch or a Decentralized launchpad we partnered with.
* Deploying liquidity over a Uniswap pool, enabling the buy and sell of the NextGem token with liquidity locked over 3 years once kick-started.

<br>

**Q2 2024**:

* Working on more crypto projects data sources fetching from different places, centralized or decentralized, to fetch the most possible source of info on project launch to save in our data.
* The accuracy of our dataset is filtered and tested, updated, and improved based on new available techniques and community feedback on the current analysis state.
* Adding more Al model sources to work with, following the latest powerful and most efficient ones, as it's moving very fast and exponentially.
* Bringing partnerships to the NextGem ecosystem adds value and visibility to our project.
* Exploring the listing of the NextGem token on some new centralized exchange Tier 1 or new blockchain AMM, potentially bridged on it to increase our growth.
* Explore partnerships or integrations with existing DeFi platforms to expand the utility of $GEMAI tokens, such as enabling them to be used in liquidity pools, lending, or yield farming.

**Q3 2024**:

* Working on different sources of potential analysis to be improved or added, such as the Community analysis of projects or code source, etc.
* Introducing new user interfaces and experience improvements based on community feedback and usability studies.
* Enhancing Al models with machine learning techniques to predict market trends and provide more accurate project evaluations.
* Evaluating and integrating emerging blockchain technologies and trends to keep the NextGem platform at the forefront of innovation.
* Expanding the NextGem platform to support additional languages and regions, making it a truly global tool for crypto investment.
* Strengthen security measures and conduct regular audits and updates to protect user database behavior data.<br>

**Q4 2024**:

* Implement Al-driven recommendations to suggest potential investment opportunities based on the user's past behavior and preferences, on the web application.
* Set up a continuous feedback loop with the community to regularly update the Al models with new data and insights.
* Implement A/B testing and other methods to continuously improve the platform based on user interaction and success rates.
* Introduce DAD, where the community can propose and vote on new features or changes to the NextGem ecosystem.
* Incorporating blockchain forensic tools to track projects' history and security, offering an extra layer of assurance and trust for investors, can be an extra note as a Certik dashboard.
* Implement machine learning algorithms to predict the potential success of crypto projects based on historical data and trends.

<br>

<br>


# $GEMAI Token

**Token Symbol:** $GEMAI\
**Contract**: [0xFBE44caE91d7Df8382208fCdc1fE80E40FBc7e9a](https://etherscan.io/address/0xFBE44caE91d7Df8382208fCdc1fE80E40FBc7e9a)\
**Network:** Ethereum\
**Standard:** ERC20\
**Deployer**: [0xb9f9aff95488e48db0c518e299548dfb986367d2](https://etherscan.io/address/0xb9f9aff95488e48db0c518e299548dfb986367d2)\
**Total Supply**: 850M $GEMAI (850,000,000)

1. #### Technology and Infrastructure (5% - 42,500,000 GEMAI)

   ( [0xb2e784284ca1bfe6f79ec4a8982d73a68c463a44](https://etherscan.io/address/0xb2e784284ca1bfe6f79ec4a8982d73a68c463a44) ) \
   Funds allocated for ongoing development, maintenance and scaling of the platform’s technology infrastructure.

2. #### Marketing and Community Growth (10% - 85,000,000 GEMAI)

   ( [0x3d9150f72a9b6bc7ce472d66e253b08430bf61a9](https://etherscan.io/address/0x3d9150f72a9b6bc7ce472d66e253b08430bf61a9) )\
   For promotional activities, partnerships, community incentives, and other strategies to increase adoption and visibility.

   ####

3. #### Ecosystem Incentives and Rewards (14.5% - 123,250,000 GEMAI)

   ( [0x9523369d3f580933e947947d1f92d92b03349332](https://etherscan.io/address/0x9523369d3f580933e947947d1f92d92b03349332) )\
   Dedicated to incentivising user participation, including rewards for using the platform, community contributions, and engagement initiatives.

   ####

4. #### Staking Rewards (9.5% - 80,750,000 GEMAI)

   ( [0xf003c59e17e82575c29fff455c477beffc8f8d78](https://etherscan.io/address/0xf003c59e17e82575c29fff455c477beffc8f8d78) )\
   Reserved for users who stake their tokens, contributing to platform liquidity and stability while earning rewards.

   ####

5. #### Team & Advisors (10% - 85,000,000 GEMAI)

   ( [0x036f777b0fa957a03e432e80be065317929c7523](https://etherscan.io/address/0x036f777b0fa957a03e432e80be065317929c7523) )\
   Compensation for the team and advisors, vested over a period to ensure long-term commitment and alignment with project success.

   ####

6. #### Private Round (12% - 102,000,000 GEMAI)

   Reserved for the first round of private sales, targeting strategic investors and KOLs.

   ####

7. #### Public Round (19% - 161,500,000 GEMAI)

   Available for broader public purchase during the public sale to increase token distribution and community engagement.

   ####

8. #### Liquidity (10% - 85,000,000 GEMAI)

   ( [0xeb7f1b38de77400c4ddada917f214854aedb708e](https://etherscan.io/address/0xeb7f1b38de77400c4ddada917f214854aedb708e) )\
   Allocated to ensure sufficient liquidity for exchanges and transactions within the ecosystem.

   ####

9. #### Platform Development Fund (5% - 42,500,000 GEMAI)

   ( [0x59fc7556e1d49744e4dddeed055c6a9d8e6cb680](https://etherscan.io/address/0x59fc7556e1d49744e4dddeed055c6a9d8e6cb680) )\
   For future development, new features, Fine Tuning Custom LLMs and integration of advanced technologies.

   ####

10. #### Operational Reserve (5% - 42,500,000 GEMAI)

    ( [0xb645031db9ae00b0d3ce2a23581bd56a977120bc](https://etherscan.io/address/0xb645031db9ae00b0d3ce2a23581bd56a977120bc) )\
    Kept as a reserve for unforeseen expenses, ensuring the smooth operation of the platform.


# $GEMAI Token Sale & Launch Plan

### Private Round&#x20;

* **Discount:** 15% discount from the Public Round
* **Tokens Allocated for this Round:** 102,000,000 $GEMAI are allocated for Private Round  (102M - 12% of total supply)&#x20;
* **Price:** 1 $GEMAI = $0.004350
* **Raise in this round:** $443,700
* **Vesting: 1**5% unlock at TGE,  no cliff, followed by 4 months linear vesting

### Public Round

* **Tokens Allocated for this Round:** 161,500,000 $GEMAI are allocated for Public Round (161.5M \~ 19% of total supply)&#x20;
* **Price:** 1 $GEMAI = $0.0051
* **Raise in this round:** $823,300
* **Vesting:** 25% unlock at TGE, no cliff, followed by 4 months linear vesting

### Liquidity on Uniswap

* **Liquidity Lock**:From funds raised  ($200K) + initial liquidity ($200K) \~ $400K liquidity to be locked on Uniswap V3 Pool for three years
* **Fully Diluted Valuation at TGE: $**&#x38;,032,500


# Token Utility

Here's an overview of the token utility for $GEMAI token:

1. **Premium Access**:

Purpose: $GEMAI tokens are required to acquire premium access to select AI premium features, including the Next Gem AI's Custom LLM.

Mechanism: Users need to spend $GEMAI tokens to unlock time-bound premium access to specific AI tools and services.

2. **Token Burning Mechanism**:

Purpose: Token burning is implemented as a deflationary measure.

Mechanism: Users burn a certain amount of $GEMAI tokens to gain access to premium services, reducing the overall token supply.

3. **Deflationary Design:**

Purpose: Encourage sustainable platform growth and align the token's value with the project's expansion.

Mechanism: The token supply is designed to decrease over time through burning, contributing to a deflationary model.

4. **Transition to Locking Model**:

Purpose: Address sustainability concerns by transitioning from a burning mechanism to a locking model.

Mechanism: At a certain stage where burning is no longer feasible, users must lock $GEMAI tokens for a specific period to access premium services, contributing to a new dynamic within the ecosystem.

5. **Balancing User Benefits and Operational Efficiency**:

Purpose: Ensure a balance between user engagement and operational efficiency.

Mechanism: The tokenomics are structured to provide superior value to users while promoting sustainable platform growth.

The $GEMAI token is positioned as a key element in incentivising community engagement, ensuring efficient operation of AI tools, and fostering a deflationary model that aligns with the project's growth.&#x20;

<br>