| Version | 2.0 |
| Token Name | rogerai platform |
| Token Symbol | ROGERAI |
| Standard | ERC-20 |
| Decimals | 18 |
| Total Supply | 600,000,000 ROGERAI |
| Network | Base Mainnet · Chain ID 8453 |
| Token Contract | 0xA48803F048606502017b4298d40065dCD14b8e53 |
RogerAI is an AI-powered platform ecosystem designed to bring intelligent software products, AI-assisted interaction, document intelligence, engineering automation, semantic retrieval, visual document understanding, and token-enabled coordination into a unified digital environment.
The RogerAI ecosystem is built around a layered architecture. At the intelligence layer, RogerAI is developing a modular model family designed for different categories of AI workloads. At the product layer, RogerAI is designed to support user-facing AI capabilities such as chat interaction, document understanding, workflow support, and future developer interfaces. At the utility layer, ROGERAI is designed as the ecosystem token on Base, intended to support future access coordination and token-enabled service models as the platform matures.
ROGERAI is deployed as a fixed-supply ERC-20 token on Base. The token contract has no owner function, no post-deployment mint function, no pause mechanism, no blacklist function, no tax or fee logic, and no upgradeability mechanism. The full fixed supply was minted at deployment to the RogerAI .
RogerAI is an evolving technology ecosystem. Platform features, model availability, token utility, integrations, liquidity planning, and third-party availability may develop over time based on product maturity, infrastructure readiness, ecosystem demand, and external review processes.
This whitepaper is provided to describe the RogerAI ecosystem, platform direction, model architecture, token structure, and public technical references.
ROGERAI is designed as a utility token for the RogerAI ecosystem. It does not represent equity, ownership, dividends, revenue share, debt, profit entitlement, or any claim over Digital Product Trading Establishment or any associated operating entity.
Nothing in this whitepaper should be read as a promise of financial return, price performance, market liquidity, public trading availability, third-party platform acceptance, or completion of any future product feature within a fixed timeframe.
RogerAI’s product roadmap, model deployment methods, token-enabled access models, and ecosystem integrations may evolve as engineering, product, security, infrastructure, and platform review processes progress.
RogerAI is designed as a modular AI platform ecosystem that combines applied artificial intelligence, intelligent digital workflows, document intelligence, developer interfaces, wallet access, and token-enabled coordination.
The platform is organized around three cooperating layers:
The intelligence layer is the model and reasoning foundation of RogerAI. It is designed to support different categories of AI workloads, including reasoning, daily assistant interaction, engineering automation, semantic search, retrieval quality, and visual document understanding.
The product layer is designed to expose AI capabilities through user-facing products and interfaces. These may include RogerAI Chat, document intelligence, workflow assistance, automation support, developer tools, and future platform modules.
The utility layer is represented by ROGERAI, the ecosystem utility token on Base. ROGERAI is intended to support future access coordination, platform usage models, and token-enabled service structures as RogerAI products and integrations mature.
This separation allows the ecosystem to evolve in a structured way: models can improve, product interfaces can expand, and the token layer can remain transparent, fixed-supply, and publicly verifiable.
RogerAI is building a modular AI model family designed to support reasoning, daily assistant workflows, engineering automation, semantic search, retrieval quality, and visual document understanding across the RogerAI ecosystem.
The model family is structured as a layered intelligence stack rather than a single model. This allows different workloads to be routed to the most suitable AI capability.
RogerAI-Apex is the flagship reasoning model of the RogerAI model family. It is designed for high-value enterprise workloads that require deep context understanding, long-document analysis, formal writing, structured reasoning, and precise output generation.
Apex is positioned for quality-first tasks where accuracy, context depth, and advanced reasoning are more important than speed.
RogerAI-Core is the balanced daily assistant model of the RogerAI ecosystem. It is designed to support general Arabic and English interaction, document summarization, formal rewriting, task extraction, classification, and internal application workflows.
Core is positioned as the default operational model for fast, reliable, everyday AI assistance.
RogerAI-Forge is the engineering intelligence layer of the RogerAI model family. It is designed to support software development, code generation, code review, bug detection, log analysis, DevOps workflows, test generation, and technical system explanation.
Forge expands RogerAI from assistant intelligence into technical execution support.
RogerAI-Index is the semantic indexing layer of the RogerAI ecosystem. It is designed to convert text into embeddings that enable intelligent search, knowledge retrieval, similarity comparison, and retrieval-augmented generation systems.
Index supports knowledge access across documents, archives, repositories, and structured information sources.
RogerAI-Rank is the retrieval ranking layer of the RogerAI ecosystem. It is designed to improve search quality by reranking retrieved passages based on relevance.
Rank helps reduce noisy results, improve answer grounding, and increase the quality of AI responses in knowledge-based workflows.
RogerAI-Scan is the vision and document understanding layer of the RogerAI model family. It is designed to support image understanding, screenshot analysis, scanned document review, form and table interpretation, and visual document intelligence.
Scan connects visual input with structured AI workflows.
The RogerAI model family is organized into four intelligence layers:
This layered structure allows RogerAI to position different AI capabilities for different workload types, from general assistant interaction to document intelligence, engineering automation, semantic retrieval, and visual understanding.
The RogerAI model family represents the technical direction and product architecture of the RogerAI ecosystem. Model availability, deployment methods, runtime environments, user-facing integrations, and production access may evolve over time based on product readiness, infrastructure requirements, and platform development.
No statement in this section should be read as representing that every model is publicly available, fully commercialized, or integrated into every RogerAI product at this stage.
RogerAI is an early-stage AI platform ecosystem.
The current working product layer is RogerAI Chat, which demonstrates the platform direction toward AI-assisted interaction, structured conversation, workflow support, and future ecosystem access features.
Additional product areas are presented as planned, roadmap, or in-development modules and are not represented as fully available commercial products at this stage.
RogerAI is designed as a modular suite of AI-powered products that share a common platform direction and may connect to a single utility layer over time.
RogerAI Chat is the initial working layer of the RogerAI ecosystem. It is designed to demonstrate AI-assisted conversation, structured interaction, and the foundation for future product expansion across the RogerAI platform.
Document Intelligence is designed to support future document ingestion, content understanding, information extraction, classification, structured output, drafting assistance, review support, signing workflow coordination, archival, and retrieval.
Workflow Automation is designed to support future AI-assisted process coordination, helping structure repeated tasks, organize information, and support operational workflows as integrations mature.
AI Workspace is planned as a workspace layer where users and teams may interact with AI tools, organize outputs, coordinate AI-assisted workflows, and connect multiple product capabilities within one environment.
The Developer and API Layer is planned to expose RogerAI capabilities through programmatic interfaces as the ecosystem matures. This may allow connected systems, internal applications, and future agentic workflows to interact with RogerAI platform capabilities.
The RogerAI token ecosystem includes wallet access and is designed to support future token-enabled access coordination, platform usage, and ecosystem service models.
Alongside its product direction, RogerAI is designed to support engineering-led services that assist with the design, integration, and operation of intelligent systems.
These services may include:
These services are intended to support the practical deployment of RogerAI capabilities as the platform matures.
RogerAI’s AI capabilities are designed for practical digital work rather than isolated demonstrations.
The platform is designed to support:
RogerAI is designed to operate across Arabic and English interaction, supporting mixed-language digital environments where appropriate.
Knowledge-grounded responses, private data grounding, and connected information workflows may evolve as platform integrations and data connections mature.
RogerAI is designed to translate AI capabilities into structured digital solutions for recurring operational needs.
Potential solution areas include:
RogerAI is designed to support future drafting, extraction, review, classification, signing workflow coordination, and archival for document-centric processes.
RogerAI is designed to support AI-assisted responses, structured interaction, and future knowledge-grounded communication workflows.
RogerAI is designed to support repeated task structuring, information coordination, and future automation of rules-based operational work.
RogerAI-Index and RogerAI-Rank are designed to support intelligent retrieval, semantic search, and relevance ranking across knowledge sources.
RogerAI is designed to support future internal review, structured approval, reporting, and control workflows as platform capabilities mature.
RogerAI is designed to expose platform capabilities to developers and connected systems through programmatic interfaces as the ecosystem matures.
Potential developer capabilities include:
These capabilities are intended to support future integration between RogerAI products, internal applications, connected systems, and agentic workflows.
The RogerAI Wallet is a self-custody wallet designed to hold the ROGERAI token and support future connection with RogerAI platform products and services.
The wallet is designed to support token holding, sending, receiving, and future token-enabled access features within the RogerAI ecosystem.
By combining self-custody with a single utility token, the wallet is designed to support future access coordination, usage metering, and token-enabled service models within one consistent economic framework.
Private keys remain under user control through the wallet model. Token-enabled usage models may evolve as platform integrations and product readiness progress.
ROGERAI forms a utility layer intended to connect RogerAI platform capabilities with future access coordination and token-enabled service models.
The design separates potential token-based coordination on Base from AI computation, which remains off-chain and can scale independently of blockchain execution.
Token-based coordination models on Base are designed to be transparent and verifiable, while AI computation remains flexible, off-chain, and performance-oriented.
Combined with self-custody, this layer is intended to support future direct access coordination for AI services using a token held under the user’s own keys, rather than relying only on disconnected, provider-specific balances.
ROGERAI is the utility token of the RogerAI ecosystem. It is implemented as a standard ERC-20 token deployed on Base.
Its role is intended to support future access coordination for platform services and token-enabled service models as the ecosystem matures.
The token’s supply is fixed at deployment and cannot be increased. The deployed token parameters are:
| Parameter | Value |
|---|---|
| Project Name | RogerAI |
| Token Name | rogerai platform |
| Symbol | ROGERAI |
| Standard | ERC-20 |
| Decimals | 18 |
| Total Supply | 600,000,000 ROGERAI |
| Network | Base |
| Chain ID | 8453 |
| Token Contract | 0xA48803F048606502017b4298d40065dCD14b8e53 |
The utility of ROGERAI is designed around its potential function within the RogerAI ecosystem.
ROGERAI may support:
ROGERAI is intended to support future access coordination for AI, document, automation, and platform capabilities.
ROGERAI is intended to support future token-enabled service models as ecosystem integrations mature.
ROGERAI may support future coordination of finite compute, retrieval, data, and platform resources.
ROGERAI may support future ecosystem participation models from the fixed supply, subject to product development, platform readiness, and ecosystem requirements.
ROGERAI may support future participation over mutable ecosystem components, while the token contract itself remains immutable.
ROGERAI has a fixed total supply of 600,000,000 tokens.
The token contract was deployed on Base with 18 decimals. The fixed supply is publicly verifiable on Base.
The contract does not include:
Future ecosystem usage, liquidity planning, platform integrations, and operational planning may be determined by RogerAI based on product development, ecosystem requirements, market readiness, and applicable platform review processes.
The ROGERAI token contract is designed around administrative minimization.
The most important security design principle is the absence of privileged controls. A function that does not exist cannot be used, misused, compromised, or delegated.
The token contract includes:
This design reduces administrative attack surface and supports public verification through the deployed contract.
The token contract is public and can be reviewed on BaseScan:
0xA48803F048606502017b4298d40065dCD14b8e53
No technology system should be interpreted as free from operational, technical, or security considerations. RogerAI’s token design focuses on minimizing avoidable administrative control within the token contract.
The roadmap describes the intended progression of RogerAI in terms of product and technical milestones rather than fixed dates.
The foundation phase includes the ROGERAI token deployment, public contract verification, the initial RogerAI Chat working model, public token materials, and platform identity.
The model stack expansion phase includes the development and positioning of the RogerAI model family: Apex, Core, Forge, Index, Rank, and Scan. This phase focuses on strengthening reasoning, daily assistant workflows, engineering intelligence, semantic indexing, retrieval ranking, and visual document understanding.
The product expansion phase includes broader document intelligence, workflow automation, AI workspace capabilities, developer interfaces, and token-enabled access coordination as platform integrations mature.
The ecosystem development phase includes community education, developer readiness, platform integrations, liquidity planning, security review planning, and future ecosystem participation models.
Roadmap items may evolve based on engineering progress, infrastructure readiness, security review, product maturity, and ecosystem demand.
RogerAI is operated by Digital Product Trading Establishment, a technology firm focused on software engineering, artificial intelligence, and enterprise automation. The entity supports the development and operation of RogerAI products, platform infrastructure, and ecosystem materials.
Digital Product Trading Establishment
Software Engineering · Artificial Intelligence · Enterprise Automation
Contact: admin@rogerai.net Official X / Twitter: x.com/rogerai_ar · @rogerai_ar
RogerAI is an evolving technology ecosystem. Platform features, model availability, token utility, integrations, liquidity planning, and third-party availability may develop over time based on product maturity, infrastructure readiness, ecosystem demand, security review, and external review processes.
ROGERAI is designed as a utility token for access coordination and ecosystem usage within RogerAI.
ROGERAI does not represent equity, ownership, dividends, revenue share, debt, profit entitlement, or guaranteed financial return.
Nothing in this whitepaper represents a promise of token price performance, market liquidity, exchange availability, third-party platform acceptance, or completion of any future product feature within a fixed timeframe.
RogerAI is building an AI-powered platform ecosystem designed around modular intelligence, product-driven AI capabilities, and a fixed-supply utility token on Base.
The RogerAI model family provides the technical foundation for reasoning, daily assistant interaction, engineering automation, semantic retrieval, retrieval ranking, and visual document understanding.
The RogerAI product direction connects these capabilities to AI-assisted workflows, document intelligence, developer interfaces, wallet access, and future token-enabled ecosystem coordination.
ROGERAI is designed as the utility token of this ecosystem. Its role is connected to access coordination and future platform usage models as RogerAI products, integrations, and infrastructure mature.
RogerAI’s direction is to build a structured AI ecosystem where intelligent software, model capability, workflow automation, and token utility can evolve together under a transparent and publicly verifiable foundation.