guillermo lucero

Project Owner

ASI:Chain AI-Native DevKit

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n/a

Type SingularityNET RFP
Funding Request n/a
RFP Guidelines An AI-native Development Environment for the ASI:Chain

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Overview

We propose building a model-agnostic, AI-native IDE and programmable development infrastructure for ASI:Chain that enables structured agent and contract generation, enforced validation checkpoints, local simulation, and safe deployment to DevNet and Testnet. A vendor-neutral AI Model Abstraction Layer and programmable Dev API Gateway ensure reproducible builds, secure wallet-controlled transactions, and governance-aware lifecycle tracking—delivering not just tooling, but stable builder infrastructure aligned with MainNet V1.

RFP Guidelines

Open for Proposals

An AI-native Development Environment for...

Ending on:

13 Feb. 2026

Days

Hours

Minutes

Type SingularityNET RFP
Total RFP Funding $50,000 USD
Proposals 21
Awarded Projects n/a

SingularityNET

Feb. 4, 2026

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This RFP seeks proposals for the development of an AI-native Development Environment (IDE) that improves the efficiency and accessibility of blockchain application development for the ASI:Chain.

Proposal Description

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In order to protect this proposal from being copied, all details are hidden until the end of the submission period. Please come back later to see all details.

Total Milestones
4
Total Budget
$50,000_USD
Last Updated
13 Feb 2026

Milestone 1 - Architecture & AI Model Abstraction Layer

Description

Timeline: Weeks 1–4 / The first month establishes the architectural and AI-governance foundation of the ASI:Chain AI-Native DevKit. The objective is to formalize a strict separation between generative AI output and executable blockchain artifacts before introducing chain interaction complexity. This milestone ensures structural clarity provider neutrality and schema-enforced generation as the core discipline of the system. The focus is stability before functionality. By the end of this milestone the AI Model Abstraction Layer will govern how structured artifacts are produced versioned and validated against ASI:Chain primitives.

Deliverables

Complete layered architecture documentation - AI Model Abstraction Layer (initial implementation): - Provider adapter interface (model-agnostic design) - Versioned structured prompt contract framework - Typed ASI:Chain output schema definitions - Structural artifact materialization pipeline Regression validation framework for provider stability Public modular repository scaffold

Budget

$12,000 USD

Success Criterion

Success is achieved when generated artifacts strictly conform to typed ASI:Chain schemas through the abstraction layer, independent of provider selection. The architecture must be documented and versioned, and structured outputs must produce consistent artifacts from identical inputs. This confirms that generation is formally governed prior to blockchain execution.

Milestone 2 - Dev API Gateway & DevNet SDK Backbone

Description

Timeline: Weeks 5–8 / The second month operationalizes the validated AI outputs by introducing programmable chain interaction. This milestone implements the ASI-Chain Dev API Gateway and connects structured artifacts to a Docker-based DevNet environment through a TypeScript SDK. The objective is to demonstrate controlled compilation and deployment to DevNet without manual chain interaction. This transforms the system from architectural framework into programmable infrastructure.

Deliverables

Dev API Gateway implementation: - Contract compilation endpoint - Agent deployment endpoint - DevNet network switch endpoint Core TypeScript SDK integrated with DevNet Docker-based local DevNet lifecycle management: - Start / Stop / Reset controls Structured compilation → deployment pipeline Versioned API documentation

Budget

$14,000 USD

Success Criterion

Success is achieved when structured artifacts validated through the abstraction layer can be compiled and deployed to DevNet through the SDK and API Gateway without manual chain interaction. API endpoints must be versioned, DevNet must operate reliably, and deployment must be reproducible.

Milestone 3 - Validation Workflow & DevNet Deployment

Description

Timeline: Weeks 9–13 / The third phase delivers the functional AI-native development environment. This is the most engineering-intensive milestone integrating the abstraction layer Dev API Gateway wallet controls simulation enforcement and explorer visibility into a unified IDE workflow. Developers will be able to generate structured contracts and agents validate them through enforced checkpoints simulate execution locally and deploy to DevNet within a controlled lifecycle. This milestone transforms infrastructure into a tangible builder experience.

Deliverables

AI-native IDE interface (alpha release) Integrated structured generation pipeline: - Generation - Schema validation - Artifact materialization - Compilation - Simulation Non-custodial wallet integration: - Keplr and Leap support - Transaction preview - Gas simulation - Explicit signing flow Integrated DevNet explorer panels: - Blocks - Transactions - Deployed contracts CLI integration with Dev API Gateway Local DevNet lifecycle controls inside IDE

Budget

$17,000 USD

Success Criterion

Success is achieved when developers can complete the full controlled workflow: Generate > Validate > Simulate > Deploy to DevNet. Invalid artifacts must be blocked before deployment eligibility, wallet transactions must require preview and confirmation, and the integrated explorer must accurately reflect on-chain state. A live end-to-end demonstration confirms operational readiness.

Milestone 4 - Testnet Launch: Runtime & ERC-8004

Description

Weeks 14–16 / The final phase embeds governance signaling and economic accountability into the builder lifecycle while enabling Testnet readiness. This milestone integrates ERC-8004 review submission token burn mechanisms lifecycle traceability and network switching to Testnet. The objective is to demonstrate a complete MainNet-aligned builder lifecycle that connects generation deployment execution review and economic signaling.

Deliverables

ERC-8004 review submission interface On-chain review verification Token burn integration: - Burn trigger endpoint - Explorer burn visibility Testnet network switching support Lifecycle tracking across: - Generation - Deployment - Review - Burn Full documentation set: - Architecture overview - Developer onboarding guide - Demo repository Public end-to-end workflow demo

Budget

$7,000 USD

Success Criterion

Success is achieved when a complete lifecycle flow can be demonstrated: Generate > Validate > Deploy > Execute > Submit Review > Burn > Verify on Testnet. Governance actions must be verifiable on-chain, Testnet migration must occur without refactor, and documentation must enable reproducible deployment by third parties.

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The weighted average of the 4 perspectives Overall

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Each RFP defines a maximum allowed budget, but teams can differentiate their proposal by offering a solution with a lower budget or a wider scope.Value for money

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This rating indicates compliance to 'Must haves' but also adaptation of 'Nice to haves' and Non-functional requirements defined in the RFP.Compliance with RFP requirements

0.0
RFPs will offer varying degrees of freedom. This rating indicates the quality of the team's specific solution ideas, the provided details, and the reviewer's confidence in the team's ability to execute.Solution details and team expertise

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A proposal that promises the development of a personal assistant that outperforms existing solutions might be feasible, but if there is no AI expertise in the team the viability rating might be low.
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guillermo_lucero

Project Owner

Senior PM leading strategy, architecture alignment, and cross-team coordination. Oversees milestones, governance integration, and ecosystem alignment to deliver a secure development stack on time.

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Leandro Gavidia Santamaria

DevKit Lead

AI & blockchain developer focused on DX. Leads DevKit, SDK, smart contract integration, validation/simulation layers, and AI-assisted tooling to deliver a secure, scalable AI-native stack.

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Juan Quiceno

Blockchain Lead

Blockchain engineer, leads smart contracts and chain integrations, implementing runtime logic and protocol connections. Ensures secure execution and Testnet readiness for the AI-native stack.

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Luis Fernando

Product UX Lead

Leads web IDE, UI/UX architecture, and frontend tooling. Designs intuitive workflows, integrates SDKs/APIs, and ensures a seamless developer experience across the AI-native environment.

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Cheddar Queso 3D

AI Runtime Lead

Leads AI runtime and model abstraction integration, designing backend services and APIs that connect AI reasoning, DevKit workflows, and blockchain execution within a secure, scalable stack.

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