Ordellum AI Native SDKIn development
Knowledge engine
Every output is grounded in a curated knowledge base — and when evidence is thin, the SDK says so.
Layer 1 · Semantic search
“An upgradeable staking contract with secure withdrawals”
- Upgradeable proxy pattern (matched)
- Reentrancy guard (matched)
- ERC-20 standard
- Gas-efficient storage (matched)
- Oracle integration
- Audit finding: access control (matched)
- Unity integration pattern
Layer 2 · Knowledge graph
- Smart contracts
- Standards
- Vulnerabilities
- Solution patterns
- Networks
- Deployment targets
Diagram with two layers. The upper layer is a field of semantically indexed knowledge fragments matched to an intent. The lower layer is a graph connecting smart contracts, standards, vulnerabilities, solution patterns, networks and deployment targets.
- Semantic layer
- A large, semantically indexed vector store maps plain-language intent to the most relevant pieces of knowledge.
- Knowledge graph
- Models the relationships between contracts, standards, vulnerabilities, patterns, networks and deployment targets.
- Standards and best practice
- Blockchain standards and proven implementation patterns.
- Security
- Security patterns and lessons drawn from audit reports.
- Efficiency
- Gas optimisation techniques.
- Verified examples
- Code examples taken from production environments.
- Integrations
- Multi-protocol integrations, game-engine patterns and standard usage of modern interface frameworks.
Regular updates keep the outputs aligned with current industry practice, and feedback from production is fed back into the knowledge base so the platform keeps improving.
The SDK’s retrieval approach, AETHER-RAG, does not stop at fetching relevant text. It assembles a bundle of evidence that must cover the security obligations, platform targets and production expectations of the output being produced.