Connected Engineering Knowledge for Verifiable Software
Reqvire turns scattered engineering intent into a structured semantic engineering model: ontologies, capabilities, requirements, verifications, implementation links, and evidence. That model stays close to the software lifecycle, can be reviewed and validated like code, and provides reliable context to engineers, AI agents, CI, reports, audits, and change-impact workflows.
Constraining AI-Generated Engineering Work
LLMs, AI agents, coding harnesses, and prompt-driven development are changing how software is produced. They can move quickly, but they also make it easier for engineering intent, assumptions, constraints, and verification obligations to disappear behind plausible code changes.
Reqvire gives these probabilistic workflows deterministic engineering anchors. The semantic engineering model provides explicit domain meaning, capabilities, requirements, contracts, verifications, and implementation links that humans and AI agents can review, query, validate, and use as controlled context during planning, coding, review, CI, and change-impact analysis.
The Model is More Than a Requirements List
It is a connected engineering knowledge model built from six core components:
- Ontologies — define reusable domain meaning.
- Capabilities — define stable operational or system abilities.
- Requirements — define implementable obligations.
- Refinements — capture behavioral, state, semantic, and constraint detail.
- Verifications — prove that obligations and capability expectations are met.
- Implementation artifacts — show where requirements and evidence are realized.
Where Reqvire Fits
Reqvire sits at the intersection of semantic engineering, MBSE discipline, connected engineering knowledge, and AI-enabled engineering workflows.
It keeps the traceability and lifecycle discipline of MBSE, but makes the engineering model explicit, reviewable, queryable, and usable as reliable context for software teams, AI agents, CI, reports, audits, and change-impact workflows.
What MBSE Means Here
Model-Based Systems Engineering shifts engineering from static documents toward connected models of system meaning, behavior, obligations, interfaces, verification, and evidence.
In Reqvire, that model is lightweight, text-based, and close to the software lifecycle:
- Ontologies — define reusable domain meaning.
- Capabilities — define stable operational or product abilities.
- Requirements — define implementable obligations.
- Refinements — capture behavioral, semantic, state, I/O contract, constraint, and specification detail.
- Verifications — prove that obligations and capability expectations are met.
- Implementation artifacts — show where requirements and evidence are realized.
This makes the model useful to systems engineers, software engineers, reviewers, compliance stakeholders, AI agents, and automated engineering workflows.
Why the Model Has Six Parts
Reqvire separates engineering knowledge into six connected parts because each one answers a different question. Ontologies define domain semantics, relations, rules, and reusable engineering concepts. Semantic contracts apply that knowledge as SHACL-based constraints and machine-readable engineering context, giving teams and AI agents implementation-facing contracts that can be checked during validation, automation, and review workflows. Capabilities describe what the product or system must be able to do. Requirements define obligations. Refinements add behavioral and semantic detail. Verifications prove expectations are met. Implementation artifacts connect the model back to code, tests, and evidence.
Keeping these concerns separate but linked makes the model easier to review, query, validate, and evolve as the software changes.