The reasoner orchestrates. The frontier consults.
Eve-Theology™ Fusion v5 is the compositional architecture behind TheoAI™. Three layers cooperate per request: a classifier (Microsoft Phi-3) reads the request, an orchestrator named Eve-Theology™ F5/reasoner — a Microsoft Phi-4-derived Small Reasoning Model LoRA fine-tuned on Eve-Genesis™ (Uṣūl Edition) — scaffolds the theological reasoning and delegates sub-problems to three frontier models as consultants, and then synthesises the answer in the discipline's idiom. Engineered at HYVE Labs.
The reasoner orchestrates. The frontier consults.
- CLASSIFIER
Microsoft Phi-3
Routes each request to the right depth — quick lookup versus deep investigation — in under a second. The first responder of the architecture; decides which downstream models compose for the query at hand.
- REASONER
Eve-Theology™ F5/reasoner — a Microsoft Phi-4-derived Small Reasoning Model, LoRA fine-tuned on Eve-Genesis™ (Uṣūl Edition)
The uṣūl reasoner. Trained on a synthetic reasoning dataset built from canonical uṣūl methodology — specifically the reasoning modes the discipline actually uses (dialectical, hermeneutic). The orchestrator: scaffolds the reasoning structure, delegates sub-problems to the frontier slots as consultants, synthesises the final answer in the discipline’s idiom. No customer data in training.
- FRONTIER SLOTS
Anthropic Claude Opus 4.7 · OpenAI GPT-5.4 · Meta Llama 4 Scout
Three frontier models composed dynamically per request — Opus for deep synthesis and judging, GPT for alternative reasoning paths, Llama 4 Scout for long-context analysis. Provider-agnostic by design; any model can be swapped without rebuilding the agent. The frontier models work for us, not the other way around.
We don’t compete with frontier labs on foundation-model capability. We compose frontier models into our reasoning systems. Eve-Genesis™ training data is 100% synthetic by construction — no customer conversation is ever used to train a model.
What a request actually does.
The flow below traces a single request through the architecture. The accent column is the reasoner's work — it scaffolds the response, delegates sub-problems, and synthesises the consultants' output. The classifier decides; the reasoner orchestrates.
- Question enters system
A request enters the fabric. The classifier reads it.
- Classifier routes classifier
Phi-3 decides the depth and modality. Sub-200ms.
- Reasoner scaffolds reasoner
The F5/reasoner builds the reasoning structure — decides what sub-questions to ask, in what order, of which consultants.
- Frontier consults frontier
Opus, GPT, Scout receive their assigned sub-problems and return their work. Provider-agnostic; per-request composition.
- Reasoner synthesises reasoner
The reasoner receives the consultants’ output and synthesises the final answer in the discipline’s idiom — not the internet’s.
- Answer returns system
The response is rendered in the surface that asked for it.
What the architecture buys us.
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Frontier substitution is cheap
When a new frontier model launches, we evaluate whether it belongs in the rotation. The reasoner is unchanged; the platform is upgraded without disruption.
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Provider diversity for sensitive scholarship
Theological reasoning has provenance constraints. The compositional fabric lets us route around providers per institution if scholarly community requires it.
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Cost shape is controllable
The bulk of theological reasoning runs through the Phi-4 SRM at near-Phi-4 cost. Frontier inference is reserved for cases the reasoner judges to warrant it.
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The IP is ours
The frontier models work for us, not the other way around. The reasoner owns the request. The frontier models are commodity consultants.
HYVE Labs.
HYVE Labs is the AI, ML, and innovation R&D division of MindHYVE.ai, Inc. The Eve-Genesis methodology, the Eve-Fusion v5 architecture, and the F5/reasoner orchestration pattern were all invented at HYVE Labs.