System Architecture
We combine deterministic logic, enterprise context and AI into one auditable instance. Enterprise context plus codified executive logic, orchestrated through AI - with human oversight at any time. Six layers between the question and a defensible result. Each layer has one job - and one guarantee.
0ALearning Design PatternKnowledge · Experiences · Methods · Best Practice · Benchmarking
05Output & AuditResults with end-to-end provenance.
traceable04Contract-guardrailed Agentic CompositionAgentic composition within contract bounds.
generative · gated03Method Contracts - Deterministic Logic EngineHeuristics, decision rules, decision trees, validation.
deterministic02ADomain Knowledge GraphLevers · Pitfalls · Benchmarks · Industry approaches · Best practices.
CROSS-TENANT02BEnterprise Context GraphData, history, politics - asked, filtered, normalized, persisted.
PER TENANT01FoundationsFrontier models · Embeddings · Tool use.
extern0BDialogue ManagementMethods · Stages · Scopes · Challenges · Reasoning
The layers in detail
05
Output & AuditEvery result is traceable to its source - which rule, which context, which lever. No black-box output, but a trail a CFO or auditor can check.
04
Contract-guardrailed Agentic CompositionWhere there is room, agents compose together - but only within the guardrails set by layer 03. Generative in the how, gated the moment it touches the result.
03
Method Contracts - Deterministic Logic EngineThe core. This is where the judgement forms - rule-based, not generative. Identical inputs yield identical results. The method is fixed as a contract; the language model may phrase, but never decide.
02A
Domain Knowledge GraphCurated domain knowledge that every tenant benefits from - which factors make decisions in an industry succeed and where they fail. Shared, versioned.
02B
Enterprise Context GraphYour company, strictly isolated from all others. Once asked, it stays: context is not re-assembled in every dialogue but grows. Politics and history belong here explicitly - that is where decisions fail, not on the numbers.
01
FoundationsWe build no language models of our own; we use the best available - swappable, never in charge. The model supplies language understanding, not the judgement. The system stays model-independent.
0A
Learning Design PatternThe system learns not through model training, but by distilling experience into method and benchmarks. This feeds the Domain Knowledge Graph.
0B
Dialogue ManagementThe dialogue is run in stages - with a clear scope that asks targeted questions rather than assuming. It feeds the Enterprise Context Graph.