A kernel for trustworthy AI conversation.
Axiomata turns “helpful & safe” promises into guarantees with laws, modes, and audited logs that survive model drift.
At a glance
- Kernel-level spec — not prompt craft. Enforceable, testable, upgradeable.
- Epistemic guardrails — foreground credible claims; demote weak or serving claims.
- Memory integrity — resilient context handling and predictable retrieval order.
- Protective modes — Crisis→Containment→Solemn ladder; overlays affect tone only.
- Audited logs — sealed reasoning surfaces per turn; linted for violations.
Axiomata: Conversational Kernel
Axiomata is an operating-system-style kernel for AI assistants. It defines Laws, modes, overlays, and memory structures that make assistants deterministic, safe, and inspectable. It’s vendor-agnostic and designed to sit under any model or product.
Deterministic by design
Law-bound dispatch, mode orchestration, and budgeted retrieval produce repeatable behavior — not vibes.
Truth with teeth
Credibility-first rendering prevents low-confidence claims from front-running facts.
Enterprise-ready
Audited logs, explicit failure modes, and compatibility matrices align with governance frameworks.
Kernel guarantees, not feature toggles
Context handling
Segmented context, ordered retrieval, and escalation rules preserve integrity under load.
Modes & overlays
Default, Research, and Protective family (Crisis/Containment/Solemn). Overlays change delivery, never decisions.
Evidence discipline
Reliability bands and slot discipline tie rendering to evidence and demote self-serving claims.
Result: product features can shift — the kernel holds the line. That’s the difference between a promise and a guarantee.
Platform features vs. kernel guarantees
Typical product features
- “Helpful by default” modes
- Long-term memory / personalization
- Safer responses / refusals
- “Transparency” blog posts
Axiomata kernel guarantees
- Deterministic mode orchestration & barred pairings
- Predictable retrieval with pinned canonicals
- Credibility-first rendering (weak claims don’t fill slots)
- Audited logs with policy linting
Request a conversation
Briefly describe your context (enterprise, research, compliance) and what you’d like to achieve. We’ll respond with a short menu of collaboration options.
Email kernel@kiteframe.app Or propose a time
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