Why should I trust this answer?
An answer that looks correct is not enough. Governed AI must show exactly what it used, where that knowledge came from and why the resulting claim has a basis.
NAGENo Age for Cognition
No Age for Cognition
The knowledge layer
The knowledge layer
for AI you can trust.
Conventional models blend sources into an opaque state. The NAGE architecture is designed to keep governed knowledge separable and source-known, then carry an inspectable record with the answer.
FIG. 01 — KLM
Four layers.
Four layers.
One traceable mind.
The target layer model unfolds: managed knowledge units are intended to remain separable, carry origin metadata and be assembled only within declared boundaries.
L1 Retrieved
L2 Declarative
L3 Procedural
L4 Metacognitive
Assembling
Structured Knowledge Layers
Keep knowledge inspectable.
Beyond two models
Two models ask.
Two models ask.
KLM One governs both.
Language models know. Action models do. Neither alone supplies a complete governance record. KLM One is the candidate standard for specifying how knowledge layers and records should remain controlled, updateable and reviewable.
Govern knowing and doing.
Fig. 03 — Anatomy of a VARVE
A structured,
A structured,
reviewable knowledge-unit design.
In the target architecture, a VARVE separates knowledge content, operating boundaries and provenance fields. Core Payload, Boundary Shell and Audit Anchor name those intended responsibilities; their deployment evidence must be evaluated separately.
Inspect every knowledge unit.
Architecture principle — Governed learning
A boundary against
A boundary against
user-data training.
The target design keeps customer knowledge outside the core optimization loop behind an explicit training boundary. That separation must be validated for each deployment; a declared record does not by itself prove training isolation.
Improve the system. Protect the data.
Hero
Layers
Origin
Purities
Scroll to begin
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Components as citizens, not rigid services
Named deployment units behave as coordinated parts of one knowledge process; each role and handoff still needs a deployment-specific contract.
How it works
A candidate standard called KLM One. A reference architecture called SEDIM One.
KLM One defines a candidate record vocabulary for layered knowledge. SEDIM One separates the architectural responsibilities; the current service uses Qwen3-8B grounding and records while trained layers remain in development.
KLM ONEThe candidate standard
The candidate standard describes layered, sourced and updateable knowledge without treating every capability as current implementation. Language remains the interface; the record vocabulary defines what can be inspected.
SEDIM ONEThe reference architecture
SEDIM One describes how source-aware answers, records and target managed layers divide responsibility. Today, grounding and records are available; trained layer application remains a development path.
Record disclosureAttribution, declared
The record can disclose the sources and signals declared for an answer. That creates inspectability within scope; it does not by itself prove causal participation or answer truth.
Evaluation-ready
Bring source and record evidence into the review path.
Governance and regulatory reviews often need traceability. A NAGE record can expose declared sources and signals for review, while the applicable requirements and additional assurance controls remain deployment-specific.
The deep technical dive is available to beta partners. Talk to us.
Platform overview
One record. Across the system.
KLM defines a candidate record vocabulary. SEDIM supplies the reference architecture. Nage AI OS carries records across the operating environment.
01 · Reference architecture
SEDIM
Grounding and records are available today. The trained-layer application remains in development.
Explore SEDIM → 02 · Operating environmentNage AI OS
The operating components are available with implementation-specific integration gaps made explicit.
Explore Nage AI OS → 03 · Candidate standardKLM
A public charter and candidate vocabulary—not a certification scheme or blanket assurance claim.
Explore KLM →Availability and evidenceOpen full platform overview →
| System | Availability | The record must answer |
|---|---|---|
| KLM | Public charter; candidate standard. Full public v1.0 forthcoming. | Which record fields and checks describe the result? |
| SEDIM | Grounding and records with Qwen3-8B. | Which sources and signals participated? |
| Nage AI OS | Operating components with implementation-specific gaps. | Which service owns each handoff and disclosure? |
| Craton / Pro | Research and development. | Can managed layers supply usable knowledge? |
Scope note. A shared record makes a result inspectable within its stated scope. It is not a blanket guarantee.
Follow one record
From output to a check another recipient can run.
The walkthrough reads the same bundled synthetic fixture used by the Record Lab. It does not invent a second demonstration record.
One request becomes a reviewable record.
Begin with the declared request, output and disclosure scope before interpreting any score or signature.
- Request
- Loading fixture…
- Answer
- Loading fixture…
- Disclosure
- Loading fixture…
Scope. Fixture values are synthetic and dated 15 September 2026. They are not production measurements or calibrated probabilities.
Verification workspaceChange the answer. Recompute the record.+
Closed by default. Checks run locally in the browser against the public synthetic fixture and test key.Open the full Record Lab →
Evidence and scope
Read the artefact, the boundary and the open work together.
The claims have a dated source set.
Use the conference whitepaper, technical annex and synthetic fixture as the evidence edition behind this experience.
A valid record is not a blanket guarantee.
Integrity, signature, support, identity and execution answer different questions. Missing evidence remains visible.
Review trust and limits →Available today stays separate from the research path.
The current service uses Qwen3-8B grounding and records. Trained layers and Craton remain development and research programmes.
Compare architecture states →A bounded evaluation
Four decisions before a production claim.
- 01
Choose the workflow.
Name the decision, recipient and consequence that make the answer worth governing.
- 02
Define the source set.
Agree which evidence is permitted, who owns it and how lifecycle changes are handled.
- 03
Agree the checks.
Set integrity, support, silence, key-trust and handoff acceptance criteria before testing.
- 04
Review against criteria.
Run the bounded scenario, retain the record and document open risks without upgrading them into claims.
Reported evidence snapshot
Research metrics, kept in their source scope
0.0265
Validation loss
120×
Faster convergence
94.5%
Language routing (TR)
351.6 MB
Per knowledge layer
90.6
SEDIM-Bench
Scope. These reported metrics belong to the supplied 15 September 2026 evidence edition and are not a single production benchmark or service-level guarantee.
Evolution is running
Meet the new dawn.
The Qwen3-8B grounding-and-record path is open for a scoped controlled beta; target trained layers remain in development.