Input
Shared benchmark context
The same prompt is routed to multiple models so differences in omission, framing, and structure can be observed directly.
Independent standards for trusted intelligence
Norynthe.
Reports / scoring logic / architecture / workbook governance / client-facing trust surfaces
Build the reporting layer on top of the trust standard.
Norynthe.Reports turns the Phase 1 trust system into a visible product surface: model comparison, dimension-level reasoning, calibration workflow, and client-facing reporting built on the same governed evaluation standard.
7 trust dimensions
Norynthe.Score
Workbook as control layer
Client-ready reports
Scoring Logic
One prompt. Multiple models. One governed standard.
Norynthe does not ask which answer feels best. It asks which answer is most defensible across a common trust framework, then records why.
Evaluation
Seven scored dimensions
Trust is decomposed into grounding, evidence strength, consistency, context integrity, framing stability, cross-model alignment, and auditability.
Signal
Final Norynthe.Score
Dimension scores are weighted, resolved, and translated into a clear trust band without hiding the underlying rationale.
Current State
Where we are now, and why it matters.
This is no longer only a concept pass. The reporting layer now has a branded front door, an internal comparison workspace, a client-facing report concept, and a clearer bridge from narrative to implementation.
Operational
Canonical source of truth
The rubric, score bands, weights, pass plan, and resolver policy now live in one implementation-ready config instead of scattered notes.
- Single config for all seven dimensions
- Per-dimension prompt-pass plan encoded
- Workbook and runtime point to the same standard
Operational
Runnable reporting flow
The system can now execute comparison, drill-down, human review, and client-surface presentation through one connected reporting flow.
- Comparison reports and model profiles exist
- Human review mode is built into the workflow
- Client-facing report layer is visible on the same domain
Why
Strategic reason for this layer
The reporting surface makes the trust system legible. It turns architecture into something a buyer, investor, or reviewer can actually inspect.
- Trust logic becomes visible
- Architecture becomes defendable
- The product story now has a front door
Trust Bands
Executive signal without flattening the detail.
The banding system makes the final score readable at a glance while preserving the reasoning beneath it.
Band
Exceptional
90-100
Exceptional trust profile
Band
Strong
80-89
Strong trust performance
Band
Reliable
70-79
Reliable with notable issues
Band
Caution
60-69
Needs closer review
Band
Risk
<60
Significant trust risk
Dimension Stack
Each dimension has a job.
The final score only works if the dimensions stay distinct, calibrated, and interpretable.
Architecture
Scoring pipeline with built-in challenge.
Norynthe’s MVP does not treat disagreement as noise. The scorer and critic structure makes scoring more defensible by forcing each dimension result through evidence and review.
01
Prompt ingestion
Same prompt, selected models, raw outputs preserved.
02
Shared analysis context
Normalized payload with prompt, target output, peer outputs, metadata, and rubric.
03
Dimension scorer
Initial score, score band, evidence, deductions, and confidence.
04
Dimension critic
Rubric review, evidence challenge, score revision or approval.
05
Resolver
Deterministic application logic finalizes the score and flags escalations.
06
Aggregation + summary
Weighted trust score, band, and an action-ready explanation.
Architecture Thesis
Why this structure holds up
- The rubric lives outside the prompt text as a governed standard.
- Every score can be inspected through evidence and critique.
- Calibration happens through workbook changes, not guesswork.
- The investor story and implementation story are the same system.
- Cross-model comparison becomes a repeatable trust decision.
Workbook
The control layer behind the score.
The workbook keeps the system from becoming arbitrary. It defines what each dimension means, how deductions work, what anchor examples look like, and how the rubric evolves over time.
Rubric
Dimension definitions
Each trust dimension has a definition, core question, required checks, evidence rules, scoring bands, common deductions, and anchor examples.
Calibration
Prompt benchmark suite
Phase 1 starts with 20 prompts spanning policy, factual, ethics, business, and adversarial categories to stress different trust behaviors.
Governance
Versioned revision log
Rubric wording, score anchors, and deduction logic are tracked over time so the standard can improve without becoming unstable.
Report Surfaces
The trust standard now has a visible product layer.
This is the part Phase 1 did not originally have: internal and client-facing report surfaces that turn the evaluation system into a live product story.
Internal Surface
Norynthe.Reports
Model comparison, Norynthe.Score, dimension drill-down, two-model deltas, and human review mode inside one reporting workspace.
Client Surface
Norynthe.Report
The external deliverable layer that translates the internal trust system into an executive-facing report with recommendation framing and decision guidance.
MVP Contracts
Strict JSON before broader automation.
Phase 1 ends with machine-readable output contracts so the prototype can be implemented with predictable parsing and deterministic score resolution.
Scorer
Dimension scorer output
Initial score, band, evidence, deductions, required checks, and escalation signal.
Scorer JSON
Critic
Dimension critic output
Review decision, revised score, concerns, compliance notes, and resolver handoff.
Critic JSON
Prompt Structure
One template per role, rubric injected at runtime.
The implementation stays manageable because the dimension-specific behavior lives in config, not in seven separate prompt systems.
Template
Scorer prompt
Prompt
Template
Critic prompt
Prompt