Measured AI for production.
Research and frameworks that make LLM behavior auditable, repeatable, and privacy-first. We publish results, conformance rubrics, and operating patterns—so teams can trust outputs without exposing code or secrets.
Focus
- • Auditable behavior & conformance.
- • Deterministic options for repeatability.
- • Privacy-first, tenant-aware memory.
- • Streaming-first, production UX patterns.
Who we are
N28’s is a small research group designing the verification layer for AI. We combine deterministic settings, policy enforcement, and privacy-preserving telemetry to produce consistent, reviewable outputs. Built for government and enterprise contexts where verify + trace = trust.
Principles
Research themes
Measured AI
Outcome-centric evaluation across tasks with comparable metrics and clear acceptance bars.
Enforcement layer
Policy-driven format, safety, and grounding that travel across vendors and models.
Grounding & determinism
Constrain generations to context; tune stability knobs for reliable, repeatable answers.
Privacy-first telemetry
Signals that illuminate behavior without exposing raw inputs or secrets.
Results
- Response normalization for comparable UX across tasks.
- Context-discipline studies reducing novel-number drift.
- Streaming-first prototypes that remain auditable.
- Privacy-preserving metrics suitable for review.
In progress
Benchmark rubrics v2
Domain task sets for privacy, grounding, and conformance with measurable bars.
Observability dashboards
Latency, conformance, and privacy indicators for product decisions.
Policy packs
Industry-aligned rule sets (finance, healthcare, enterprise).
Partner evaluations
Vendor-agnostic comparisons centered on stability & behavior.
Quantum Memory (preview)
Minute-level smart cells
Atomic memory cells for fast recall and precise updates.
Tenant-aware privacy
Strict segregation with audit-friendly signals; no cross-tenant reuse.
Deterministic recall
Same state + query → same rationale; explainable retrieval.
Evaluation-first design
Metrics for recall utility, drift resistance, and update latency.
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