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PILLAR 02

AI, RAG & Vector Store Optimization

Improve AI accuracy, retrieval quality, grounding, auditability, and model reliability. KRYOS reverse-engineers where AI systems fail and rebuilds them on evidence-gated foundations.

Sub-services & deliverables

18 named deliverables in this pillar.

Each is engageable as a diagnostic, sprint, project, managed program, or board / investor advisory pack.

AI Data Asset Registry

A single catalog of every training set, eval set, corpus, vector store, model, and prompt asset.

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INPUT

Model inventory, training data manifests, vector store metadata.

HYPERCUBE WORKFLOW

Source discovery → asset classification → utility tagging → governance overlay.

OUTPUT

AI Data Asset Registry with ownership and utility class.

FREE DIAGNOSTIC

Free 10-Asset AI Inventory.

BEST FOR

CTOs, CDOs, AI governance leads.

Training Data Valuation

Defensible value of the corpora driving model utility and competitive position.

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INPUT

Training data manifests, model performance attribution.

HYPERCUBE WORKFLOW

Source map → marginal-contribution analysis → cost / replacement / utility layering → band output.

OUTPUT

Training Corpus Valuation Pack with P10/P50/P90.

Evaluation Dataset Valuation

Value the eval sets that determine which models ship - and which fail.

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INPUT

Eval manifests, model leaderboard history.

HYPERCUBE WORKFLOW

Coverage map → uniqueness scoring → contribution analysis → valuation band.

OUTPUT

Eval-Set Valuation Memo.

Vector Store Valuation

Quantify the asset value embedded in your retrieval index, not just its compute cost.

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INPUT

Vector store metadata, query logs, retrieval performance.

HYPERCUBE WORKFLOW

Index audit → query value attribution → reconstruction cost → utility band.

OUTPUT

Vector Store Valuation Pack.

RAG Evidence Graph

A live graph of which sources actually ground which answers, with weak links flagged.

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INPUT

Source corpus, retrieval logs, answer-source citation traces.

HYPERCUBE WORKFLOW

Source graph build → answer-to-source binding → weak-evidence flagging.

OUTPUT

RAG Evidence Graph with weak-link ledger.

RAG Diagnostic and Failure Audit

Find why your AI system retrieves weak evidence, hallucinates, or misses sources.

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INPUT

Golden queries, model answers, retrieved chunks, vector metadata.

HYPERCUBE WORKFLOW

Query classification → retrieval scoring → evidence-gate review → hallucination failure analysis → repair roadmap.

OUTPUT

RAG Failure Map and Repair Roadmap.

FREE DIAGNOSTIC

Free 10-Query RAG Audit.

BEST FOR

CTOs, AI leads, compliance-sensitive AI teams.

Chunking and Knowledge Architecture Redesign

Rebuild how source documents are decomposed so retrieval actually grounds answers.

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INPUT

Source corpus sample, existing chunking config, retrieval logs.

HYPERCUBE WORKFLOW

Corpus profiling → chunking strategy bake-off → retrieval lift measurement → migration plan.

OUTPUT

Knowledge Architecture Blueprint.

Cognitive Middleware API Design

Standardize how your products call models, with evidence, guardrails, and observability built in.

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INPUT

Existing AI calling patterns, target product surface.

HYPERCUBE WORKFLOW

API surface design → guardrail layer → telemetry hooks → adoption plan.

OUTPUT

Cognitive Middleware Spec.

Hard-Mode Compliance Layer

Make AI outputs survive compliance, legal, and regulated-industry scrutiny.

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INPUT

Use case scope, regulatory regime, current AI outputs.

HYPERCUBE WORKFLOW

Risk framing → policy gate design → evidence requirement → human-in-the-loop protocol.

OUTPUT

Compliance Gate Spec for AI outputs.

Decision Intelligence Layer

Wrap raw model outputs in the decision context - thresholds, alternatives, and escalation paths.

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INPUT

Target decision, current model outputs, decision-owner playbook.

HYPERCUBE WORKFLOW

Decision framing → option enumeration → confidence calibration → escalation routing.

OUTPUT

Decision Intelligence Schema.

Prompt Library Assetization

Convert your prompt collection into a versioned, governed, evaluatable asset.

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INPUT

Existing prompts, target use cases.

HYPERCUBE WORKFLOW

Inventory → taxonomy → eval harness → versioning and ownership model.

OUTPUT

Prompt Library Registry with eval scores.

Hallucination Failure Ledger

A continuous ledger of where AI made things up, why, and how it was caught.

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INPUT

Production AI traffic sample, current evaluation harness.

HYPERCUBE WORKFLOW

Failure capture → root-cause classification → mitigation routing → trend reporting.

OUTPUT

Hallucination Failure Ledger with monthly trend.

Agent Trace Intelligence

Make multi-step agent behavior auditable, reproducible, and debuggable.

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INPUT

Agent execution traces, tool definitions.

HYPERCUBE WORKFLOW

Trace schema → step-level evidence binding → failure-mode classification.

OUTPUT

Agent Trace Console.

Model Telemetry Asset Review

Treat production telemetry as an asset, not exhaust - and value it accordingly.

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INPUT

Telemetry inventory, current retention.

HYPERCUBE WORKFLOW

Stream classification → utility attribution → retention optimization → valuation band.

OUTPUT

Model Telemetry Asset Memo.

RAG Poisoning Risk Review

Find where adversaries could corrupt your retrieval index or its sources.

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INPUT

Source ingestion pipeline, vector store, access logs.

HYPERCUBE WORKFLOW

Attack surface map → poisoning scenario tests → mitigation roadmap.

OUTPUT

RAG Poisoning Risk Report.

FREE DIAGNOSTIC

Free Single-Vector Poisoning Scenario.

AI Governance Asset Dossier

A board-ready dossier proving your AI systems are governed, evidenced, and defensible.

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INPUT

AI inventory, current governance artifacts.

HYPERCUBE WORKFLOW

Inventory → gap analysis → dossier assembly → red-team challenge.

OUTPUT

AI Governance Dossier.

Continuous RAG Evaluation

An always-on eval harness that catches retrieval regressions before users do.

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INPUT

Golden query set, RAG endpoint.

HYPERCUBE WORKFLOW

Harness design → metric selection → CI integration → alert routing.

OUTPUT

Continuous Eval Console with regression alerts.

AI Benchmark Product Design

Turn your evals into a market-credible benchmark product.

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INPUT

Existing eval scope, candidate audience.

HYPERCUBE WORKFLOW

Benchmark scoping → integrity controls → publication pack.

OUTPUT

AI Benchmark Spec and Launch Pack.

What every engagement guarantees

The KRYOS standard.

Evidence-tagged inputs

Every claim carries a provenance and quality tag - no untraceable assertions.

Red-team review

Independent adversarial challenge before delivery - by design, not by exception.

Executive-ready output

Decision packets, not slide decks. Sized for the role that has to act.

No unsupported guarantees

We do not promise valuations, funding, or regulatory outcomes. We deliver evidence.

Engagement

Begin with a forensic data asset assessment.

A focused engagement that maps your data estate, scores assets against KRYOS frameworks, and produces a board-ready brief on what to recognize, value, productize, and capitalize.