Enterprise AI Execution & Optimisation

Govern AI Infrastructure Like You Govern Financial Capital.

The CARDIAC-PURR Intelligence Platform is an enterprise control layer for multi-model AI systems. It orchestrates execution across providers in real time — optimising for cost, performance, reliability, and risk simultaneously. Not a router. A governance engine.

USPTO App. 64/073,758 · May 2026 EU AI Act — Conformity Assessment Completed: 25 June 2026 Self-hosted option Zero training required

The Problem

Every Enterprise Running AI
Faces the Same Four Gaps.

Most organisations treat AI infrastructure as a procurement problem — buy API credits, pick a model, hope it works. The result is uncontrolled cost, ungoverned risk, and zero operational visibility.

Uncontrolled Cost
Every request routed to the most expensive model by default. No cost attribution. No budget enforcement. Teams burn through API credits with no accountability.
Ungoverned Risk
Hallucinations, unsafe outputs, and low-confidence responses reach production unchecked. No policy enforcement before the response is returned to the user.
Zero Observability
No traceability of routing decisions. No audit trail of provider substitutions. When a model fails, you cannot reconstruct why or when it happened.
Provider Lock-In
Single-provider dependency creates operational fragility. Outages, price hikes, or capability degradation leave you with no fallback and no negotiation leverage.
Performance Blindness
No measurement of model performance per task type. No comparison of latency, cost, and quality across providers for the same workload.
Regulatory Exposure
The EU AI Act now mandates risk management, logging, transparency, and human oversight. Most AI stacks have none of these capabilities built in.

Platform Capabilities

Three Layers.
One Control Surface.

The platform combines intelligent routing, runtime governance, and financial optimisation into a single operational layer. Every decision is logged, every substitution is auditable, and every policy is enforced before a response leaves the system.

Layer 1

Intelligent Routing & Optimisation

Not all tasks need the most expensive model. The platform evaluates task complexity, latency requirements, provider availability, model capability, pricing, and execution context — then dynamically selects the most efficient model for every request.

Real-time cross-provider routing based on live telemetry
Session-aware optimisation that learns from conversation context
Graceful failover with automatic provider substitution
Dynamic degradation handling when providers become unstable
Cascade recovery with fallback execution paths
No model training, fine-tuning, or training data required — operational from day one
Layer 2

Risk Prevention & Governance Engine

A multi-stage governance system that enforces policy constraints, model eligibility rules, confidence thresholds, and validation logic before any response reaches the user. Designed for regulated environments where every output carries liability.

5-layer guard hierarchy for deterministic policy enforcement
Hallucination risk reduction through validation pipelines
Unsafe output blocking with configurable severity thresholds
Fallback escalation chains for low-confidence responses
Controlled degradation strategies under provider failure
Layer 3

Financial Optimisation & Observability

Every routing decision is measured, costed, and attributed. The integrated Model Delta Index (MDI) transforms AI infrastructure from a black-box expense into a measurable optimisation asset with procurement-grade audit trails.

Real-time cost visibility per request, session, and team
Measurable ROI with savings attribution per optimisation
Provider health monitoring with predictive degradation alerts
OpenTelemetry integration for enterprise observability stacks
Routing analytics with performance benchmarking per provider
Enterprise Grade

Production-Scale Reliability

Built for environments where downtime is measured in millions. The platform maintains bounded operational behaviour under provider outages, degraded inference quality, latency spikes, and policy violations.

Multi-provider failover with deterministic fallback chains
Rate limiting and quota enforcement per tenant
Cross-region deployment for geographic resilience
Observability pipelines with structured logging
Self-hosted deployment options for air-gapped environments

Provider Ecosystem

Multi-Provider.
Zero Lock-In.

The platform orchestrates across the full spectrum of commercial and open-source AI providers. Route by capability, cost, latency, or compliance requirements — and switch providers without changing your application code.

Claude
Anthropic — Advanced reasoning, long context, safety-focused
GPT
OpenAI — Broad capability, extensive fine-tuning ecosystem
Gemini
Google — Multimodal, native integration with Google Cloud
Azure OpenAI
Microsoft — Enterprise compliance, regional data residency
Mistral
Mistral AI — European, cost-efficient, open-weight models
Cohere
Cohere — Enterprise embeddings, multilingual, RAG-optimised
Llama
Meta — Open weights, self-hostable, no API dependency
Custom
Private endpoints, on-premise models, proprietary fine-tunes

Applications

Built for Enterprises
That Cannot Afford
Uncontrolled AI.

Every environment where AI outputs carry financial, legal, safety, or reputational consequences — and where "good enough" routing is not good enough.

Financial Services
Route sensitive calculations to high-precision models. Enforce audit trails for every recommendation. Block outputs that violate compliance policies before they reach traders or clients.
Legal & Compliance
Govern AI-assisted document review with deterministic policy enforcement. Ensure every output is traceable to a specific model version, provider, and validation checkpoint.
Healthcare & Life Sciences
Route diagnostic support queries to medically validated models. Enforce confidence thresholds. Maintain full audit trails for regulatory submissions and liability protection.
Critical Infrastructure
Operate AI systems under strict availability SLAs with multi-provider failover. Maintain deterministic behaviour during provider outages or degraded inference quality.
Enterprise Copilots
Optimise cost per interaction across thousands of users. Route simple queries to efficient models and complex tasks to premium models — automatically, transparently, accountably.
Customer Support Automation
Scale AI-powered support without scaling API costs proportionally. Govern tone, accuracy, and escalation policies across all customer-facing AI interactions.

Regulatory Alignment

EU AI Act.
Governance Is Now Law.

The EU Artificial Intelligence Act (Regulation (EU) 2024/1689) creates binding obligations for organisations deploying AI in regulated sectors. The CARDIAC-PURR Intelligence Platform is being developed to meet the obligations applicable to high-risk AI systems under Annex III.

The CARDIAC-PURR Intelligence Platform — LLM Router has undergone formal risk classification under Regulation (EU) 2024/1689 (EU AI Act). A written Article 6 classification determination has been completed on 25 June 2026 and incorporated into the Article 18 technical documentation.

EU AI Act compliance status matrix
Article Requirement Status Notes
6Risk classificationCompletedArticle 6 classification determination completed 25 June 2026
9Risk management systemIn progress
10Data and data governanceIn progressNo training data used by the routing system — confirm and amend if incorrect
11Technical documentationIn progressSee Article 18
12Record-keeping and loggingIn progressLog retention period to be confirmed
13Transparency to deployersIn progressDeployer information package under preparation
14Human oversightIn progressSee corrected description below
15Accuracy, robustness, cybersecurityIn progressPerformance claims under validation — see replacement text below
16Quality management systemIn progress
17QMS specificsIn progress
18Technical documentationIn progress
19Automatic loggingIn progress
43Conformity assessmentCompletedInternal self-assessment completed 25 June 2026 per Article 43
47EU declaration of conformityIn progressTo be issued following Article 43 completion
48CE markingIn progressTo be affixed following Article 47
49EU database registrationIn progressTo follow CE marking

Article 14 — Human Oversight

Human oversight under Article 14 requires that natural persons can understand the system's capabilities and limitations, monitor its operation in real time, and intervene or override automated routing decisions. Automated fallback chains are a reliability feature; they do not constitute human oversight under Article 14.

The CARDIAC-PURR LLM Router provides authorised operators with a real-time operator dashboard and OpenTelemetry-compatible telemetry pipeline through which routing decisions, model selections, provider substitutions, and governance checks can be monitored per request. Operators can review full provenance metadata for every response, identify routing anomalies, and intervene or halt execution through the platform API. A structured audit trail of all routing decisions and operator interventions is maintained automatically.

Deployer Obligations under Article 26 of Regulation (EU) 2024/1689

When you integrate the CARDIAC-PURR LLM Router into a product or service operating in a regulated sector, you assume the deployer obligations under Article 26 of Regulation (EU) 2024/1689. These include ensuring your specific use case complies with the EU AI Act, implementing human oversight measures appropriate to your context, and restricting use of the system to its intended purpose.

CARDIAC-PURR provides deployers with technical documentation covering the system's intended purpose, known limitations, performance characteristics, and risk mitigation measures. Deployers remain independently responsible for their own Article 26 compliance and for conducting any fundamental rights impact assessment required under Article 27.

General-Purpose AI Models — Article 53 of Regulation (EU) 2024/1689

The CARDIAC-PURR LLM Router routes prompts to third-party general-purpose AI models. CARDIAC-PURR does not train, fine-tune, or place those underlying models on the market and does not assume provider obligations for the underlying GPAI models under Chapter V of Regulation (EU) 2024/1689. Deployers should confirm GPAI compliance status directly with each underlying model provider.

Data Protection Notice

If routing operations involve the processing of personal data contained in user prompts, such processing is subject to Regulation (EU) 2016/679 (GDPR) concurrently with the EU AI Act. Where routing decisions constitute automated processing that produces legal or similarly significant effects on natural persons, Article 22 GDPR applies independently of and in addition to Article 14 of the EU AI Act.

Deployers are responsible for establishing a lawful basis for prompt processing and for implementing appropriate data subject rights procedures. CARDIAC-PURR processes prompt routing metadata only and does not retain prompt content beyond the routing operation.

Regulatory Timeline — Regulation (EU) 2024/1689 as amended by the Digital Omnibus on AI

Article 50 transparency obligations apply from 2 August 2026. High-risk AI obligations for standalone Annex III systems apply from 2 December 2027, as amended by the Digital Omnibus on AI (provisional political agreement of the European Parliament and Council, 7 May 2026; formal adoption and Official Journal publication pending). GPAI obligations have applied since 2 August 2025.

Enterprises evaluating deployment of the CARDIAC-PURR LLM Router in regulated sectors should contact us to discuss current compliance documentation availability.

Routing accuracy validated on a 100-item gold price sentiment classification benchmark (dataset v60, 15 June 2026) across three provider integrations: Anthropic, OpenAI, and Google. Results: 100% classification accuracy across all three providers (n=100 per provider; 95% confidence interval lower bound: 96.3%). Zero errors recorded. Cost savings versus single-model baseline: 78.8% (Anthropic), 84.9% (OpenAI), 83.5% (Google). Routing distribution: approximately 75% small-tier, 17% medium-tier, 8% large-tier. Azure OpenAI integration excluded from published results pending resolution of provider connectivity issues. Full benchmark methodology and per-item results available in technical documentation upon request.

Note: This page describes ongoing compliance work under Regulation (EU) 2024/1689. It does not constitute legal advice, a conformity declaration, or a claim of compliance with any specific EU AI Act obligation. Organisations should conduct their own legal assessment of applicable requirements.


Financial Impact

Turn AI Spend
From a Black Box
Into a Measurable Asset.

Most organisations have no visibility into which models they are using, why they are using them, or what they could have saved by routing differently. The platform changes that.

0%70%100%
0%40%80%

The platform typically reduces unnecessary premium-model usage by 30–50% while preserving task quality through intelligent substitution.

Projected Annual Impact
Current Annual AI Spend$600,000
Premium Model Spend$420,000
Potential Savings$168,000
Effective Cost Reduction28%
30–50%
Typical Cost Reduction
<3 mo
Typical Payback Period
Full
Audit Trail Coverage
Zero
Code Changes Required

How It Works

From Request to Response.
Governed at Every Step.

The platform sits between your application and your AI providers. It does not replace your models — it governs how they are used.

1

Request Intake

Your application sends a request through the platform API — exactly as it would to any single provider. No code changes. No SDK migration. The platform captures the request, its context, and its constraints.

2

Intelligent Routing

The platform evaluates the task against live provider telemetry — cost, latency, availability, and capability — and selects the optimal model. A simple classification task might route to Mistral. A complex reasoning task might route to Claude. All automatically.

3

Governance Enforcement

Before the response reaches your user, it passes through the governance layer. Policy constraints are checked. Confidence thresholds are validated. Unsafe outputs are blocked. Fallback chains are triggered if quality is insufficient. Every decision is logged.

4

Response & Audit

The response is returned to your application with full provenance: which model was used, why it was selected, what it cost, and what governance checks were applied. Your finance team sees savings. Your compliance team sees audit trails. Your engineers see performance.


Ready to Govern Your AI Infrastructure?

Full technical documentation and mechanism details are available under mutual NDA. Initial response within two business days. Patent-pending technology — outcomes only until IP protection is complete.

USPTO App. 64/073,758
EU AI Act — Conformity Assessment Completed: 25 June 2026
Self-hosted Option

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