MDCP™ (Murray Deterministic Computing Platform) is a deterministic computing platform for safety-critical and regulated systems, designed to provide bit-perfect, replayable execution across supported hardware architectures. It supports certification evidence generation, forensic debugging, and liability closure for AI-enabled and autonomous systems operating under standards such as DO-178C, ISO 26262, IEC 62304, and IEC 61508.

01 The problem

Non-deterministic computing contributes to challenging failures in safety-critical systems. The MDCP deterministic computing platform addresses this by enabling reproducible execution traces under defined conditions—without this capability, debugging can become difficult, certification evidence may be incomplete, and liability can remain unresolved. MDCP builds on deterministic computing principles designed to address the limitations of conventional real-time operating systems.

Difficult-to-reproduce failures

Timing dependencies, race conditions, and non-deterministic schedulers can make post-failure analysis challenging rather than definitive.

£100M+ per critical failure (industry estimates)

Certification challenges

DO-178C Level A, ISO 26262 ASIL D, and IEC 61508 SIL 4 benefit from reproducible execution evidence, which is difficult to obtain with conventional non-deterministic systems.

AI/ML systems face certification barriers

Extended legal exposure

Without deterministic replay capability, liability disputes can extend for years with significant financial exposure.

Multi-billion pound exposure in prolonged disputes

Historical context: Non-determinism in safety-critical systems

Examples are illustrative and based on publicly reported analyses; causal factors in complex system failures are typically multi-dimensional.

NASA Mars Climate Orbiter (1999): £100M loss. Post-incident analyses highlighted challenges in reconstructing exact execution sequences.

Aerospace Software Disputes: High-profile incidents have involved extended post-incident analysis periods due to challenges reproducing execution sequences.

Medical Device Industry: Estimated £250M/year in recall costs from failures that are difficult to precisely reconstruct.

02 The solution

The MDCP deterministic computing platform is designed to achieve bit-perfect reproducibility through deterministic kernel architecture. Execution is designed to be replayable, verifiable, and supportive of certification evidence generation.

Core design principle

Given identical initial state and input sequence, MDCP is designed to produce reproducible, bit-identical execution traces under defined system conditions, supported by cryptographic verification.

This is achieved through tick-based scheduling, deterministic memory ordering, controlled I/O, and cryptographically chained audit logs.

Determinism by construction

Tick-based execution

All operations execute at discrete tick boundaries, constraining timing non-determinism from interrupts and scheduler decisions.

Deterministic multi-core

MycoEco kernel architecture is designed to achieve deterministic parallel execution without locks or non-deterministic synchronization.

Deterministic replay engine

Instruction-level replay designed to produce byte-identical results across supported hardware architectures, enabling root cause analysis.

Cryptographic attestation

SHA-256 sealed execution traces provide tamper-evident evidence of execution sequence for regulatory compliance support.

14-kernel architecture across 7 layers

AI/ML Layer: MDRL (Reinforcement Learning), MDML (Machine Learning)

Safety Layer: PBAS-7 (Four-Axis Safety), PBAS-6 (Progressive Autonomy), EKF-V (Epistemic Uncertainty), DSC (Swarm Coordination)

Infrastructure Layer: DTL (Trust), DSEM (Semantic Evolution), MAC+ (Capability Security)

Cryptographic Layer: MDCK (Deterministic Cryptography)

Storage Layer: FungiFS (Immutable Merkle Filesystem)

Kernel Layer: MDMK (Multi-Core Kernel), UMTK (Unified Time)

Core Layer: MycoEco (Deterministic Coordination)

Technical Comparison

How Does MDCP Compare to Conventional RTOS?

See detailed side-by-side comparison of MDCP against VxWorks, QNX Neutrino, and FreeRTOS across deterministic execution, certification considerations, debugging economics, and multi-core coordination.

$5-25M

Potential certification cost savings

90-95%

Potential debug cost reduction

46KB

vs. 100-200KB conventional

View Full Technical Comparison →

03 Validation

MDCP has been validated as a proof-of-concept deterministic computing platform through comprehensive automated testing and long-duration stability analysis.

14 Production kernels

545 Automated tests passing

50M Ticks validated (579 days equivalent)

29 Novel capabilities

Validation includes cross-platform replay verification (ARM, x86, RISC-V), 50-million-tick stability testing with adversarial perturbations, cryptographic seal verification (SHA-256), and architectural design alignment with DO-178C, ISO 26262, IEC 62304, and IEC 61508 safety standards. Formal certification would be completed by the acquiring organization.

Stability test results

Duration: 50,000,000 ticks (equivalent to 579 days continuous operation)

Perturbations: 27 deliberate adversarial inputs designed to test system resilience

Recovery: 100% recovery to stable state, zero accumulating errors observed

Replay verification: Byte-identical results observed across supported hardware platforms

04 Value

MDCP is designed to deliver financial, regulatory, and strategic value to organizations deploying safety-critical autonomous systems.

Note: All financial figures are indicative estimates based on industry benchmarks and published case studies; actual outcomes depend on deployment context and organisational factors.

Cost reduction potential

Potential operational savings

Potential for significantly faster debugging

Order-of-magnitude certification cost reductions observed in comparable contexts

Can reduce duration of liability disputes

Indicative annual value £50M–£100M per organization (scenario-dependent)

Strategic differentiation

Market-level advantage

One of the first platforms explicitly designed with certification evidence generation in mind

Patent protection (GB2521625.0)

Standards compliance pathway support

Potential competitive moat 10–20 years

Safety standards addressed

DO-178C Level A — Aerospace software (catastrophic failure prevention)

ISO 26262 ASIL D — Automotive safety-critical systems

IEC 62304 Class C — Medical device software (life-critical)

IEC 61508 SIL 4 — Industrial safety integrity

05 Acquisition relevance

MDCP is designed to be acquired, licensed, or embedded as a foundational platform capability by organizations operating safety-critical autonomous systems. This acquisition model builds on MDCP's deterministic execution design and validation results.

Aerospace

DO-178C Level A considerations

Major aerospace manufacturers — Following high-profile incidents, deterministic execution and liability closure have become strategic priorities. AI certification faces challenges without reproducibility.

Autonomous Vehicles

ISO 26262 ASIL D considerations

Leading autonomous vehicle developers — Level 4/5 autonomy certification faces challenges without deterministic execution. Significant costs when failures cannot be replayed for analysis.

Medical Devices

IEC 62304 Class C considerations

Major medical device manufacturers — Significant litigation costs from difficult-to-reproduce failures. AI-based diagnostics face regulatory barriers.

Industrial Control

IEC 61508 SIL 4 considerations

Industrial automation leaders — Safety-critical industrial systems benefit from reproducible execution for certification and incident analysis.

Defense Systems

Military safety standards

Defense contractors — AI-based systems benefit from deterministic execution for accountability and compliance requirements.

Development Status: MDCP is a validated proof-of-concept platform with 14 production kernels, 545 passing tests, and 50-million-tick stability validation. Full safety certification (DO-178C, ISO 26262, IEC 62304, IEC 61508) would be completed by the acquiring organization with their certification infrastructure and domain expertise.

Strategic computing IP

MDCP is a validated proof-of-concept deterministic computing platform for safety-critical AI and autonomous systems. Detailed technical documentation, 50M-tick validation results, architectural specifications, and patent materials are available under NDA for serious acquisition discussions.

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Full technical specifications, validation data, and patent claims available under NDA for qualified strategic buyers.

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