Patent Pending Technology

Timing trust
you can prove.
Automatically.

Today's systems know the time. Timing Trust Fabric lets them know whether the time can still be trusted.

Existing timing services tell you your clock is accurate. Averyn Systems tells you what happened to timing trust after the signal left the source — through every downstream system, every hop, every dependent event.

Detect timing failures before they become business failures.

See How It Works Talk with the Founder

The Problem

When timing fails, you cannot
reconstruct what happened

A clock can be wrong before it alarms

GPS loss. Holdover. Oscillator degradation. Systems continue making decisions even though timing confidence is declining — silently, below alarm thresholds, until something breaks downstream.

Operations teams see symptoms, not causes

API latency. Replication lag. Ordering anomalies. Engineers spend hours or days correlating logs across dozens of systems trying to determine whether timing was involved — and often never know for certain.

Applications cannot see timing quality

Applications receive timestamps. They do not receive information about whether those timestamps are trustworthy. Infrastructure makes decisions based on time values with no knowledge of the timing confidence behind them.

Auditors ask questions after the fact

When an incident or dispute occurs, organizations need proof of what happened, when it happened, and how timing quality changed. Most infrastructures cannot reconstruct that chain — reconstruction is manual, slow, and contestable.

Operational Resilience Root Cause Analysis Compliance & Audit AI Infrastructure Cloud & Telecom

How It Works

From physical time to verifiable trust

When timing degrades anywhere in the causal chain, Timing Trust Fabric shows you exactly where it happened, what the trust state was at each hop, and provides cryptographic proof — automatically, without application changes.

TIMING TRUST FABRIC — ARCHITECTURE OVERVIEW

Timing Trust Fabric is a software framework that continuously calculates, signs, and propagates timing trust state across distributed infrastructure — automatically, without application changes.

Example Incident

The clock never alarmed. The system failed anyway.

A large SaaS provider running Kubernetes clusters across multiple regions. Hundreds of microservices. A service mesh. Distributed databases. At 2:13 AM:

What Operations Saw

→ API latency spikes
→ Database replication lag
→ Some transactions fail
→ No major alarms fire

A regional PTP grandmaster lost GPS and entered holdover. The clock stayed inside configured limits. No timing alarm was generated.

Engineers spent three days manually gathering PTP logs, switch logs, Kubernetes logs, service metrics, and database telemetry — trying to reconstruct whether timing degradation contributed.

Incident closed as "probable timing-related issue — root cause unconfirmed." It happened again six weeks later.

With Timing Trust Fabric

Every event already carries a signed trust record. When symptoms appear, the operations team queries the trust lineage:

GPS Antenna degradation
    ↓
Grandmaster GM-3
    ↓
PTP Boundary Clock
    ↓
Kubernetes Node
    ↓
Database Replica
    ↓
Application Service

Timestamps and cryptographic proof at every step. Exact point of degradation identified.

Root cause isolated in minutes. The same signed record supports any subsequent audit or regulatory inquiry.

The key distinction: Accurate clocks tell you the time. They do not tell you what happened to trust after the signal left the clock. Timing Trust Fabric closes that gap — automatically, at the infrastructure layer, without application changes.

The Solution

Infrastructure governance
for timing-dependent systems.

The Timing Trust Fabric gives distributed infrastructure the ability to know whether timing can still be trusted — and act on that knowledge automatically. When an incident occurs, the full trust lineage is already there, ready to reconstruct exactly where degradation began and how it propagated. No manual log correlation. No guesswork.

Timing failures are treated as monitoring problems. They are actually infrastructure problems. Infrastructure problems require infrastructure solutions.

Measure

Physical timing sources continuously measured across the infrastructure.

Score & Inherit

Trust score computed from measurements and causal history of predecessor events.

Sign & Propagate

Score cryptographically signed and attached to every event automatically.

Enforce & Prove

Infrastructure acts on trust state automatically. When incidents occur, full signed lineage is available on demand for troubleshooting or regulatory proof.

Govern & Respond

Trust state becomes an infrastructure control signal — driving automated operational decisions without human intervention.

Days
Typical time to reconstruct a timing-related root cause using existing tools — logs, metrics, and clock data manually correlated across dozens of systems. Often inconclusive.

No
Standardized auditable trust lineage exists in most distributed systems at the moment an incident occurs — making timing root cause reconstruction guesswork.

One
Query to reconstruct the full timing trust lineage across every system involved in an incident — with cryptographic proof at every step, available in seconds.

Why Now

Distributed systems are growing
more timing-dependent

MiFID II RTS 25 Enforcement

European regulators actively enforcing microsecond-level timestamp accuracy requirements for trading venues. Manual compliance approaches are under increasing scrutiny.

SEC Consolidated Audit Trail

SEC CAT requires broker-dealers and exchanges to report timestamped order events with defined clock synchronization accuracy, creating a need for verifiable, auditable timing records across the trade lifecycle. The auditable chain of timing evidence is now a regulatory requirement.

AI Governance Requirements Emerging

The EU AI Act and enterprise AI governance frameworks are creating new requirements for timing attestation in AI training and inference pipelines — an adjacent market opening now.

Distributed Systems Are More Complex

As financial infrastructure grows more distributed — more microservices, more cloud, more causal dependencies — the timing attestation problem becomes harder to solve with existing approaches and more valuable to solve correctly.

Use Cases

One technology. Multiple environments.

Timing Trust Fabric addresses the same core problem across industries — when timing trust degrades in distributed systems, teams need to know where it happened, when it happened, and what systems were affected.

Cloud Infrastructure

Trace timing degradation through multi-region and hybrid-cloud environments

→ Multi-region event ordering failures
→ Hybrid cloud timing boundary gaps
→ Kubernetes workload placement by trust
→ Distributed database replica consistency

AI Infrastructure

Understand timing dependencies across training, inference, and distributed compute

→ Training provenance across GPU clusters
→ Inference consistency verification
→ Data pipeline timing lineage
→ Agent traceability and governance

Financial Infrastructure

Prove timing integrity for trading, market data, and regulatory reporting

→ MiFID II and SEC CAT timestamp assurance
→ Trading dispute reconstruction
→ Hybrid colocation timing boundaries
→ Settlement hold and release governance

Telecom Networks

Monitor timing trust propagation beyond PTP and synchronization boundaries

→ Silent GPS holdover degradation
→ Cloud RAN timing trust lineage
→ Multi-vendor fault isolation
→ Synchronization assurance beyond PTP

Charlotte Andriunaitis

Founder & Inventor

Inventor — Timing Trust Fabric, Patent Pending

Distributed systems and Java development

Enterprise infrastructure transformation — telecommunications industry

MBA, PMP — University of Texas at Dallas

Based in Plano, Texas

About

Built by someone who
lived the problem

Averyn Systems was founded on a simple observation: the timing trust problem across financial, AI, and critical infrastructure is not a policy problem or a process problem — it is an infrastructure problem. And infrastructure problems require infrastructure solutions.

After years delivering large-scale technology transformation programs in the telecommunications industry, I invented the Timing Trust Fabric — a mechanism that makes timing trust a first-class infrastructure primitive, propagated automatically, signed cryptographically, and available as proof on demand.

A provisional patent was filed in May 2026. Averyn Systems is now in the market validation phase, engaging with financial infrastructure technologists to understand the deployment landscape and commercialization path.

Contact

Working on
timing-critical infrastructure?

I'd like to hear what challenges you're seeing. I am in the market validation phase and looking for conversations with engineers, architects, and operators who deal with timing-critical infrastructure. No sales pitch. Just a comparison of notes.

Email charlotte.andriunaitis@averynsystems.com Phone (469) 213-8604 LinkedIn Averyn Systems

Schedule a Discussion

Timing trust you can prove. Automatically.

When timing fails, you cannotreconstruct what happened