GET IN TOUCH

Parlon Solutions for Travel & Transportation

The cutover is the risk moment. See it before it becomes an outage.

Infrastructure has changed. Observability hasn't.

Airlines, carriers, and logistics networks are running the largest infrastructure migrations in their history: reservation systems moving to the cloud, data centers consolidating onto hybrid estates, fulfillment networks re-architected node by node. Every one of those transitions creates a blind spot precisely when the schedule can't absorb one. Parlon gives migration teams a single, correlated view across the hybrid estate, validated by active synthetic testing, before the cutover, not after.

73%of IT pros likely to replace an observability tool within two years
200–300%renewal cost increases reported after private-equity acquisition
~70%Reduction in alert noise with Alert Auto-Tune™
3–8×Lower three-year TCO than legacy platforms

See it in 30 seconds

What a cutover looks like with Parlon watching it.

A 30-second look at unified visibility across a live migration.

Travel & Transportation Solutions

Built for a sector that can't afford a blind spot mid-transition.

Cutovers, cloud migrations, and network consolidations all create the same exposure: a gap between what changed and what your monitoring still assumes is true. Three entry points, one platform underneath. Start where your problem is.

What you already know

AI workloads run on layers your observability does not reach.

A thermal-throttled GPU, a rack approaching breaker capacity, an agent reading production telemetry without attribution, a congested east-west path. None of these appear in an application trace, and none of them wait for a dashboard to be reconciled.

47.7%of enterprises already run AI training or inference workloads.
35%believe their tools are ready to observe them.

EMA Network Management Megatrends 2026, n=352.

What Parlon does

  • 01
    Device-level GPU health. Utilization, thermal throttle, and ECC/XID errors on a single device, not a cluster average.
  • 02
    Power as a first-class signal. Breaker-level load, A/B feed redundancy, and capacity runway before a rack trips.
  • 03
    Agent activity, attributed. Every AI agent read tied to a known identity and audit-logged. Governance is in the platform, not a paid add-on.
  • 04
    Fabric path, hop by hop. East-west traffic and fabric health across the cluster, on the same data model as everything above.

The first question worth answeringCan you see GPU health, power headroom, agent activity, and fabric path in one place today?

What you already know

Migrations do not fail at 2am for no reason. They fail at the cutover, in daylight, on schedule.

Reservation systems moving to the cloud, data centers consolidating onto hybrid infrastructure, fulfillment networks reconfigured node by node: transportation runs on some of the tightest, most public uptime commitments of any sector, and the migration window is exactly when existing monitoring has the least context to trust.

73%of IT professionals are likely to replace an observability tool within two years.
200–300%renewal cost increases reported after private-equity acquisition.

EMA 2026 · Published SolarWinds pricing analysis, 2025.

What carries over, what gets replaced

  • Keep
    Device coverage and certifications. 250+ vendors. Nobody re-cables a network or recertifies a device to run Parlon.
  • Keep
    On-premises operating maturity. Deployment history in regulated environments carries straight over.
  • Replace
    The point-tool sprawl. One normalized data model instead of correlation across four to ten consoles.
  • Replace
    Alert volume and admin load. Alert Auto-Tune™ recommends thresholds with evidence and a human approves them.

The first question worth answeringWhich systems are load-bearing through the next cutover, and which of your monitoring assumptions won't survive it?

What you already know

Telemetry tells you what happened. It does not tell you whether the path works right now.

Passive collection reports a condition after it exists. Active validation tests the path on purpose, on a schedule you set, before a user or a workload finds the fault for you.

4–10tools used by the typical IT organization to monitor one network.
34%cite the lack of integration between them as a top challenge.

EMA Network Management Megatrends 2026, n=352.

What Parlon does

  • 01
    Native synthetics, not a module. Latency, availability, and path analysis in the same system as the telemetry.
  • 02
    Active tests within hours. Including inside fully air-gapped environments.
  • 03
    LLM-aware workflow checks. Validate the AI-dependent path, not only the network beneath it.
  • 04
    One data model behind both. A synthetic result and a device metric correlate without a swivel chair.

The first question worth answeringHow long after a change do you know the path still works?

One platform underneath

Three routes into the same data model.

The routes above are entry points, not products. Nothing here is a module, a bolt-on, or a second console.

Normalization at ingest

Every source mapped to a unified schema the moment it arrives, with vendor detail preserved. Correlation is immediate rather than reconstructed.

Synthetics and telemetry, unified

Active testing and continuous collection in one native system, including LLM-aware workflow checks.

Alert Auto-Tune™

Threshold recommendations with the evidence behind them, approved by a human. When Parlon alerts, it is worth acting on.

Deploy anywhere

SaaS, on-premises, hybrid, and fully air-gapped, with customer-controlled boundaries. In production today.

Evidence, with the record attached

One deployment, and what it does and does not establish.

Enterprise healthcare, air-gapped and HIPAA-compliant

A multi-vendor stack across more than 1,000 clinic locations, datacenters, and remote branches, consolidated into one deployment: one data model, one console, one contract. Synthetics were active within hours inside a fully air-gapped environment with strict data-residency requirements.

~50%lower observability spend than the prior multi-tool footprint
2–3 → <0.5FTE of operational effort to administer
2 → 1legacy tools replaced by one platform, one contract
Hoursfrom deployment to active synthetic tests
We found Parlon's capabilities beyond parity with the legacy vendors, and the simplicity of deployment and the cost were a significant value in themselves. Network Infrastructure Lead, enterprise healthcare provider

The evidence record

What this result establishes

  • Where observed: one production enterprise healthcare deployment.
  • How measured: against the documented cost and staffing of the replaced multi-tool footprint.
  • Configuration: on-premises, fully air-gapped, HIPAA-compliant, device monitoring and synthetic path testing.
  • What it does not establish: a universal payback period, or a result in a cloud-first or GPU-dense environment.
  • Named-use authority: anonymized here by agreement. Reference available for qualified, late-stage opportunities.

No logo wall, no generic ROI calculator. Every number on this page carries a record like this one.

Start the conversation

The first step is not migration. It is defining the decision.

Upcoming Webinar: The Four Blind Spots in AI Infrastructure

Learn More