Why PulseRoute

Every payment processor has outages. The question isn't whether your processor will fail — it's how fast you detect it and how much revenue you lose before traffic moves.

The Cost of Slow Detection

When a processor starts failing, every second of delay costs you transactions. Here's what a typical outage timeline looks like:

                          Processor A Outage Begins
                                    │
                                    ▼
  ┌──────────┬──────────┬──────────┬──────────┬──────────┐
  │ Healthy  │ Degrading │ Outage   │ Recovery │ Healthy  │
  │          │          │          │          │          │
  │ 98% SR   │ 92%→80%  │ 15% SR   │ 80%→95%  │ 98% SR   │
  └──────────┴──────────┴──────────┴──────────┴──────────┘
                  │                       │
         Without PulseRoute:      With PulseRoute:
         You find out here ──┐    Traffic shifted here ──┐
         (15-30 min later)   │    (within seconds)       │
                             ▼                           ▼
                      ~450 failed txns            ~12 failed txns

Simulation Results

We run continuous simulations against realistic processor failure scenarios. Here are the results:

Scenario 1: Sudden Processor Outage

A processor goes from healthy to full outage. 500 transactions over the incident window.

Metric	Without PulseRoute	With PulseRoute (Tier 1)
Success rate	~70%	~90%
Failed transactions	~150	~50
Detection time	Manual (15-30 min)	Automatic (<30 sec)
Recovery	Manual	Automatic

Result: ~100 rescued transactions per incident.

Scenario 2: Gradual Degradation

A processor slowly degrades over minutes before full outage. 600 transactions. This is the harder case — latency creeps up, error rates inch higher, but nothing screams "outage" until it's too late.

Metric	Without PulseRoute	With PulseRoute (Tier 1)	With Prediction (Tier 2)
Success rate	~82%	~88%	~92%
Failed transactions	~108	~72	~48
Detection	Never (gradual)	After threshold breach	Before threshold breach

Result: Tier 2 prediction catches the degradation pattern 30-60 seconds before error rates cross the failover threshold.

Scenario 3: Continuous Optimization

Both processors are healthy but performing differently. 900 transactions with alternating degradation periods.

Metric	Static Routing	PulseRoute Tier 3 (Autopilot)
Success rate	~88%	~94%
Traffic allocation	Fixed 90/10	Dynamic, follows performance
Adaptation	None	Continuous

Result: Even when nothing is "broken," adaptive routing improves success rates by continuously favoring the better-performing processor.

Revenue Impact

For a business processing 100,000 transactions/month at $75 average order value:

Scenario	Failed Txns Rescued	Revenue Saved
1 outage/month (sudden)	~100	$7,500
2 degradation events/month	~120	$9,000
Continuous optimization	~600	$45,000
Combined monthly impact	~820	~$61,500

These are conservative estimates from simulation data. Actual impact depends on your transaction volume, processor reliability, and average order value.

Reactive vs. Predictive Timeline

Here's what the detection timeline looks like for a gradual degradation event:

Time ──────────────────────────────────────────────────────►

         Degradation       Error rate        Full
         begins            hits 10%          outage
            │                 │                │
            ▼                 ▼                ▼
Processor:  ████████████████████████████████████░░░░░░░░░░░░
            healthy    degrading    degraded    outage

Tier 2:     ·····▓▓▓▓▓▓▓▓▓▓▓▓░░░░░░░░░░░░░░░░░░░░░░░░░░░░
                  ↑ Prediction triggers
                  │ pre-emptive shift
                  │ (~30-60 sec early)

Tier 1:     ·····················▓▓▓▓▓▓░░░░░░░░░░░░░░░░░░░░
                                 ↑ Threshold triggers
                                 │ reactive failover

Manual:     ·····································▓▓▓▓▓▓░░░░░
                                                 ↑ Alert fires
                                                 │ engineer responds

            ████ = healthy traffic  ▓▓▓ = traffic shifting  ░░░ = failed over

The gap between Tier 2 and Tier 1 detection is where PulseRoute saves the most transactions — failures that happen after degradation starts but before error rates are obviously bad enough to trigger traditional monitoring.

Shadow Mode: See Before You Commit

Not convinced? Run PulseRoute in shadow mode first. It observes your real production traffic without changing any routing decisions, then generates a report showing:

• How many transactions it would have routed differently
• How many failures it would have prevented
• The estimated revenue impact based on your average order value

# Check the shadow mode report after a few days
curl https://api.yourcompany.com/v1/shadow-report?average_order_value=75

No risk, no code changes to your routing logic. Just data.