Silent latency spikes
A 500ms delay in time to first token can make an AI feature feel broken, even when the API technically succeeds.
OUTSIDE-IN MONITORING FOR AI APIS
See what AI status pages miss.
ProbeGrid measures real-world LLM API latency, throughput, errors, and regional degradation across providers, models, and cloud regions.
Track time to first token, token throughput, timeout rates, and silent brownouts before they reach your users.
Built for platform teams, AI-native SaaS companies, and engineering leaders running production LLM workflows.
AI Provider Telemetry
Example synthetic probe window · last 30 minutes
sample probes online
Provider comparison
TTFT p95
| Provider | Model | Region | Trend | TTFT p95 | Status |
|---|---|---|---|---|---|
| OpenAIgpt-4o-mini | gpt-4o-mini | us-east-1 | 812ms | Normal | |
| Anthropicclaude-sonnet | claude-sonnet | us-east-1 | 1.4s | Elevated | |
| Googlegemini-flash | gemini-flash | eu-west-1 | 940ms | Normal | |
| Azure OpenAIgpt-4o-mini | gpt-4o-mini | eastus | 3.8s | Degraded | |
| Bedrockllama-3.1 | llama-3.1 | us-west-2 | 1.1s | Normal |
Silent slowdown detected
Azure OpenAI / eastus
TTFT p95 increased 4.6x for 17 minutes. Control latency stable. Provider status: no incident reported.
TTFT p95
+4.6x
Control
stable
Region grid
6 probes
us-east-1
us-west-2
eu-west-1
westeurope
eastus
ap-southeast-1
Early telemetry
Live probe running · baseline forming now
Provider
OpenAI / gpt-4o-mini
Signals
TTFT · tokens/sec · total latency · errors · validation
Expanding next
Anthropic · Google · Azure · Bedrock · more regions
AI outages do not always look like outages.
A provider can be up while your product feels slow. First-token latency can spike. Streaming throughput can drop. One region can silently degrade while another looks healthy.
Provider status pages are useful, but they are often too coarse for production AI systems. ProbeGrid gives teams independent visibility into the performance of the AI APIs their products depend on.
Regional brownouts
Your users in one geography may see degraded performance while another region looks healthy.
Vendor blind spots
Provider dashboards rarely expose the model, region, and routing behavior that affects your actual user experience.
Purpose-built telemetry for LLM APIs.
Traditional uptime checks are not enough for AI. ProbeGrid tracks the moments that determine whether an AI workflow feels instant, sluggish, or broken.
Time to First Token
How long before the response feels alive.
Tokens per Second
How quickly the model streams after generation begins.
Total Response Time
End-to-end latency for complete responses.
Error and Timeout Rate
Failures, API errors, malformed streams, and timeout behavior.
Regional Variance
How performance changes across cloud regions and user geographies.
Status Page Gap
Observed degradation compared with provider-reported incidents.
A global probe network for AI infrastructure.
ProbeGrid runs fixed LLM workloads from independent cloud regions on a continuous schedule, then turns noisy telemetry into degradation windows, provider comparisons, and routing signals.
Run synthetic probes
ProbeGrid runs fixed LLM workloads from independent cloud regions on a continuous schedule.
Capture AI-specific timing
Each request captures TTFT, throughput, total latency, errors, response validation, and control endpoint timing.
Detect degradation windows
ProbeGrid turns telemetry into degradation windows, provider comparisons, and routing signals.
Control requests help separate local network noise from upstream AI provider behavior.
For teams accountable for AI performance.
ProbeGrid helps platform, product, and infrastructure teams monitor the LLM APIs behind production features, agents, and internal workflows.
AI-native SaaS
Know when customer-facing latency comes from your app, your provider, or a regional infrastructure issue.
Platform engineering
Monitor the LLM APIs behind internal tools, agents, support workflows, and production features.
SRE and incident response
Use independent telemetry to separate provider degradation from your own systems during incidents.
Vendor evaluation
Compare providers by real-world latency, throughput, and reliability before shifting traffic or signing contracts.
Routing and fallback
Decide when to route around degraded models, providers, or regions.
Vendor and SLA evidence
Bring external performance data to vendor reviews, SLA discussions, and architecture decisions.
From raw probes to decisions.
ProbeGrid is designed to compress repeated synthetic measurements into incident-shaped signals your team can use during reliability reviews and vendor decisions.
Silent slowdown detected
Azure OpenAI eastus showed a sustained first-token latency regression while control latency and adjacent regions stayed stable.
p95 TTFT
+4.2x
Duration
22m
Control
stable
Status page
clear
12:00normal
12:15elevated
12:22degraded
12:39recovered
p95 TTFT increased 4.2x for 22 minutes while control latency remained stable.
p95 TTFT +4.2x
22m window
status clear
Provider B delivered 31% lower p95 TTFT in Western Europe over 24 hours.
-31% p95 TTFT
eu-west
24h sample
East US degraded while West US remained stable. Route latency-sensitive traffic accordingly.
eastus degraded
us-west stable
failover candidate
Example data shown for illustrative purposes.
Not another internal observability tool.
Your logs tell you what happened inside your system. ProbeGrid shows what your AI providers looked like from the outside, across regions, models, and time.
Provider status pages
Binary, delayed, and provider-controlled.
Internal observability
Powerful, but limited to your own stack.
Generic uptime checks
Miss streaming behavior, token throughput, and model-level degradation.
ProbeGrid
Independent, AI-specific, region-aware performance intelligence.
Help define the benchmark for production AI infrastructure.
ProbeGrid is currently collecting early telemetry and working with teams that rely on LLM APIs in production. If latency, provider reliability, or multi-provider routing matter to your product, we want to talk.
Request early access