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Next.js
React
Tailwind
Bare-Metal Servers
Cloudflare
AWS
Azure
DDoS Protection
Global CDN
Microservices Architecture
AI
LLM ReliabilityKeep the AI Models BehindYour Product Reliable
UpScanX AI monitoring watches the chat, embeddings and vision APIs your product depends on. On every check we send a test prompt to your model endpoint, measure how long the answer takes and verify that the response matches what you expect — then alert you the moment a model slows down, returns the wrong output or stops answering.
- Synthetic test prompts against chat, responses, embeddings and vision endpoints
- Latency thresholds that flag a model before it gets too slow for your users
- Response assertions that catch empty, malformed or off-target answers
AI Endpoint Health
Models RespondingPOST /v1/chat/completions
HealthyLLM Pulse · p95 1.8s · 100% uptime
POST /v1/images/analyze
SlowVision · p95 6.2s · limit 5s
POST /v1/responses
Assert failedLLM Pulse · expected phrase missing
Test prompts sent (24h)4,320 checks
AI Monitoring FeaturesMore Than a Status Code:Check the Answer Itself
Synthetic Test Prompts
Send a fixed prompt to your model endpoint on every check — exactly the way your product calls it.
- • Chat completions & responses APIs
- • Custom headers and API keys
- • Request body you control
Latency Thresholds
Measure the time to a full answer on every check and set the slowest response you are willing to accept.
- • Response time per check
- • Max latency per endpoint
- • Slowdown alerts
Response Assertions
Define what a correct answer looks like and get alerted when the model returns something else.
- • Expected keyword or phrase
- • JSON structure checks
- • Empty or truncated answers
Embeddings & Vision
Monitor more than chat: embeddings and image analysis endpoints get the same scheduled checks.
- • Embedding vector responses
- • Vision & image analysis APIs
- • LLM, EMBED and VISION types
Error & Quota Detection
Catch expired keys, rate limits and provider outages as soon as they reach your endpoint.
- • 401/403 key problems
- • 429 rate limiting
- • 5xx provider errors
Uptime History
AI monitors get the same uptime, incident counts and grouping as the rest of your monitors.
- • Uptime percentage
- • Today / week / month incidents
- • Groups with drag-and-drop ordering
Supported EndpointsMonitor Every Kind ofAI Endpoint
LLM
Chat Completions
Conversational endpoints such as /v1/chat/completions, checked with a real test prompt.
RESP
Responses APIs
Response-style endpoints such as /v1/responses, validated against the answer you expect.
EMB
Embeddings
Vector endpoints behind search and RAG, checked for a valid, non-empty result.
VIS
Vision
Image analysis and multimodal endpoints, monitored for availability and response time.
GPU
Self-Hosted Models
Models you run on your own GPUs or inference servers, behind any HTTPS URL.
GW
AI Gateways & Proxies
Gateways and proxies that route your traffic to one or more model providers.
API
Any HTTP Model API
If your product calls it over HTTPS, UpScanX can send it a test request.
Use CasesBuilt for ProductsThat Run on AI
AI Assistants & Chatbots
Know immediately when the model behind your assistant stops answering or starts answering slowly.
RAG & Semantic Search
Make sure the embeddings endpoint your search and retrieval pipeline depends on keeps returning valid vectors.
Third-Party Model Providers
Get independent data on how your AI provider actually performs instead of relying on their status page.
When an AI Endpoint Fails
Model not responding
Feature downTimeouts or 5xx errors
Wrong or empty answers
Silent failureHTTP 200, bad content
Slow responses
Users drop offLatency above threshold
With UpScanX AI monitoring: an HTTP 200 is not enough — you find out when the answer itself is wrong, not only when the server is down.
FAQFrequently AskedQuestions
What is AI monitoring?
AI monitoring is synthetic monitoring for the AI models your product depends on. UpScanX sends a test prompt to your chat, embeddings or vision endpoint at a fixed interval, measures latency, checks the response against your expectations and alerts you when something goes wrong.
How is AI monitoring different from regular API monitoring?
A regular API check usually stops at the status code. AI endpoints often return HTTP 200 while the answer is empty, truncated, slow or wrong. AI monitors send a real prompt and validate both the content and the response time of the answer.
Which AI endpoints can I monitor?
Any model API you can reach over HTTPS: chat completions and responses endpoints, embeddings, vision and image analysis, self-hosted inference servers and AI gateways. You provide the URL, headers and request body.
Will test prompts increase my AI provider bill?
Each check sends one small request, so the cost depends on your check interval and prompt size. Keep the test prompt short and choose an interval such as 5 or 10 minutes to keep token usage minimal.
How am I notified when a model fails?
AI monitors use the same alert channels as the rest of UpScanX: email, Slack, Telegram, Microsoft Teams and webhooks. You choose which channels each monitor notifies.
Want AI alerts in Slack, Microsoft Teams or your own webhook?
See IntegrationsRelated Monitoring Services