Statuspage tells your users your API is up. Apselog tells them whether the AI behind your API is working.

Statuspage is the incumbent. It is the right pick if you sell e-commerce, fintech, or any SaaS that does not depend on AI — the brand recognition matters in security questionnaires, and the Atlassian integrations are real.

But Statuspage was designed for web servers. It does not know what an LLM is. It cannot tell you that gpt-4o silently degraded overnight, that your token spend spiked 3x, or that your eval set dropped 12%. For AI-powered products, those are the failure modes that matter — and they are invisible to Statuspage.

The premise of a status page is: when something breaks, your customers should see it. The modern question is: what counts as broken? Statuspage answers that question the way it was answered in 2014 — your endpoint returns HTTP 200 or it does not. Apselog answers it the way an AI product actually breaks.

Provider probes for 10 LLM APIs, out of the box. OpenAI, Anthropic, Gemini, Mistral, Groq, xAI, Replicate, Fireworks, Cohere, and Together — all monitored from the second you sign up, with no integration to wire. Bedrock and Vertex get control-plane probes on Team. Pro runs at 60-second intervals. On Statuspage you would need a worker, a cron, and a custom incident POST-er — and you would still be writing the schema for “provider degraded” yourself.

Golden-set eval drift detection. The single most differentiated thing here. Upload 20 representative prompts with expected outputs. Every night at 02:00 UTC, Apselog replays them against your model and an LLM-as-judge scores them against a 7-day rolling baseline. If accuracy drops more than 5%, an Anomaly is created and an alert fires before your first support ticket lands. Statuspage has no concept of this and no way to bolt it on.

Token-spend anomaly alerts. POST your token usage to our ingest endpoint and we watch for 2.5x baseline spikes — the signature of retry loops, prompt-injection cost attacks, and runaway agents. The thing that would have shown up next month as a surprise bill instead shows up tonight as an incident card.

LLM request tracing and prompt management. Per-call latency, token counts, and errors are traceable in the dashboard, with PII scrubbed on the way in. Prompts are versioned and diffable, so when a change tanks accuracy you can see exactly which revision did it and roll it back. Statuspage does not touch this layer of the stack and never will.

AI-drafted incident summaries. When an Anomaly hits, Apselog uses Claude Haiku to draft a plain-English status update from the actual telemetry — probe state, golden-set score, token deltas. You review, edit, approve. The 2 AM status update writes itself.

60-second setup. Sign in with Google, pick a slug, and your public page at apselog.com/status/yourapp is live with all 10 provider probes already running. No integration directory to shop, no component schema to design, no webhooks to plumb before you see your first data point.

Concrete scenario. You ship an AI résumé builder, $19/mo, 1,800 paying customers, all routing to gpt-4o via a thin wrapper. Tuesday 02:14 UTC, OpenAI quietly rotates the underlying weights. The API still returns 200. Latency is unchanged. Costs are unchanged. But your cover-letter prompt that scored 0.91 on your golden set now scores 0.78. By Wednesday morning, support tickets land — “the AI is dumber today.”

With Statuspage:

Nothing happens. Statuspage is watching the HTTP probe you wired against your own API, which is green. There is no component representing model quality, because that primitive does not exist in the product. Your public page reads “all systems operational” for the entire 36 hours your accuracy is in the toilet. The first signal is a support backlog. You write the postmortem on Friday.

With Apselog:

02:00 UTC the nightly golden-set replay runs through the AI Gateway. Aggregate score drops 14% versus the 7-day rolling average — well past the 5% threshold. An Anomaly is created, severity HIGH. Claude Haiku drafts the summary: “Golden-set accuracy dropped from 0.91 to 0.78 overnight on cover-letter prompts. Provider probe for OpenAI shows normal latency and uptime, consistent with a silent model update rather than an outage.” Email and Slack alerts fire. You wake up, read the draft, click approve, and your public status page at status.yourapp.com shows the incident card before the first user opens a ticket.

The 60-second probe interval on Pro means uptime degradations show inside a minute. Drift is a nightly cron — we are honest about that. The point is not that we are faster on every dimension; the point is that we catch the degradation at all.

If your product does not depend on a language model, Statuspage is a fine choice. The things it does well are real:

• Brand recognition in security questionnaires. “We use Statuspage” ends a conversation. Apselog is a coinage that is two months old.
• A decade of Atlassian-ecosystem integrations. Jira, Opsgenie, ServiceNow, 150+ connectors. We ship Slack and webhook today.
• Mature operational hardening on plain HTTP uptime. Statuspage has run every status-page edge case in production for ten years. For non-AI services, you are paying Atlassian for that institutional memory.

If a language model is load-bearing in your product — an AI résumé builder, a writing assistant, a chatbot, an agentic workflow, a summarization feature, anything you would describe to a customer using the word “AI” — pick Apselog. The failure modes you actually face are upstream provider degradation, silent model drift, and runaway token spend. Statuspage has no primitives for any of those. Apselog has all three on day one, at the same $29 price point, with a quick setup. For AI products that distinction matters.

If your product does not depend on AI — pure e-commerce, a billing platform, a CRM, a developer tool whose reliability story is about your own services returning HTTP 200 — pick Statuspage. The brand recognition and integration depth are worth the money, and our LLM-specific features are weight you would not use.

The tie-breaker, in one sentence: how much of your customer's experience would still work if the LLM you depend on were replaced with a random number generator? If the answer is “most of it,” Statuspage is fine. If the answer is “none of it,” you want Apselog.