Apselog vs Helicone
Helicone answers "what went wrong in my LLM call?"
Apselog answers "should my user trust this product right now?"
Helicone built the engineer-internal observability dashboard for LLM apps. Apselog built the customer-facing surface. Both have a place — but if your problem is angry users when OpenAI hiccups, prompt-injection cost spikes you don't catch until the bill arrives, or silent model drift that quietly erodes accuracy, Apselog is the tool built around that workflow. At $29/mo Pro (well under Helicone's $79), with tracing, versioned prompts, PII scrubbing, 60-second probes, public subscribers, embed badges, PagerDuty and Opsgenie integrations, and 10 provider probes — all shipped today.
TL;DR
Apselog gives you a branded public status page, golden-set drift detection, token-spend anomaly incidents, lightweight tracing, versioned prompts, PII scrubbing by default, 60-second probes, end-user subscribers, embed badges, PagerDuty and Opsgenie integrations, and custom theming — at $29/mo Pro. Helicone gives you a deeper internal trace viewer and prompt playground at $79/mo Pro. If your buyer is the engineer who needs full-payload replay, Helicone. If your buyer is the founder whose users notice when an LLM provider degrades — and who'd like to keep more than 80% of the price difference — Apselog.
Feature comparison
Verified against Helicone's public docs and pricing page as of May 2026.
| Capability | Apselog | Helicone |
|---|---|---|
| Customer-branded public status page (your domain) | Yes status.yourapp.com on Pro | No helicone.ai/status only |
| End-user incident email subscribers | Yes visitors subscribe from your page | No |
| Embeddable status badge / iframe | Yes drop into your marketing site | No |
| Provider uptime probes (OpenAI, Anthropic, Gemini, +7 more) | Yes 10 providers, 60s on Pro | Yes their own status page only |
| 60-second probe cadence | Yes Pro tier | No |
| Golden-set eval drift detection (nightly) | Yes LLM-as-judge, 5%+ drop → incident | No |
| Token-spend anomaly → public incident | Yes 2.5x baseline = HIGH severity | No cost dashboard only |
| AI-drafted incident summaries (human-reviewed) | Yes Team tier | No |
| Automatic PII scrubbing on ingest | Yes emails, keys, tokens stripped | Yes enterprise tier |
| Lightweight request tracing | Yes /api/traces/ingest → /dashboard/traces | Yes |
| Prompt management + versioning | Yes addressable as <slug>@<v> | Yes |
| Out-of-band by design (we never proxy your LLM traffic) | Yes POST aggregated usage events | No SDK-wrapping is their core |
| PagerDuty native integration | Yes Events API v2 dispatch | No |
| Opsgenie native integration | Yes US + EU regions | No |
| Scheduled maintenance windows | Yes public-page banner | No |
| Audit log | Yes dashboard-action trail | No |
| Custom status-page theming (fonts, radius, colors) | Yes sanitized tokens, no raw CSS | No |
| Multi-region probes | Yes 3 regions (US + EU + APAC) on Team | No |
| Bedrock + Vertex probes | Yes control-plane probes, no token cost | Yes full SDK support |
| Indie pricing: paid tier under $30/mo | Yes Pro $29/mo | No Pro $79/mo |
| Free tier with all 10 LLM providers monitored | Yes Open tier, $0 | Yes free indie tier |
| Full request/response payload logging + grep | roadmap | Yes |
| Prompt playground + A/B replay against historical data | roadmap | Yes |
Where Apselog wins
Every LLM-observability competitor we have surveyed — Helicone, Langfuse, Braintrust, LangSmith, Datadog LLM Obs — points at the engineer with a login. Apselog is built around the person who's actually inconvenienced when an AI app breaks: your user.
The status page IS the product
Helicone runs helicone.ai/status as a public LLM-provider checker — but it's Helicone's page, not yours. Your end users have no URL to bookmark when your AI app goes down. Apselog gives every customer status.yourapp.com on Pro at $29/mo, with their logo, their domain, no vendor badge. When OpenAI degrades at 3am, your user opens your status page — not Twitter — and sees a calm, plain-English incident summary: "OpenAI is degraded since 03:42 UTC. This is upstream. Here's the OpenAI status link." That's a support ticket you didn't have to answer.
End-users subscribe — your status page becomes a viral loop
Visitors to your Apselog page can subscribe their email to get notified the moment an incident is published. Every angry-tweet-in-the-making becomes an opt-in to your incident channel instead. Helicone has no public-subscriber concept — their page is for their dashboard users, not your users' users. This is the difference between a tool and a surface.
Golden-set drift catches silent model updates Helicone can never see
When OpenAI ships a silent weight update to gpt-4o on a Tuesday, your endpoint still returns 200, Helicone's traces still look healthy, and your classifier accuracy quietly drops 12%. Apselog runs your golden eval set every night against your chosen model, uses Claude Haiku as a judge, and fires an incident if scores drop 5%+ vs the 7-day rolling average. The dashboard-first cohort cannot do this — they only see what your app calls, not whether the model is still the model you signed up for.
Token-spend spikes become customer-visible incidents within the hour
A runaway retry loop, a prompt-injection that triggers 10x token consumption, an agent stuck in a thought loop — Helicone shows these on a cost graph an engineer might check tomorrow morning. Apselog turns a 2.5x spend baseline breach into a HIGH-severity Incident with an AI-drafted summary that even attempts to localize the cause ("cost concentration in /chat suggests retry loop"), fires Slack + email + webhook, and — when you approve — publishes it to your status page. This single workflow is the row in the matrix nothing else productizes.
Lightweight tracing without giving up your traffic
Apselog ships tracing too — POST spans to /api/traces/ingest, view them at /dashboard/traces. It's deliberately lightweight: enough to investigate the request behind an anomaly, not so heavy it forces you to route every LLM call through us. You keep your latency, your privacy posture, and your provider keys. If you outgrow this and need deep trace replay, you can layer a dedicated tool on top — but most teams shipping AI products never will.
Versioned prompts you can ship from the dashboard
Apselog includes prompt management at /dashboard/prompts. Templates are versioned and addressable as <slug>@<v>, so your runtime pins a specific version and you ship a new one without a deploy. This isn't a full playground with A/B replay against historical data — that's Helicone's home turf — but it covers the 80% case (version, address, ship) without making prompts a separate vendor.
PII scrubbing on by default — not an enterprise upsell
Apselog scrubs emails, API keys, JWTs, and obvious tokens from anything posted to /api/usage/ingest and /api/traces/ingest. Free tier, Pro tier, every tier. Helicone gates PII redaction behind their enterprise plan. If you're an indie founder who's even slightly conscientious about what leaves your servers, that's a meaningful difference.
Out-of-band architecture, so an Apselog outage never breaks your app
Helicone's core architecture wraps the OpenAI SDK — your LLM traffic routes through their servers so they can capture every request. That adds latency, creates a compliance question, and means a Helicone outage degrades your app. Apselog never touches your inference traffic. We probe providers from our side, you POST aggregated events from yours, and the rest is server-rendered status. If Apselog disappears tomorrow, your AI app keeps serving requests. That asymmetry matters.
60-second probe cadence on Pro — fast enough to beat the support ticket
Apselog Pro runs probes every 60 seconds against all 10 providers. From an OpenAI hiccup to a published incident on your status page is typically under three minutes — faster than your support inbox notices. It's not instantaneous — and we say so up front — but it's the right cadence for the workflow: detect, draft, ship, deflect.
A 5x lower price point at the tier that matters
Apselog Pro is $29/mo. Helicone Pro is $79/mo. For an indie AI product or a small team, the price difference is the deciding factor when picking a long-term tool. The Apselog Open tier is also genuinely free forever — all 10 providers monitored, public status URL, email alerts to one address — not a 14-day trial.
When Helicone is the right call
Helicone serves a different buyer than we do. If any of these describe your team, their depth is the right answer:
- You have a dedicated ML platform team whose daily work is prompt iteration and A/B replay against historical traces — Helicone's playground is the right tool for that workflow.
- You need to grep through full request and response payloads to debug individual user complaints — Helicone stores the bodies, by design.
- Your stack requires full SDK-level wrapping across any OpenAI-API-compatible provider — Helicone's architecture covers that breadth natively.
- You need an institutional vendor with a YC seed round and a public logo wall on the procurement form — Helicone has the track record, Apselog has the focus.
None of these describe a typical indie AI founder or a small product team — which is why we're comfortable building Apselog around the other 80%.
Which should you choose?
For most teams shipping an AI product to real customers, the choice is Apselog. The edge cases below are real, but they're edge cases.
Pick Apselog
You're shipping an AI product to users who notice when an LLM provider hiccups. You want a branded public status page they can bookmark, golden-set drift catching silent model updates, token-spend anomalies surfacing prompt-injection or runaway agents before the bill, lightweight tracing to investigate what happened, versioned prompts you can roll without a deploy, and PII scrubbing on by default. All for $29/mo. This is roughly 80% of teams reading this page.
Pick Helicone
Your team's daily work is prompt iteration and full-payload trace replay, you need SDK-level wrapping across every OpenAI-API-compatible provider, or procurement needs a YC-backed vendor on the form. Helicone is the deeper internal tool.
Run both (rare)
You're past $30k MRR with a real engineering team that needs deep internal tracing AND a non-trivial support load when providers degrade. Helicone for engineers, Apselog as the customer-facing surface. They don't overlap. One honest hedge: Apselog's tracing today is lightweight by design — if your engineers truly need full payload replay and historical A/B, a dedicated tracer still earns its line item.
Put a status page in front of your AI app today.
Open tier is free forever — 10 providers monitored, public status URL, email alerts. Pro at $29/mo unlocks your custom domain, 60-second probes, golden-set drift, token-spend anomalies, end-user subscribers, embed badges, PagerDuty and Opsgenie integrations, and versioned prompts.
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