API observability that debugs for you
Monitor your APIs.
Understand every error.
Zicroe collects structured logs from your APIs and connects them to your GitHub repositories. When something breaks in production you get the root cause, the affected files and a fix — without digging through logs.
- No agents
- No SDK
- One HTTP POST
- Bring your own key
Storefront / Production
checkout-api
- 200GET/api/health12msjust now
- 500POST/api/checkout142ms4s ago
- 201POST/api/orders88ms9s ago
- 404GET/api/users/usr_42/avatar31ms12s ago
- 200GET/api/cart24ms15s ago
- 200PUT/api/cart/items/957ms21s ago
Root-cause analysis
CompleteRoot cause
user.email is read before the guest-checkout user is loaded.
Affected file
src/controllers/checkout.controller.js
@@ -45,4 +45,5 @@
const user = await getUser(id);
- sendReceipt(user.email);
+ if (!user) return res.status(404).end();
+ sendReceipt(user.email);
Bring your own key — analysis runs on the provider you already pay for
OpenAI
Google
AWS Bedrock
Anthropic
Groq
The problem
Production errors shouldn't be a treasure hunt
Most teams know something failed. Few know why — at least not quickly.
Logs without context
You see a 500 and an error string, but no link to the code path that caused it. Debugging becomes guesswork.
Context switching kills momentum
Log viewer, GitHub, IDE, back again — just to understand one production failure.
Full APM is overkill
Enterprise observability is expensive and takes weeks to roll out. You just need to know what broke and how to fix it.
What is Zicroe
Lightweight observability with built-in debugging
Ingest request logs with a single HTTP call, link your repo, and let AI do the detective work when things go wrong. No agents, no per-host pricing, no week-long onboarding.
Centralized API logs
Every request in one place — method, endpoint, status, latency and custom metadata. Filter and drill in instantly.
GitHub-connected
Each application links to its repository, indexed so analysis reads real source — not just stack traces.
AI root-cause analysis
Failed requests are investigated automatically: root cause, affected files, explanation and a suggested fix.
Patch pull requests
When a patch verifies against your repo, open a GitHub pull request from the dashboard — or copy the diff.
Project hierarchy
Projects → environments → applications, each app with its own ingestion key. Staging and prod stay separate.
Bring your own AI keys
Use your OpenAI, Google, AWS Bedrock, Anthropic or Groq key. Zicroe picks the model per provider; you're billed by your vendor directly.
How it works
From signup to your first explained error in minutes
- 1
Create your workspace
Sign up, connect GitHub, add a model API key and register your first application.
- 2
Index your repository
The linked repo is indexed automatically, and re-indexed on every push to its branch.
- 3
Send logs
POST a small JSON payload after each request. No agent, no SDK — any language that can make an HTTPS call.
- 4
Get answers
Errors are analysed as they arrive. Root cause, files, fixes, patches and PRs land in your dashboard.
Integration
One HTTP call. Any language.
After each request, POST the method, endpoint, status and response time — plus the error and stack when it fails. Each application has its own API key for isolated ingestion.
- Works from Express, FastAPI, Rails, Laravel, Go — any HTTP client
- Send the stack trace and analysis pins the exact source files
- Rotate an app's key without touching other services
curl -X POST https://api.zicroe.com/api/logs \
-H "Content-Type: application/json" \
-H "X-API-Key: $ZICROE_API_KEY" \
-d '{ "timestamp": "2026-06-11T14:30:00.000Z", "method": "POST", "endpoint": "/api/checkout", "statusCode": 500, "responseTime": 142, "errorMessage": "Cannot read properties of null (reading 'email')", "stack": "TypeError: Cannot read properties of null...\n at checkout (src/routes/checkout.js:48:22)", "metadata": { "orderId": "ord_123" } }'Cannot read properties of null (reading 'email')
- Root cause
- Null user when the session outlives the account — email is read without a guard.
- Affected files
- src/controllers/users.controller.js
- Suggested fix
- Return 401 when the session's user no longer exists.
- Patch
- Unified diff · verified against main · ready as a PR
From error log to fix
Every failed request comes with an explanation
Zicroe investigates each error against your indexed code and tells you what went wrong, where, and how to fix it — right next to the log.
- Root cause with confidence
- Affected files in your repo
- Plain-language explanation
- Verified patch & one-click PR
Why Zicroe
Observability without the overhead
You don't need a six-figure APM contract to understand why your API returned a 500.
| Zicroe | Traditional APM | |
|---|---|---|
| Setup time | Minutes | Days to weeks |
| Integration | One HTTP POST | Agents, SDKs, config |
| Error debugging | Automatic root-cause analysis | Manual log digging |
| Code context | Indexed from your GitHub repo | Separate tools |
| Fix delivery | Copy patch or open a GitHub PR | Manual implementation |
| Pricing | Per application, flat monthly | Per seat, per host, per GB |
Solo developers & startups
Ship without standing up Datadog. One HTTP call per request and you're covered when production breaks at 2 AM.
Agencies & consultancies
Every client API in one dashboard, with separate projects, environments and isolated keys per client.
Backend teams
Microservices, webhooks and internal APIs side by side. Know which service failed, why, and where to look.
What is Zicroe?
Zicroe is an API observability platform that collects structured request logs from your services and automatically investigates production errors. Link your GitHub repo and every failed request comes with a clear explanation — root cause, affected files, and suggested fixes.
Do I need to install an agent or SDK?
No. Zicroe ingests logs via a simple HTTPS POST with a JSON body. Add one call after each API request from any language or framework — Node, Python, Go, Ruby, PHP, or anything that can make HTTP requests.
What data should I send in each log?
At minimum: timestamp, HTTP method, endpoint, status code, and response time in milliseconds. For failed requests, also send errorMessage and stack (e.g. err.stack in Node.js). You can include request IDs, IP addresses, user agents, and arbitrary metadata for additional context.
How does error analysis work?
When you link a GitHub repository to an application and an error log arrives, Zicroe automatically investigates the failure and returns actionable results — root cause, affected files, explanation, suggested fix, and an optional patch you can copy and apply.
Can I separate staging and production?
Yes. Zicroe uses a project → environment → application hierarchy. Create separate environments for dev, staging, and production, each with their own applications and API keys.
Do I need my own AI API keys?
Yes. Zicroe uses your inference API keys (OpenAI, Google, AWS Bedrock, Anthropic, or Groq) for error analysis. Create a model API key in the dashboard and assign it to each application. You control usage and billing directly with your provider.
Can I create a pull request from a suggested fix?
When analysis produces a verified patch, you can open a GitHub pull request from the log detail page with one click, or copy the unified diff and apply it manually.
Is my source code stored?
Zicroe connects to your GitHub repository to understand your codebase when analyzing errors. Your code stays in GitHub — Zicroe uses it for context, not as a replacement for version control.
Stop guessing. Start fixing.
Create an account, link your first repository and start sending logs. Your next production error comes with an explanation.
