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 a clear explanation — root cause, affected files, and suggested fixes — without digging through logs yourself.

Recent logs

GET/api/health20012ms
POST/api/checkout500142ms
GET/api/users/4220038ms

AI analysis

Root cause

Null reference when accessing user.email during checkout

87% confidence

Affected file

src/controllers/checkout.controller.js

Suggested fix

Add a guard before accessing user.email

1 call

Per request log

No agents or SDKs

Any stack

Language agnostic

Node, Python, Go, Ruby…

GitHub

Repo connected

Errors tied to your code

Seconds

To first insight

Automatic on errors

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 status and an error string, but no clear link to the code path that caused it. Debugging becomes guesswork.

Context switching kills momentum

Jump between log viewers, GitHub, and your IDE just to understand one production failure. Every minute counts.

Full APM is overkill

Enterprise observability tools are expensive, complex, and take weeks to set up. You just need to know what broke and how to fix it.

What is Zicroe?

Lightweight observability with built-in debugging

Zicroe is an API observability platform for teams that ship fast and need to debug production errors without digging through logs or spinning up a full APM stack. Ingest request logs with a single HTTP call, link your GitHub 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, response time, and custom metadata. Filter, search, and drill into any log instantly.

GitHub-connected debugging

Link each application to its GitHub repository. Your codebase is indexed so error analysis understands real source files — not just stack traces.

AI root-cause analysis

Failed requests are investigated automatically. Get root cause, affected files, explanation, suggested fix, and a copy-ready patch.

Project hierarchy

Organize by project, environment, and application. Keep staging, production, and client work cleanly separated with isolated keys per app.

Patch pull requests

When analysis produces a verified patch, open a GitHub pull request directly from the dashboard — or copy the diff and apply it yourself.

Bring your own AI keys

Paste your provider API key — OpenAI, Google, AWS Bedrock, Anthropic, or Groq. Zicroe uses predefined models per provider; you control billing directly with your vendor.

Bring your own key

Your API keys. Your bill. Your control.

Zicroe is a bring-your-own-key platform. Add your provider API key and we handle the rest — including which model runs for analysis. You pay your provider directly; we never resell tokens or bundle inference into your subscription.

OpenAI logo

OpenAI

Native integration

Google logo

Google

Native integration

AWS Bedrock logo

AWS Bedrock

Native integration

Anthropic logo

Anthropic

Native integration

Groq logo

Groq

Native integration

Save your API key once in the dashboard, assign it to an application, and Zicroe uses it automatically when analyzing errors. No model picker — just your key.

From error log to fix

Every failed request comes with an explanation

When a request fails, Zicroe automatically investigates the error and tells you what went wrong — root cause, which files are involved, and how to fix it. Everything you need to act on is right in your dashboard.

No manual triage. No context switching between logs, GitHub, and your IDE.

  • Root cause with confidence score
  • Affected files in your repository
  • Plain-language explanation
  • Suggested fix and copy-ready patch
  • One-click GitHub pull request

POST /api/checkout · 500

Error
Cannot read property 'email' of null
AI analysis

Root cause

Null reference in user lookup when email is missing

Affected files

src/controllers/users.controller.js

Suggested fix

Add a guard before accessing user.email

Patch

Unified diff — copy and apply

Organized by design

A hierarchy that mirrors how you ship

Projects contain environments. Environments contain applications — each with its own API key. Keep client work, internal tools, and production services cleanly separated without spinning up separate accounts.

Project

E-commerce Platform

Environment

Production

Application

checkout-api

zic_live_•••

How it works

Up and running in four steps

Go from signup to AI-powered debugging in minutes. Integrate with a single HTTP POST from any language or framework.

01

Create your workspace

Sign up, connect GitHub, add your model API keys, and create your first application with an ingestion key.

02

Index your repository

Your linked GitHub repo is indexed automatically so error analysis understands your actual codebase — not just stack traces.

03

Send logs

POST request metadata after each API call with a simple JSON payload. No agents or heavy SDK — just an HTTPS call from any language.

04

Get answers

Error logs are analyzed automatically. Root cause, affected files, fix suggestions, patches, and optional GitHub PRs appear in your dashboard.

Integration

One HTTP call. Any language.

No agents or heavy SDKs. After each API request, POST a JSON payload with the method, endpoint, status code, response time, and optional error message. Each application has its own API key for secure, isolated ingestion.

Works with Express, FastAPI, Rails, Laravel, Go stdlib, or any HTTP client.

POST /api/logs
X-API-Key: YOUR_APPLICATION_API_KEY
Content-Type: application/json

{
  "timestamp": "2026-06-11T14:30:00.000Z",
  "method": "POST",
  "endpoint": "/api/checkout",
  "statusCode": 500,
  "responseTime": 142,
  "errorMessage": "Cannot read property 'email' of null",
  "stack": "TypeError: Cannot read property 'email' of null\n    at checkout (src/routes/checkout.js:48:22)",
  "metadata": { "orderId": "ord_123" }
}
// Node.js — add after your route handler
await fetch("https://api.zicroe.com/api/logs", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "X-API-Key": process.env.ZICROE_API_KEY,
  },
  body: JSON.stringify({
    timestamp: new Date().toISOString(),
    method: req.method,
    endpoint: req.path,
    statusCode: res.statusCode,
    responseTime: Date.now() - start,
    errorMessage: err?.message,
    stack: err?.stack,
  }),
});

Built for

Teams that ship APIs and need answers fast

Solo developers & startups

Ship fast without standing up Datadog or New Relic. One HTTP call after each request and you're covered when production breaks at 2 AM.

Agencies & consultancies

Manage multiple client APIs from one dashboard. Separate projects and environments per client, with isolated keys and clear log boundaries.

Backend teams

Monitor microservices, webhooks, and internal APIs from a single dashboard. Know which service failed, why, and where to look in the repo.

Why Zicroe

Observability without the overhead

You don't need a six-figure APM contract to understand why your API returned a 500.

 ZicroeTraditional APM
Setup timeMinutesDays to weeks
IntegrationSingle HTTP POSTAgents, SDKs, config
Error debuggingAutomatic root-cause analysisManual log digging
Code contextIndexed from your GitHub repoSeparate tools
Fix deliveryCopy patch or open GitHub PRManual implementation
Pricing complexityStraightforwardPer-seat, per-host, per-GB

FAQ

Common questions

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. The next production error comes with an explanation.

Featured on

Featured on Startup.sx