Everdone CodeSecurity and CodePerformance

Name: Everdone CodeSecurity and CodePerformance
Availability: InStock
Author: vinitmaniar

by vinitmaniar·Feb 17, 2026·1 point·0 comments

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AI Analysis

●●SolidSlickSolve My Problem

The Take

The product's real selling point is the iterative verification loop: AI inspects PRs/branches, surfaces exploitable issues with file+line and severity, and then re-runs reviews to confirm fixes — that workflow (Open → In Progress → Resolved → Closed/Rejected) is practical and would reduce issues slipping through. Promising as a unified place for docs, review, security and perf, but success depends heavily on low false-positive rates and transparent evidence for security findings; without that, it risks feeling like another noisy scanner.

Post Description

Hi everyone,

Over the past few months, we’ve been building Everdone — an AI-powered engineering workflow platform.

We initially launched with: - CodeDoc (AI-generated code documentation) - CodeReview (structured issue detection + tracking)

Today we’ve added two more services: - CodeSecurity — iterative application security review - CodePerformance — structured performance improvement workflow

Why we built CodeSecurity Most security tools generate a report and stop there.

In practice, teams: - Fix a few issues - Forget the rest - Don’t re-verify properly

We designed CodeSecurity as an iterative loop instead of a one-off scan: - Connect GitHub - Select a PR or branch - AI reviews for real, exploitable vulnerabilities - Engineers fix - Re-run → AI verifies whether issues are actually resolved

Issues are tracked with: - Severity (High/Medium/Low) - File + line numbers - Concrete suggested fixes - Status workflow (Open → In Progress → Resolved → Closed/Rejected) - Full verification history

It behaves more like a managed security workflow than a static analyzer.

Why we built CodePerformance Performance reviews often happen reactively (after something slows down in prod).

CodePerformance focuses on material runtime impact: - Algorithmic inefficiencies - N+1 queries - Blocking I/O - Memory pressure - Concurrency bottlenecks - Event-loop blocking (Node), GIL issues (Python), etc.

Same loop: Find → Fix → Re-run → Verified.

Current platform Everdone now includes: - CodeDoc - CodeReview - CodeSecurity - CodePerformance

Pricing: - First 200 files free - $0.05 per file per review (early access pricing) - Unlimited users - No contracts

Usage-based only.

We also have live demos on public OSS repos if anyone wants to explore without signing up.

We’re trying to build “Work as a Service” — AI systems that fit into real engineering workflows rather than replacing them or generating static reports.

Would love feedback from other founders or engineering teams.

Happy to answer anything.

— Vinit