Freelancer profile translated to English.

Description

You built your app with Lovable, Bolt, Cursor, v0, Replit Agent or Claude Code. It works in demo. But as soon as there are real users, it bugs, hallucinations, fragile security, dead scaling. Stuck at 70-80% to launch?

I audit and make AI-generated apps production-ready in 48 hours. Full report + concrete fixes.

My 3 service levels:

• Express Audit — 1 critical flow, top 3 bugs + maturity score

• Full Audit + Roadmap — full audit up to 2000 LoC, fix top 5 bugs, production roadmap

• Total Overhaul — clone repo, fix all bugs, tests, refactor, hardening

What sets me apart:

• Deterministic anti-hallucination checker: my method blocks unsourced outputs. From Beaume, my open-source RAG engine that achieves 0 hallucination on numerical thresholds (tested in production on 672K legal documents).

• Senior approach, not a $15 seller: architecture, security, performance — not just "it compiles".

• AI-native from day 1: I direct AI agents to deliver 10x faster.

Stack: Python, LLM (Claude/GPT/Gemma), RAG, BGE-M3, FAISS, PageRank, Swift (iOS), React/Next.js, Supabase. Specialized in the vibe-coding ecosystem: Lovable, Bolt, Cursor, v0, Replit Agent, Base44, Claude Code.

Proof:

• Beaume (open source): github.com/mathieuballotma-sketch/lucie

• Bocaux (iOS): budget management app in progress

Goal: unlock the missing 20-30% for you to LAUNCH, sell, scale. Operational English, remote work only.

Industry field of expertise

Languages

French
Native or bilingual
English
Fluent

Workplace preferences

Remote only

Primarily works remotely

Orionix
Founder · AI App Auditor
June 2026 - Today
You built your app with Lovable, Bolt, Cursor, Claude Code, v0, Replit Agent...

It works perfectly in demo. But as soon as there are real users, it bugs, hallucinations, fragile security, dead scaling. You're stuck at 70-80%? It's not you. Most vibe-coded apps die exactly there.

ORIONIX METHOD
• Full audit of spaghetti code (AI generators anti-patterns)
• Deterministic anti-hallucination checker before each LLM response (often 60-70% → 90%+ recall)
• Silent killers: race conditions, absent error handling, N+1 queries, fragile security, failed scaling
• Delivery of your choice: detailed report OR total overhaul (clone + fix + tests + clean handover)

PROOF
• Bocaux — native iOS app (5500 LoC, 102 tests, StoreKit 2, Family Controls)
• Beaume — RAG verifier 672K docs, 90% recall@10, BGE-M3 + PageRank, 3-brain architecture, 100% local. Deterministic verifier tested in production. Open source: github.com/mathieuballotma-sketch/lucie

STACK: Claude, Python, Swift, React, RAG, agents.

Specialized in apps made with Lovable, Bolt, Cursor, v0, Replit Agent, Claude Code.

Goal: pass the missing 20-30% so you can LAUNCH and sell.

Delivery in 48 hours.
Python LLM RAG Artificial Intelligence Code Audit