Senior AI SaaS Auditor for LLM Visibility / AI Search Product AIO GEO SAAS

We are looking for an independent senior technical auditor to review a delivered AI SaaS product focused on AIO / GEO / LLM visibility across platforms such as ChatGPT, Gemini, Perplexity, and similar AI-driven answer engines. This is not a development role. We need a neutral expert who can evaluate whether the delivered product is technically solid, commercially credible, and aligned with the original scope. Product context The SaaS is designed to help brands and websites understand and improve their visibility in AI-generated answers, LLM-driven search experiences, and generative answer engines. This includes areas such as: - AIO (AI Optimization) - GEO (Generative Engine Optimization) - brand/entity visibility inside AI answers - answer presence and citation patterns - competitor comparison across LLMs - sentiment, resonance, and mention analysis - scraping, extraction, scoring, and dashboard reporting The delivered project appears to include: - [login to view URL] / React frontend - FastAPI / Python backend - authentication, dashboards, database, async/background flows, and AI-related processing modules What we need from you We need someone who can audit the project from both a technical architecture and AI product logic perspective. 1. AI / LLM product credibility Please evaluate: - whether the product logic actually makes sense for AIO / GEO / LLM visibility - whether the workflows for analyzing ChatGPT / Gemini / Perplexity style outputs are technically meaningful - whether the scoring, extraction, ranking, and analysis logic is substantive or superficial - whether this feels like a real product in the AI search / generative visibility space, or mostly a shallow wrapper 2. Scope vs implementation Please compare the original specification/documentation against the delivered codebase and classify major components as: - Complete - Partially complete - Missing - Placeholder / demo-level only - Misleading or not production-ready 3. Code and architecture review Please review: - code quality - maintainability - frontend/backend structure - database consistency - API quality - async/background processing design - production readiness - scalability and reliability - signs of rushed development or recycled boilerplate 4. Security and engineering risks Please identify: - authentication weaknesses - secret/config problems - weak environment handling - dangerous defaults - broken or inconsistent data flows - poor engineering decisions that would reduce trust in the system 5. Final judgment We want a blunt final conclusion on: - whether this is a real V1 SaaS, a prototype, or an incomplete build - whether the AI / LLM aspects are technically credible - whether the delivered system appears aligned with a serious paid SaaS build - whether the implementation quality matches the expected scope Deliverables Please provide: - a written audit report in clear English - issue severity levels: Critical / High / Medium / Low - executive summary for a non-technical founder - code references or screenshots where relevant - a final honest conclusion on both technical quality and commercial credibility Ideal background Please apply only if you have strong experience in some of the following: - LLM products - Generative AI systems - AIO / GEO / AI visibility / AI search - technical due diligence - SaaS code audits - Python / FastAPI - [login to view URL] / React - systems involving extraction, scoring, ranking, or answer analysis Important We are not looking for: - a generic full stack developer - a basic code reviewer - a traditional SEO specialist with no LLM product experience - a chatbot builder with shallow AI experience We want someone who understands both: - AI / LLM product logic - real SaaS architecture and production quality Proposal instructions To apply, please include: 1. Similar AI / LLM / SaaS systems you have audited or reviewed 2. Your experience with technical due diligence or architecture review 3. Your experience with AIO, GEO, LLM visibility, answer engines, or AI search-related systems 4. Your preferred pricing model and estimated time for: - a first-pass review - a full audit 5. The phrase: AIO audit first

ID do Projeto: 40319680