You will get I will review your AI product claims for overclaim and leakage
Project details
I help teams make AI-related documentation safer, clearer and easier to review before it becomes public-facing.
This service is designed for AI startups, SaaS teams, product teams and organizations using LLMs, AI agents, Codex, GitHub Copilot or AI automation. I review landing pages, pitch material, product descriptions, documentation and investor-facing text for overclaim, leakage risk, unsupported readiness wording and unclear governance boundaries.
The core focus is simple: generated AI text should not automatically become a public claim.
I check whether claims about safety, compliance, automation, performance, deployment readiness or AI capability are supported by evidence and clearly separated from review, approval and operational action.
Typical deliverables include a claim-level review matrix, anti-leakage checklist, safer wording suggestions, evidence-bound notes, public-safe phrasing and open questions.
This is not legal advice and not compliance certification. It is technical AI governance and documentation review.
This service is designed for AI startups, SaaS teams, product teams and organizations using LLMs, AI agents, Codex, GitHub Copilot or AI automation. I review landing pages, pitch material, product descriptions, documentation and investor-facing text for overclaim, leakage risk, unsupported readiness wording and unclear governance boundaries.
The core focus is simple: generated AI text should not automatically become a public claim.
I check whether claims about safety, compliance, automation, performance, deployment readiness or AI capability are supported by evidence and clearly separated from review, approval and operational action.
Typical deliverables include a claim-level review matrix, anti-leakage checklist, safer wording suggestions, evidence-bound notes, public-safe phrasing and open questions.
This is not legal advice and not compliance certification. It is technical AI governance and documentation review.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Regression Analysis, Transformer ModelAI Applications
Natural Language GenerationAI Development Language
PythonAI Tools
Azure OpenAI, Bing AI, GitHub Copilot, Gradio, Hugging Face, Microsoft 365 Copilot, PyTorch, Replit, Streamlit, TensorFlowAI Models
AlphaCode, BERT, ChatGPT, DALL-E, GPT-3, GPT-4, GPT-Neo, Jurassic-2, LLaMA, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$350
|
Standard
$750
|
Advanced
$1,500
|
|---|---|---|---|
| Delivery Time | 3 days | 6 days | 12 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | - | - | - |
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | |
Model Deployment | - | - | - |
Model Documentation | |||
Model Monitoring | - | - | |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | |||
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | ||
Setup File | - | - | - |
Source Code | - | - | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$250
Extended claim matrix up to 50 claims
(+ 3 Days)
+$500
Public-safe LinkedIn / website summary rewrite
(+ 1 Day)
+$250About Andreas
KI-Berater fuer LLM-, Codex- & Agenten-Governance
Hamburg, Germany - 9:37 am local time
My focus is not generic prompt engineering. I specialize in technical AI governance: identifying where model outputs are overinterpreted, where human approval is missing, where internal information may leak, and where clear decision boundaries are needed.
I work with my own governance and audit framework, threshold-ai-slim, to analyze AI-assisted workflows, surface risks and design practical review mechanisms.
I can help with:
• LLM, Codex and AI agent workflow audits
• AI automation review before production use
• Source binding: which claim is supported by which source?
• Human-review gates: where must a person approve or stop the workflow?
• Overclaim detection: safety, compliance, performance or deployment-readiness claims
• Anti-leakage checks for internal traces, private paths, raw artifacts or sensitive data
• Decision-boundary design: Allow / Hold / Re-ground / Human Review / No Action
• Review of AI-generated website, pitch, product or investor-facing content
• Codex / GitHub workflow review: what can be automated, what requires tests, gates or approval?
Typical deliverables include governance readouts, risk matrices, human-review maps, anti-leakage checklists, public-safe wording, technical recommendations and staged roadmaps for safer AI workflow development.
I do not replace legal review or provide compliance certification. I help you make the technical workflow more controlled, more reviewable and easier to audit before it becomes operationally risky.
Best fit for teams working with OpenAI, Codex, GitHub Copilot, AI agents, internal AI tools, SaaS AI features or automation workflows that need stronger control, traceability and governance.
Steps for completing your project
After purchasing the project, send requirements so Andreas can start the project.
Delivery time starts when Andreas receives requirements from you.
Andreas works on your project following the steps below.
Revisions may occur after the delivery date.
Scope & Material Review
I review the provided AI documentation, target audience, source material and intended use to define the review scope and identify sensitive claim areas.
Claim-Level Review
I identify claims related to AI capability, safety, compliance, automation, deployment readiness, performance, reliability and governance.