For AI Startups Raising Series A/B
Investors are asking: "How do we know your AI is ethical?" You have 48 hours until the partner meeting. We deliver evidence-based documentation using our proprietary Ma'at-Score™ framework—powered by local LLMs for complete privacy.
No human override for high-stakes decisions. Fix before close.
You're 3 weeks from term sheet close. The partner sends over their checklist. There's a section you've never seen before.
"How do we know your AI is ethical?" Your team says it's fine. You have product docs, but zero AI ethics documentation.
Big 4 audits take 6 months. You have 48 hours. You need proof, not promises. Documentation that satisfies institutional due diligence.
Evidence-based assessment using the Ma'at-Score™ framework. Delivered in 48 hours. Fixed price. Guaranteed. Investor-ready documentation.
Not opinions. Evidence. Every score backed by documentation from your materials. Every risk mapped to investor concerns.
Your AI scored across 8 ethical principles. Total score out of 40 with risk classification.
Specific vulnerabilities mapped to investor concerns: bias, privacy, misuse, governance gaps.
Actionable checklist ranked by impact and implementation difficulty. Fix before close.
Every claim backed by document references, quotes, and links. "Not Evidenced" flags where documentation is missing.
Walk through findings with your team. Answer questions. Clarify next steps for the data room.
30 minutes. Document handoff. Scope confirmation.
Deep dive into your PRDs, model cards, policies. Score each principle.
Identify top 10 risks. Prioritize fixes by impact and difficulty.
Quality check. Evidence pack assembly. Formatting.
Report delivered. Debrief call scheduled.
Inspired by the ancient Egyptian principle of Ma'at—truth, balance, order, and justice. Eight principles that map directly to what investors ask about.
Transparency & Explainability
Can users understand how the AI makes decisions?
Fairness & Non-Discrimination
Does the AI treat all groups equitably?
Data Governance & Privacy
Is personal data handled responsibly?
Accountability & Redress
Can affected parties seek remedy?
Stakeholder Alignment
Are all stakeholder interests considered?
Ethical Purpose
Does the AI serve legitimate, beneficial purposes?
Competence & Reliability
Is the AI technically sound and reliable?
Continuous Improvement
Is there ongoing oversight and adaptation?
No data leaves your premises. We use local LLMs (Phi-3 3.8B) running on optimized hardware for complete confidentiality.
What your report actually looks like. Evidence-based, investor-ready, actionable.
Mapped to investor concerns