ASIRI evaluates your code, LLM architecture, security posture, IP exposure, PII handling, and operational readiness — then turns the findings into an investor-ready risk report.
Sample investor readiness score showing a company with clear promise but material diligence questions to address.
Investor-oriented technical diligence output delivered fast enough to use before a live fundraising process accelerates.
Core diligence domains covered: security, IP, AI safety, architecture, privacy, and token economics.
Conditionally Investable. Moderate diligence risk.
This sample company is commercially promising but has technical and AI operational gaps that should be remediated before serious investor review.
Secrets exposure creates immediate security and diligence risk for investors reviewing production hygiene.
Unsafe prompt handling may allow malicious input to override instructions and compromise system behavior.
Single-model dependency weakens resilience and raises diligence concerns around uptime and continuity.
Current orchestration increases inference cost and weakens margin assumptions under scale.
Monitoring and traceability gaps make incident response slower and reduce confidence in operating maturity.
The hero shows the report itself. This section explains what sits behind it: what an investor or partner would review, what founders can act on immediately, and where diligence questions are most likely to surface.
A concise investor-oriented overview of the company’s diligence profile, core blockers, and the questions most likely to come up in initial review.
Domain-by-domain analysis across security, IP ownership, open-source exposure, AI / LLM safety, architecture, privacy controls, and token economics.
A prioritized remediation roadmap founders can use right away to reduce diligence friction before active fundraising begins.
ASIRI does not rely on a simple checklist or questionnaire. We combine technical evidence, repository signals, architecture review, AI/LLM risk analysis, IP and open-source exposure, privacy indicators, and operational maturity signals.
Findings are mapped against recognised frameworks including NIST, CIS Controls, OWASP, NIST SSDF, OWASP SAMM, OWASP ASVS, OWASP Top 10 for LLM Applications, and NIST AI RMF.
Repository signals, code patterns, architecture inputs, privacy indicators, and supporting documents are gathered for review.
Observed issues are organized against established security, software assurance, privacy, and AI governance standards.
ASIRI highlights the issues most likely to create objections during technical diligence, investment review, or follow-up requests.
The final Investor Readiness Score is generated using ASIRI’s proprietary scoring methodology.
Founders receive a structured report that explains what matters, why it matters, and what to fix first.
The score reflects severity, evidence quality, investor relevance, remediation complexity, and the likelihood that an issue could become a diligence blocker.
The report explains findings and evidence clearly, including which issues are likely to matter most in investor review and which gaps should be remediated first.
The underlying scoring model remains proprietary. We do not expose exact weights, formulas, deductions, internal thresholds, or scanner-specific scoring logic.
We show founders what matters, why it matters, and what to fix first — without exposing sensitive source code or retaining code after analysis.
The report explains findings and evidence clearly. The underlying scoring model remains proprietary.
A strong score does not promise a financing outcome. It indicates how much technical and AI diligence friction is likely to appear before an investor gains conviction.
Evidence is strong, blockers are limited, and the team appears prepared for technical review.
Commercially credible, with targeted diligence issues that should be addressed before serious review deepens.
Important technical, AI, IP, or privacy concerns are likely to slow momentum or trigger follow-up objections.
Multiple weaknesses point to meaningful investor concern and a substantial pre-fundraise remediation burden.
Core security, IP, compliance, or AI safety gaps create a strong likelihood of diligence failure.
ASIRI is built for investor-oriented technical diligence, not a generic AI scanner. The engine looks for the issues most likely to slow, reframe, or block conviction.
Hardcoded API keys, tokens, credentials, unsafe configuration, and dependency risks that signal weak production discipline.
GPL/AGPL dependencies, unclear code ownership, contractor IP gaps, copied code risk, and weak evidence of proprietary ownership.
LLM workflows that can be manipulated through prompts, retrieval content, memory, or external tool use.
Personal data in logs, datasets, prompts, repositories, or pipelines without clear handling controls or compliance evidence.
Unclear training data origin, missing dataset licenses, weak fine-tuning documentation, or inability to reproduce model behavior.
Overbuilt inference chains, missing fallback model strategy, poor observability, and unit economics that may break at scale.
ASIRI maps founder statements to technical and documentary evidence, helping teams identify where investor objections are likely to appear.
ASIRI checks data flows, logs, prompts, sample schemas, and storage patterns to see whether privacy claims are actually supported.
Risk if missing: Privacy and compliance concern.
ASIRI reviews repository history, OSS licenses, and contractor or IP assignment documents to check whether ownership claims are defensible.
Risk if missing: Potential investment blocker.
ASIRI reviews prompt handling, retrieval paths, agent tools, guardrails, and fallback behavior to test whether that claim holds up.
Risk if missing: AI safety and operational risk.
ASIRI reviews architecture, token usage, fallback models, observability, and CI/CD evidence to see whether scale claims are technically credible.
Risk if missing: Scalability and margin risk.
Start with a fast signal, move to a full technical review, or run a deep audit built for investor scrutiny.
Fast initial signal for founders who want to understand whether deeper diligence is urgent.
For founders preparing for investor conversations and needing a practical remediation plan.
For teams preparing for high-stakes fundraising, accelerator review, or strategic investor scrutiny.
Share read-only access or provide a structured overview of your stack, architecture, and AI workflow.
We evaluate security, AI / LLM safety, IP ownership, open-source exposure, PII handling, reviewed GDPR and UAE PDPL risk areas, and the issues most likely to raise investor concern.
Receive an investor readiness score, category breakdowns, issue severity, and a clear remediation view before diligence begins.
ASIRI is designed around controlled access, limited retention, and a confidential review process for sensitive startup materials.
Our security model is designed around documented access control, data handling, and operational safeguards.
Analysis is scoped to confidential review workflows with limited access and no unnecessary exposure of client materials.
Reviews run in isolated processing workflows designed to reduce unnecessary exposure of source materials.
ASIRI evaluates PII exposure and data-handling practices against the privacy and compliance areas investors are likely to ask about.
ASIRI gives founders a clearer view of what technical diligence is likely to surface, what matters most to address first, and how to go into investor conversations with more confidence.
ASIRI organizes findings around the questions investors and technical diligence teams are most likely to raise.
Instead of a generic audit dump, founders get a prioritized view of the issues most likely to affect readiness, credibility, and follow-up diligence.
Use the report to tighten your technical story, address the biggest gaps early, and enter investor conversations with more confidence.
Get a structured view of your AI startup’s security, IP, privacy, architecture, LLM, and operational risks before investors turn them into objections.