Skip to content

Architecture and assurance for enterprise AI · 97 official sources

Decide what to build. Prove it's safe, grounded and affordable.

The independent architecture and assurance layer around your AI stack, for enterprise architects, AI leads and security teams. Every recommendation is rule-based, reproducible and cited to NIST, OWASP and the EU AI Act.

Design your architecture Audit an existing system

No sign-up Results in minutes No tracking cookies

Mapped to the frameworks your auditors use

  • OWASP Top 10 for LLM Apps 2025
  • NIST AI RMF 1.0
  • NIST AI 600-1
  • EU AI Act · Reg. 2024/1689
  • ISO/IEC 42001
  • ISO/IEC 23894
  • MITRE ATLAS
  • GDPR

Start with your question

Four modules, from design to evidence

~3 min

Design

“What should we build, and how?”

Get a reference architecture, pattern choice and controls for your use case.

  • RAG / agent pattern choice
  • Layer-by-layer architecture
  • Residual risk and cost handoff
Rule-based, cited designerOpen
~1 min

Estimate

“What will this cost at production scale, and what could go wrong?”

Project token spend, cache savings and runaway-loop exposure.

  • Token and platform TCO
  • Prompt-cache savings
  • Runaway-loop exposure
LiteLLM pricing, synced dailyOpen
~3 min · 13 questions

Audit

“Are we secure and ready for the EU AI Act?”

Triage against OWASP LLM Top 10, NIST AI RMF, the EU AI Act and ISO/IEC 42001.

  • Traceable posture score
  • Cited findings with fixes
  • Reference architecture
OWASP · NIST · EU AI Act · ISO/IECOpen
~2 min

Analyze

“Is our assistant answering from our data, or making things up?”

Score RAG precision, grounding and hallucination risk.

  • Context precision & recall
  • Hallucination risk
  • Unsupported claims
Ragas / DeepEval metricsOpen

How teams use it

Three journeys, one evidence trail

  • Build an AI system

    1. Describe
    2. Design
    3. Estimate
    4. Audit

    Get a reference architecture for your use case, what it will cost at your volume, and the risks to close before build.

    Start with Design

  • Review an AI system

    1. Describe
    2. Assess
    3. Prioritize
    4. Remediate

    Triage an existing workflow against OWASP, NIST, the EU AI Act and ISO/IEC 42001, and hand engineering a prioritized, cited fix list.

    Run an audit

  • Check answer quality

    1. Paste
    2. Evaluate
    3. Diagnose
    4. Fix

    Test one real question end to end: retrieval precision, grounding, and every claim the context doesn't support.

    Analyze a test case

What this platform is and isn't

What it is

  • Architecture decision support before you build
  • Cost, security and compliance assessment with cited evidence
  • A shared, reproducible basis for architecture and risk reviews

What it isn't

  • A model hosting or AI development platform
  • A runtime monitoring or observability tool
  • Legal advice or a compliance certification

It sits alongside your cloud AI platform, evaluation and observability tools, and works with any of them.

Built for scrutiny

Results you can defend in front of an auditor

Every finding is cited

97 primary sources: EUR-Lex, NIST, OWASP, EDPB and vendor documentation. No blogs, no hearsay.

Transparent by design

Rule-based and reproducible. Every score shows its arithmetic, weights and the findings behind it.

Private by default

No account needed. Inputs aren't stored after your request, and there are no tracking cookies.

Always current

Scheduled jobs sync model pricing daily, threat intelligence weekly and grounding benchmarks every two weeks.

Browse all 97 official references

Make the architecture decision before the build decision.

Describe your use case and get a cited reference architecture, its residual risks and its cost.

Design your architecture

About the author

Tanveer Kumbari is a product manager and technical product owner with 16+ years in regulated life sciences, now building AI solutions for service operations.

Read more
↑↓ navigate↵ openEsc close