Most AI tools give you one model and a prompt. IronArchitects gives you a pipeline: an AI architect that designs, four specialist reviewers that deliberate, live evidence tools that ground every claim, and a remediation loop that fixes gaps before a human ever sees them.
One paragraph of intent becomes a complete solution architecture: components, technology choices, data flows, deployment topology, and all four C4 diagram levels. Generation runs on enterprise AI providers (Google Vertex AI Gemini today, with Anthropic Claude available through per-surface provider routing) and is constrained to your approved technology catalog, your org policies, and the regulations that apply.
After generation, the design goes to a panel of specialist agents: the architect that proposed it, plus an independent security reviewer, cost optimizer, compliance officer, and an adversarial reviewer whose only job is to attack hidden assumptions and failure modes. The four reviewers each critique it on their own terms, they deliberate over the findings, and the worst verdict wins. No rubber stamps.
The agents don't answer from memory. They call live tools: real CVE data from NVD, real cloud prices, your own knowledge base, and your technology catalog. Every recommendation carries its evidence, and every outbound call is allowlisted and sandboxed.
When a design fails a control or needs a capability with no approved technology, the engine doesn't hand you a to-do list. It loops: redesigns, re-evaluates, and closes what it can automatically, within a bounded iteration budget. Only what genuinely needs a human reaches one.
Ask the design why it made a choice and get an answer grounded in the actual documents and controls, not a generic essay. Ask for a change and the engine applies it, re-runs the analysis, and versions the result. Decisions worth keeping become Architecture Decision Records automatically.
The engine is autonomous inside the run, and accountable everywhere else.
Generation runs on Google Vertex AI under terms that prohibit training on Customer Content. Your designs stay yours.
The AI proposes; people approve. Low-confidence decisions are flagged, and no design ships without an accountable human sign-off.
Generation runs, agent verdicts, remediation steps, and chat answers are persisted to a hash-chained, tamper-evident audit trail.
Chat responses are validated for injection; abuse patterns are detected and reported to your admins automatically.
Every outbound call the agents make (CVE, pricing, research) is validated against an allowlist with DNS-rebinding protection.
Logs and chat responses are scrubbed of personal data before storage, with regulated-tier controls over what reaches an LLM provider.
Start free, describe what you want to build, and watch the engine design, review, and remediate it in one run.