Interactive demo
Aira is the governance layer for AI agents. Multi-model consensus, policy enforcement, human approval, and cryptographic proof — in one API call.
Pick a use case and watch the full pipeline — data in, models evaluate, policies check, humans approve, receipt minted. These are examples. The infrastructure works with any agent.
Decision pipelines
AI assistant
Which model decided?
You don't know. There's no record of which model ran, what version, or what it saw.
Was the decision correct?
No second opinion. A single model hallucinating means a wrong decision ships.
Did a human review it?
High-stakes decisions go straight through. No approval gate, no audit.
Can you prove it later?
No cryptographic proof. If a regulator asks, you have logs — maybe. Not evidence.
Multi-model consensus
Fan out to 2–5 models. Score agreement. Flag disagreement. No single point of failure.
Policy engine
Three modes — deterministic rules, AI evaluation, or consensus. Auto-enforce on every decision.
Human-in-the-loop
When policies trigger, approvers review via email or dashboard. Approve or deny with full context.
Cryptographic receipts
Ed25519 signatures + RFC 3161 timestamps. Tamper-proof, independently verifiable proof.
Ask Aira
Natural language interface for your governance data. Query cases, policies, agents — conversationally.
Full audit trail
Every data point, model output, policy evaluation, approval, and receipt — linked and logged.
Your agent calls aira.evaluate() once. Everything else happens automatically.
Aira sits between your agents and your AI providers. It doesn't replace your models — it governs them.
┌─────────────────────────────────────────────────────────┐
│ Your Agent │
│ (lending, claims, KYC, compliance, content mod, ...) │
└───────────────────────┬─────────────────────────────────┘
│ aira.evaluate(details, models)
▼
┌─────────────────────────────────────────────────────────┐
│ Aira Governance Engine │
│ │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ │
│ │ Claude │ │ GPT │ │ Gemini │ ... N models │
│ │ Sonnet 4 │ │ 5.2 │ │ 3.1 Pro │ │
│ └────┬─────┘ └────┬─────┘ └────┬─────┘ │
│ └──────────────┼─────────────┘ │
│ ▼ │
│ ┌───────────────┐ │
│ │ Consensus │ score agreement │
│ └───────┬───────┘ │
│ ▼ │
│ ┌───────────────┐ │
│ │ Policy Engine │ rules / AI / consensus │
│ └───────┬───────┘ │
│ ▼ │
│ ┌───────────────┐ │
│ │Human Approval │ email + dashboard │
│ └───────┬───────┘ │
│ ▼ │
│ ┌───────────────┐ │
│ │ Receipt │ Ed25519 + RFC 3161 │
│ └───────────────┘ │
└─────────────────────────────────────────────────────────┘
│
▼
Decision + Proof returned to agentPython SDK, TypeScript SDK, or raw HTTP. Three lines of code.
Python
from aira import Aira
aira = Aira(api_key="...")
result = aira.evaluate(
details="Loan application...",
models=["claude-sonnet-4",
"gpt-5.2",
"gemini-3.1-pro"],
)
print(result.consensus.decision)
print(result.receipt.signature)TypeScript
import { Aira } from "@airaproof/sdk"
const aira = new Aira({ apiKey: "..." })
const result = await aira.evaluate({
details: "Loan application...",
models: ["claude-sonnet-4",
"gpt-5.2",
"gemini-3.1-pro"],
})
console.log(result.consensus.decision)
console.log(result.receipt.signature)EU AI Act — Article 14
Human oversight for high-risk AI. Aira enforces it with policy-driven approval gates and full audit trails.
Tamper-proof evidence
Cryptographic receipts are independently verifiable. Ed25519 signatures can't be forged. RFC 3161 timestamps can't be backdated.
Model accountability
Every receipt records which models ran, which versions, what they decided, and how they disagreed. Full attribution.
Decision provenance
The complete chain from input data to final decision is hash-linked. If anything was altered, the chain breaks.
AI teams
Ship agents faster. Governance is one SDK call, not months of custom infrastructure.
Compliance teams
Audit any AI decision after the fact. Cryptographic proof, not screenshots.
Regulated industries
Finance, insurance, healthcare, legal — anywhere AI decisions carry real consequences.
Aira
AI governance infrastructure
Softure · Berlin