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We build control planes for autonomous spend.

One pattern: observe, route, verify. AION applies it to covered enterprise AI traffic across the API, gateway and managed-provider surfaces it prices. The ledger is the contract.

The problem with dashboards

Cost dashboards chart waste. They surface it, alert on it, even rank it. None of them controlit. The action gap (between “your bill is high” and “the bill is now lower”) is where every cost initiative dies. AI agents make the gap wider because they spend faster than teams can review.

The pattern: observe, route, verify

AION starts observe-only, builds attribution, applies a cheaper safe option, then verifies the saved dollar before billing. It prices covered AI traffic (API, gateway, managed-provider), routes it to the cheapest safe model, preserves cache economics, compresses safe context and enforces budgets, with an evidence ledger. Browser-side AI tools, personal-account usage and unmanaged endpoints sit outside the control plane and are best-effort via enterprise exports, SSO and network policy.

Control loop

Observe, route, verify

01 / observe

Map usage with attribution

Read the source signal: model calls, gateway traffic, agent traces and cache events. Every AI request is tied to a team, app, project, cost center and replay hash.

02 / route

Route cheaper before billing

AION routes covered traffic to the cheapest safe model, holds warm routes to save cache priming costs, compresses context selectively and enforces budgets before spend lands.

03 / verify

Write ledger receipts

After a policy ships, the verifier replays the next billing cut against the merged state and writes one verified saving event per validated dollar. Notional savings never bill.

The ledger is the contract

One append-only table per customer holds every advisory, every dispute, every verified dollar. Each row carries a replay hash that ties it back to a specific billing slice. If we’re wrong, the math is auditable in your own VPC (Enterprise). If you dispute, the verifier re-replays against the pre-change state and emits a reversal.

What “AI-native” means here

Not LLM-wrapped buttons. Agents and autonomous systems are first-class cost actors. Each control loop must have an attribution model, a routing decision and a verifier. When a route or recommendation regresses, the ledger says so before a customer notices.

Milestones

Roadmap

01
Available

AION Observe

Mirror or proxy covered AI traffic, build attribution, compile cost reporting and replay shadow routing models locally.

02
Available

AION Optimize

Enforce cheapest-safe routing, cache affinity preservation rules, selective context compression and verified savings logging.

03
Planned

Schema Policy

Deploy contract-shaped schema validation, execution rules and real-time query interface schema checkers under one control plane.