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Observe, price and sign every enterprise AI request.

AION runs inside your boundary, beside the gateway you already use. Every covered agent and employee AI request becomes a per-row-signed, CFO-auditable record: what it cost, the model that answered and the AI Bill of Materials behind it. Then it enforces policy: cheapest-safe routing, data-egress controls and action approval gates. CPU-first, sidecar or air-gapped. A vendor never sees your data.

The Enterprise AI Risk Control Plane

Employees and agents now call Claude, ChatGPT, Gemini, Cursor, Codex, Claude Code, Cline and internal tools with company-paid credits. Most enterprises cannot clearly answer who used AI in covered traffic, what data left the boundary, which model answered, what it cost or whether the agent should have been allowed to act. AION becomes the private register where every covered AI agent, covered model, covered memory scope, covered skill and covered data path is inventoried, signed and answerable to audit. “Covered” means the API/gateway path and managed-provider traffic AION is configured for. Browser-side AI tools, personal-account usage, and unmanaged endpoints are best-effort and called out as blind spots in the register.

AI traffic inventory

Inventory the AI traffic AION observes beside your gateway (across the API, gateway and managed-provider paths) and surface unmanaged usage there. Named honestly: AION sees the traffic that flows through the gateway it sits beside, not usage outside that path. Browser-side usage is covered through enterprise exports and network policy.

  • inventory observed AI traffic across teams, apps and credentials
  • identify unmanaged or personal-account Claude, ChatGPT, Gemini, Cursor, Codex and internal agent calls in the API/gateway path
  • flag traffic to unapproved providers and call out blind spots honestly

AIBOM and signed provenance

AI Bill of Materials for every covered agent: models, providers, data flows, tools, policies. Signed and append-only for the agents AION integrates with.

  • record agent, skill, memory scope, model, provider and data path per request
  • sign provenance and pin it to a verifiable evidence ledger
  • supply auditors a complete, time-stamped record

Verified Savings Ledger

Cost claims that survive audit. Every saved dollar tied to an observed traffic event and a replay-hashed receipt before it reaches an invoice.

  • attribute spend to user, team, app, project and cost center
  • compare baseline to enforced policy on the same traffic
  • write savings_verified events; notional savings never bill

Enforcement

A reviewed kill switch and policy controls halt or redirect risky AI traffic. Enforcement runs on the governance classifiers; the ledger and AIBOM stay intact for forensics throughout.

  • pause or redirect a covered model, provider, agent or skill
  • gate risky calls behind review before they execute
  • every enforced decision lands in the signed ledger

Cost-optimized for enterprise deployment

AION is cheap to run inside the customer boundary. The router and governance classifiers (egress, data category, prompt risk, action risk, runaway-loop detection) run CPU-first on ONNX Runtime. GPU is reserved for training, batch jobs, frontier-model fallbacks or optional high-throughput deployments; never a default requirement for governance. Strict mode runs with no outbound Infivector network dependency.

Sidecar

Deploy beside a single workload, in-boundary, for low-latency local inference and minimal blast radius. Bring your own gateway: AION observes the traffic that already flows through it, signs the evidence and enforces policy. Single-writer, local storage, no client-server DB.

  • observe, price, sign and enforce in-boundary
  • CPU-first classifiers for the routing/cost evidence
  • records append-only files + an embedded coordination KV
  • no Infivector network dependency in strict mode

Strict mode (overlay)

An air-gapped overlay on the sidecar: no outbound calls to Infivector services. Policy bundles, classifier weights and updates ship as offline artifacts. The in-boundary, customer-key-held, no-phone-home posture for regulated finance, healthcare and gov.

  • zero outbound vendor dependency
  • customer holds the keys; a vendor never sees the data
  • offline-staged updates and policy bundles
  • same footprint as the sidecar plus offline ops overhead

Bring your own gateway

AION rides the gateway you already run rather than replacing it. Acting as the customer's traffic gateway competes with commoditized OSS gateways and pulls AION off its defensible axis (the signed ledger). The sidecar covers the in-boundary case; a shared gateway is added only against a real requirement the sidecar cannot meet.

  • the in-boundary sidecar + strict-mode are the core shapes
  • bring-your-own-gateway is the default posture
  • AION enforces on the gateway you already run
  • an Infivector-hosted control plane stays out of scope

Four runtime controls

AION sits beside the gateway on the API/gateway/managed-provider path. It observes covered traffic, attributes it, signs the evidence, then enforces policy: each covered model call or tool action runs through a single classified decision before it executes. Browser-side AI tools, personal-account usage and unmanaged endpoints sit outside this path.

Cost control

The AION router sends covered AI traffic to the cheapest safe model, with budget, token, cache, team, app and cost-center context gating model selection. Every routing decision and its cost land in the signed ledger.

  • route routine work to the cheapest safe model
  • escalate high-risk work to stronger models
  • stop retry loops and runaway token spend

Data control

The data-category classifier checks whether prompt data can leave the customer boundary before forwarding, applying zero-retention and approved-provider policy. AION stores no raw prompt or response, only keyed-HMAC evidence anchors.

  • keep secrets, credentials and sensitive records local-only
  • apply approved provider and zero-retention policy
  • redact or block unsafe data movement

Action control

The action-risk classifier evaluates agent tool calls as actions, not just prompts, so risky operations pause for approval before execution. Every action is recorded as signed evidence.

  • allow low-risk read-only work
  • require approval for production and finance actions
  • block destructive commands and unsafe tool requests

Model control

The AION routing engine combines request intent, route confidence, risk, policy and budget signals into a single auditable route decision, recorded with its baseline id as signed evidence.

  • choose cheaper, stronger, local or fallback routes
  • preserve route affinity when cache and policy allow
  • record why each route changed

Agent governance harness

AION wraps each integrated agent in a governed harness covering memory, skills, tools, approvals, budgets, and audit. New memory and self-evolved skills move through policy before becoming trusted runtime behavior. Agents that are not integrated with the harness, for example free-tier browser AI usage or personal-account agents, sit outside this control surface entirely.

Memory governance

Agents can only read, write or promote memory inside approved user, team, project, customer or app scopes.

  • label sensitive memory before reuse
  • apply retention and redaction policy
  • audit which memory influenced an action

Skill registry

Every agent skill has an owner, version, status, permission set, data boundary and approval rule.

  • allow approved read-only skills
  • review proposed self-evolved skills
  • block deprecated or risky skill versions

Tool execution

AION treats tool calls as governed actions, not invisible side effects after a prompt.

  • scope tools by team and environment
  • pause production or finance actions
  • record skill and tool outcomes in the ledger

CloudScout Skill Pack inside the harness

CloudScout is also the first concrete governed skill pack inside the AION harness. CloudScout finds cloud waste on its own; AION wraps inspect / explain / remediate / approve flows around that skill pack so production remediation runs through the action-risk approval gate.

Governed cloud-spend skills

  • inspect AWS cost anomalies
  • explain Bedrock or GPU spend spikes
  • find idle or oversized infrastructure
  • propose IaC remediation PRs
  • verify cloud and AI savings in one ledger

Default posture is read-only investigation and scoped cloud-account access. Production remediation runs through the AION harness with an approval gate; one verified savings ledger covers cloud and AI spend.

Scoped enterprise AI control

AION sits beside the gateway in front of production apps, internal agents and employee AI tools that route through managed providers or custom base URLs. It observes that traffic, attributes it, signs the evidence and enforces budget, approved-provider, work-purpose and sensitive-data policy. Browser-side AI tools, personal-account usage and unmanaged endpoints sit outside this path (covered via enterprise exports, SSO, network policy).

Runtime action control

Routing is only one decision. Within covered traffic, agents also read files, call tools, query databases, write tickets, send emails and touch production systems. AION separates each request into a classified action before customer policy is applied, and records every action as signed evidence. Actions that bypass AION (unmanaged browser tools, personal-account agents) sit outside this path.

The four decision categories AION applies:

Custom routing model

The AION router decision combines prompt intent, route confidence, data sensitivity, action risk, provider policy and budget state into one auditable choice for each request. The model detail stays private; the decision metadata stays auditable.

Sidecar: bring your own gateway

AION deploys as an in-boundary sidecar beside a single workload, with an air-gapped strict-mode overlay. API-based apps and coding agents are the first-class path; browser AI tools are covered through enterprise exports, SSO controls, extensions or network policy where available.

Start in observe, expand to control

Adoption starts in observe mode on the API/gateway/managed-provider traffic routed through AION. The rollout pattern begins with one low-risk team, then turns on model, data and action controls across additional covered surfaces.

Start here

AION Observe

Mirror or proxy covered AI traffic, build attribution and cost reporting, then replay cost-routing scenarios using the AION router baseline.

  • traffic attribution
  • cost attribution
  • shadow cost-route simulation
  • redaction
  • full evidence ledger

Govern usage

AION Control

Turn on virtual keys, budgets, provider allowlists, data-egress rules and approval queues for selected teams or apps.

  • virtual keys
  • budgets
  • data-egress policy
  • approval workflow

Custom routing + savings ledger

AION Optimize

The AION routing engine drives cost-routing, fallbacks, route replay, cache-aware affinity and a customer-tunable governance policy. The verified savings ledger writes one event per validated dollar.

  • custom routing model
  • route replay
  • fallbacks
  • verified savings ledger

Design preview · self-host or hybrid

AION Enterprise

Deploy sidecars or a central gateway inside the customer environment with private policy, SSO/RBAC and dedicated rollout support, alongside AION Control.

  • sidecar/gateway
  • private deployment
  • SSO/RBAC
  • custom policies

30-day AI Agent Risk & Cost Audit

The first pilot does not need to change production behavior. AION observes covered traffic, builds traffic and spend attribution by team and workflow, and replays traffic through cost-routing scenarios. Pilot deliverables include sensitive-data movement reports, risky-agent-action reports, the evidence ledger and enforcement-policy replay.

Pilot deliverables

  • traffic attribution and reporting table by team, app, project, provider and model
  • spend and cost-routing simulation from observed AI traffic
  • work-purpose and non-work category report
  • sensitive data egress and redaction report
  • risky tool-action and approval queue report
  • memory and skill-governance rollout map
  • CloudScout cloud-spend skill-pack fit review
  • token-loop and runaway-spend candidates
  • enforce-mode rollout plan for one team

CloudScout governs cloud infrastructure spend. AION governs covered AI traffic (routing, agent, memory, skill and AI usage spend) and signs it into one evidence ledger. Infivector customers run cloud and AI spend on the same control plane.

Pilot access

Pilots open one cohort at a time. Joining the waitlist puts you on the next-cohort list.