New·Argos now detects usage deviation across 100+ model endpoints See how →
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Argos — your AI bill is the fastest growing line nobody can explain.

Cloud solved this a decade ago and called it FinOps. AI is harder: costs are per token, prices move monthly, one prompt edit doubles spend overnight, and a data science sandbox can route PHI to a model nobody approved. Argos sits at the gateway and answers three questions, continuously.

What is it costing?

Every call metered and attributed to a project, use case and outcome. Month-end forecast updated hourly. Showback to cost centres in the format Finance already uses for cloud.

Is it what we approved?

Live usage compared to each project's approved model card and data classification. Wrong model, region, data class or volume raises a ticket with evidence. Hard policy violations are blocked outright.

Is it worth it?

Cost per approved determination, per closed care gap, per resolved call. Routing to the cheapest model that still passes evals, with quality parity proven before the switch.

The console

One screen for Finance, platform and governance.

argos.8thelement.internal / portfolio
Live · Sept MTD
AI spend MTD$0forecast $214k of $230k
Cost per outcome$0↓ 18% QoQ
Open deviations01 hard block · 2 review
Routing savings0vs single model baseline
burn anomaly · 02:14 Tue · alerted
ProjectSpend / budgetSignalModel policyStatus
Prior auth assist · UM$41.2k / $48k86% of budgetpinned · approvedon track
Clinical policy reader$27.9k / $30k+38% wk/wkroutedreview
Member service copilot$63.4k / $60kover by $3.4kroutedrouting fix
Spend categoriser$8.1k / $20k41% of budgetroutedon track
Data science sandbox$19.7k / $5kPHI → unapproved endpointblockedhard block #412

Illustrative data. Deploys in-VPC behind your existing gateway; prompt content is never stored, metadata only.

Capabilities

Nine things Argos does from day one.

Token metering & attribution

Every call attributed to project, use case, team, model and outcome. Metadata only.

Budgets & burn alerts

Soft alerts before hard caps. Anomaly detection on burn rate, not just totals.

Usage deviation detection

Wrong model, region, data class or volume raises a ticket with evidence. Hard blocks on violations.

Model routing

Cheapest model that meets the quality bar, proven by evals. Regulated cases pin approved models.

Cost per outcome

Joins spend with outcome attribution so sponsors see cost per determination, not per token.

Showback & chargeback

Monthly allocation to cost centres in the format your FinOps team already uses.

Vendor price tracking

Provider price changes applied automatically; forecast impact visible the same day.

Drift linkage

Cost changes correlated with quality, so a cheaper route that degrades accuracy is caught.

Governance reporting

Spend, deviations, blocks and remediation time feed the quarterly board pack.

Let's talk

Tell us the number you need to move.

A 45-minute working session with an operator who has run the kind of work you are describing. You will get an honest read on where your programme stands and what it would take to move it.