TensorCost TensorCost
Solutions

Same story. Different job.

CFO, Platform / SRE, Product / ML, Finance Ops. Each team gets its own version of see, gate and prove. Every tile below maps to a shipped module.

For CFOs: see the bill, gate the backlog, prove the saving

One number finance will defend. No spreadsheets. No waiting for the monthly invoice.

See · bill match across every provider

OpenAI, Anthropic, Bedrock, Azure and Vertex, reconciled daily against the invoice. One number: what you expected vs. what arrived.

Gate · backlog sorted by ROI

Open savings opportunities ranked by expected quarterly impact. Accept one, and the ledger entry appears within seconds.

Prove · net savings YTD, verified not estimated

The savings figure comes from a tamper-evident record. Every line links back to the recommendation that produced it. The ledger can read negative.

Source freshness banners

When an upstream provider API is degraded, a per-source banner surfaces the staleness. The rest of the dashboard keeps running.

See · Gate · Prove, for the people who own the number

What finance actually opens

Training
Inference
Fine-tune
Dev
Idle

See

Spend, sliced any way

Every dollar by team, feature and customer, so you can see which products actually drive the AI bill.

0%
recoverable

Gate

Where a cheaper model holds up

Patterns ranked by daily cost. Fix the biggest line first, without putting quality on someone's neck.

Prove

Have we paid for ourselves?

Year-to-date verified savings against the cost of running TensorCost. Freshness per source so one slow API never hides the rest.

For Platform / SRE: see the fleet, gate the policy, prove the intervention

If you also own the cards: utilization, hardware health, spot eligibility, agent health. NVIDIA on AWS live; GCP, Azure, and on-prem under validation.

See · per-node hardware telemetry

Utilization, memory pressure, temperature and power draw, per GPU, per node, per customer environment. Customer data is fully isolated.

See · partition health

A fleet-wide hardware summary: how many slices are active, which are idle, and which workloads own them.

Gate · enforcement policies

Define policies that fire automatically: moving idle nodes to spot pricing, model-tier limits, spend-cap cutoffs. Results land in the audit log.

Prove · fleet TCO and buy-vs-rent

Hardware purchase costs spread over useful life, plus power, cooling, and networking, combined with cloud variable cost. Compare buy-vs-rent for every workload type.

For Product / ML: see the call, gate the swap, prove quality held

Stamp the request. Shadow the cheaper path. Arm only after it holds. Owned GPUs join the same ledger when you need them.

See · per-workload spend

Training vs. inference breakdown, workload classification, cost attributed by user, feature, and model. On owned GPUs, sourced from per-GPU NVML sampling, phase-labelled so a checkpoint isn't mistaken for idle.

See · traces and routing decisions

Every call carries which model handled it, tagged with team, feature and end customer at the call site. Explicit, not inferred. Live routing ships default-off per policy and can't arm without shadow proof on your own traffic; it fails open.

Gate · quality validation

Every candidate is judged twice with the answers swapped so position bias cancels, and a safety regression in either pass fails it outright. Shadow mode shows the outcome before any policy is armed.

Prove · guardrails and interventions

Per-run budgets checked at the proxy before the provider is called. On owned GPUs, runaway-job catch flags a workflow at five times its own 14-day baseline; intervention events confirm the guard did its job.

For Finance Ops: see the invoice, gate allocation, prove chargeback

One workflow for invoice match, team allocation, monthly chargeback, and board reporting.

See · provider bill tie-out

Every day we compare what we measured against each provider's own reported usage and flag any drift outside tolerance, so a provider pricing change shows up the day it lands rather than on the invoice. Savings figures are a separate before-and-after measurement, not reconciled to an invoice.

Gate · allocation rules

Map AI cost line items to internal cost centers by tag, account, service, or resource. Rules are versioned; history is preserved for audit.

Prove · monthly chargeback

Run chargeback against your allocation rules in one click. Output is a per-team cost breakdown your finance team can import directly. Full run history.

Gate · team budgets

Per-team spend caps with configurable alert thresholds (50 / 80 / 100%). Alerts fire before the cap is hit. Budget history tracked per environment.

Which surface do you start with?

Most written replays begin with CFO and reconciliation. Connect your sources; two weeks to a written report. Read-only the whole way: no production access, no code changes. First snapshot in 48 hours.