ƒ FinOps LLM Schematic · Rev C
FINOPS · LLM FinOps Foundation principles — adapted for tokens

AI cost control for the era of tokens.

FinOps LLM is the AI cost management and LLM observability platform for engineering teams running production GenAI. Real-time attribution across OpenAI, Anthropic, Bedrock, and Gemini · anomaly detection, chargeback, and automated optimization — reconciled monthly against raw provider invoices.

Invoice-first audits 38–68% typical reduction Read-only by default Multi-cloud
FIG. 01 — Request routing schematic · per-request cost
Reconciled against → OpenAIAnthropicGeminiBedrockAzureGroqTogetherMistral
SEC. 01 — Platform

FinOps for AI, on four pillars.

The FinOps Foundation framework — visibility, attribution, optimization, accountability — applied to LLM spend. Same discipline. Different unit of cost.

FIG. 02-APILLAR 01

Visibility

Token-level cost data ingested from every provider. Reconciled hourly. Filterable by provider, model, feature, team, customer, environment.

  • OpenAI · Anthropic · Bedrock · Gemini · Azure · Groq
  • Hourly ingestion · <5 min reconciliation lag
  • Read-only by default · NDA + DPA on request
FIG. 02-BPILLAR 02

Attribution & chargeback

Every token mapped to a feature, team, and customer cohort. Monthly chargeback and showback, exported to your finance system or as CSV.

  • Custom dimensions · feature, team, tier, region
  • Cohort spend · customer-tier P&L
  • NetSuite · QuickBooks · CSV · API
FIG. 02-CPILLAR 03

Anomaly detection

Real-time alerts when spend, latency, or quality deviates from a feature's rolling baseline. Slack, PagerDuty, email — and auto-throttle when it matters.

  • Per-feature rolling baselines · seasonality-aware
  • Slack · PagerDuty · email · webhook
  • Optional auto-throttle & budget enforcement
FIG. 02-DPILLAR 04

Automated optimization

Routing, caching, and compression deployed behind feature flags, A/B tested seven days minimum, graduated only on quality & cost wins.

  • Routing tree · per-request quality classification
  • Semantic cache · sub-10ms hit latency
  • Quality SLO + auto-rollback on regression
SEC. 02 — Optimization

Six levers, one parts list.

Most teams combine three or four. The audit ranks which dominate your spend surface and projects savings before any commitment.

PART №LEVERFUNCTIONRANGE
OPT-01

Model routing

Each request classified by complexity and routed to the cheapest model that meets your quality bar.

30–50%
OPT-02

Semantic caching

Near-duplicate prompts fingerprinted with embeddings; identical answers served from sub-10ms cache.

20–40%
OPT-03

Prompt compression

System prompts audited, examples deduplicated, retrieved context compressed. Every change A/B tested.

15–30%
OPT-04

Batch & async pricing

Non-interactive workloads routed to batch endpoints (up to 50% discount) with SLO-aware queueing.

10–50%
OPT-05

Provider arbitrage

Identical capability often costs 2–3× more at one provider. Route by capability-per-dollar.

20–35%
OPT-06

Fallback chains

Smart retries and tiered fallbacks beat worst-case over-provisioning while holding SLO.

5–15%
SEC. 03 — Engagement

Assembly sequence: five weeks.

Every engagement follows the same four phases. Most customers see their first reconciled provider invoice by the end of week five.

STEP 01 · WEEK 01

Audit — map every dollar.

Ingest provider invoices, gateway logs, usage telemetry. Full spend map by provider, model, feature, team — ranked by dollar waste.

STEP 02 · WEEK 02

Plan — rank by waste.

A prioritized engineering plan respecting compliance, latency SLOs, and release process. You sign off on every change.

STEP 03 · WEEKS 03–05

Ship & A/B.

Optimizations ship behind feature flags, A/B tested 7 days vs. baseline, graduated to 100% traffic. Cockpit goes live alongside.

STEP 04 · ONGOING

Reconcile — compound.

The platform watches for drift; savings compound. Every month closes with a signed Statement of Savings.

SEC. 04 — Pricing

Two ways to pay.

Most teams start on Performance — the audit is free, you only pay on results.

★ MOST POPULAR · PAY ON RESULTS

Performance

Free audit. Then you only pay when we save you money — measured against a locked baseline, reconciled to provider invoices.

15–25%
of verified savings · no savings, no fee
  • Free audit · 1-week turnaround · countersigned baseline
  • Full optimization stack · routing, cache, compression, arbitrage
  • Live cockpit + chargeback + monthly signed statements
  • Engineering pair · weekly reviews
  • Quality SLO enforcement & auto-rollback
  • Minimum: $20K/month LLM spend
Book free audit →
SELF-SERVE

Platform

Cockpit, attribution, and chargeback for teams that want visibility without a managed implementation.

from $1,500/mo
annual or monthly · upgrade any time
  • Real-time spend attribution across all major providers
  • Anomaly detection · Slack & PagerDuty alerts
  • Chargeback & showback exports · NetSuite, CSV, API
  • Budget enforcement & per-team auto-throttle
  • Forecast & what-if scenario modelling
  • Email + chat support · 24h SLA
Talk to sales →
SEC. 05 — Reference

Common questions.

Missing something? Email hello@finopsllm.com — we respond within one business day.

How much can we save? [+]
Typical reduction in the first full billing cycle after implementation is 38–68%, depending on architecture and traffic mix. Real targets are set after a provider-invoice audit and workload review.
Does FinOps LLM support chargeback & showback? [+]
Yes. Token-level attribution to providers, models, features, teams, and customer cohorts. Monthly chargeback and showback exported to NetSuite, QuickBooks, CSV, or API. Custom dimensions supported.
How do you handle customer data? [+]
Read-only by default. Billing and usage data is enough for most attribution work. Prompt and output data is only accessed with explicit approval, for specific optimizations that require it. NDA and DPA available on request.
How long does implementation take? [+]
Attribution and dashboards go live in under a week. Optimization implementation takes 3–5 weeks; savings appear on the first full provider invoice after go-live.
Will optimization hurt output quality? [+]
No. Every routing, caching, and compression change is A/B tested against production for seven days minimum before promotion. Regressions auto-rollback. Quality is monitored continuously alongside cost.
Which providers are supported? [+]
OpenAI, Anthropic, Gemini & Vertex AI, AWS Bedrock, Azure OpenAI, Groq, Together, Mistral, Cohere, Fireworks, Replicate, and most OSS endpoints. Multi-provider deployments typically have the largest savings surface.
SEC. 06 — Start here

Get your AI bill under adult supervision.

Two weeks. Read-only access. We return with a full map of your spend, ranked by waste, plus a baseline our cockpit can track against. Free. No implementation commitment.

30-min discovery · read-only by default · NDA + DPA on request · no commitment