AssessmentGovernance

AICost AI Assessment

AI assessment in 20 modules, collected for you

Automated collection plus stakeholder interviews, scored workflow by workflow. Pick a module to see what we collect and what you get.

1Automated collection and reports

Read-only connections to Microsoft Entra and Graph and to AWS cost data, plus bill, licence and gateway exports, collect the facts and build the reports.

2Stakeholder interviews

We consult the people who own the work for what data cannot show: purpose, decisions, risk appetite. Their decisions are recorded with name and date.

3Workflows, priced and governed

126 cost and governance engines price every workflow step and keep it inside the governance envelope.

4Executable policy

Cost and governance rules compiled into policy your own gateway and cloud enforce. Approved decisions become the rules the checks run against.

5Continuous governance

Watchers and an evidence journal check cost, vendors, models and policy on a schedule, so drift and new AI show up before the bill or the audit.

Already assessed or governed? We start from what you have. Today that means your registers, assessments and audits as spreadsheet or CSV files. Direct imports from ServiceNow, OneTrust and Credo AI are planned. AICost adds cost control and executable policy across every workflow.

Assess and know

1AI inventory and shadow AI

Every AI app, agent, model, key and AI feature in use, with the spend behind it.

You getInventory: app, vendor, how found, users, spend, data class, owner P1P15 AutomatedStakeholder interviews · 3/5 runs today · 2 controls 2Workflow map and owners

Each AI system mapped to the business workflow it serves, its steps and a named owner.

You getWorkflow register: steps, systems, models, owner, data class P10P3 AutomatedStakeholder interviewsUses your existing assessments · 2/4 runs today · 3 controls 3Use-case value and priorities

Which AI workflows are worth funding, scaling or stopping, ranked by value and risk.

You getUse-case register ranked by value, cost and risk P3P16 Stakeholder interviewsAutomatedUses your existing assessments · 3/4 runs today · 2 controls 4Risk tiering and risk register

Every AI system gets a risk tier and sits in one register mapped across frameworks.

You getRisk tier per system with the reasons P9P19 AutomatedStakeholder interviewsUses your existing assessments · 2/4 runs today · 2 controls 5Regulatory applicability

Which rules apply to each AI system by country, sector, role and use, with effective dates.

You getObligations per system with effective dates P9P19 Stakeholder interviewsAutomatedUses your existing assessments · 3/4 runs today · 3 controls 6Data sensitivity, privacy and residency

What data each AI system can reach, where it is processed and on what terms.

You getCopilot readiness: overshared sites and content P14P5P8 AutomatedStakeholder interviews · 4/4 runs today · 4 controls 7Identity, access and agent permissions

Who and what can call AI, and what every agent is allowed to read, write or approve.

You getShared identities behind several agents P7P2 AutomatedStakeholder interviews · 3/3 runs today · 3 controls 8MCP servers, tools and AI supply chain

Every MCP server, plugin, model source and library an AI system depends on.

You getDependency map per workflow P4P2 AutomatedStakeholder interviews · 2/4 runs today · 2 controls 9Vendor and model due diligence

AI vendors and models checked for terms, concentration, price and fit before and after you buy.

You getVendor scorecard: training use, retention, regions, subprocessors, price P14P11 AutomatedStakeholder interviews · 3/3 runs today · 3 controls

Test and control

10Answer quality and grounding

Answers checked for made-up facts and kept to the data you give the model.

You getPass or fail per consequence class, never one universal percentage P12 Stakeholder interviewsAutomatedUses your existing assessments · 2/4 runs today · 2 controls 11Security and red teaming

Prompt injection, data leakage, jailbreaks and excessive agency tested and screened.

You getInjection and leakage paths with fixes P2 AutomatedStakeholder interviewsUses your existing assessments · 2/4 runs today · 1 control 12Fairness, explainability and human oversight

Reviews that catch real errors, bias tests where decisions affect people, and decisions you can explain.

You getReview coverage and catch rate P12P19 AutomatedStakeholder interviewsUses your existing assessments · 1/3 runs today · 2 controls 13Agent safety and runaway control

Loops, retries and long agent runs capped before they cost money or cause damage.

You getWorst-case and runaway cost per agent P4P6 AutomatedStakeholder interviews · 3/3 runs today · 2 controls

Cost within the governance envelope

14Workflow cost and TCO

Every step of every workflow priced: models, retrieval, tools, review, compliance and run cost.

You getCost per step and per outcome for every workflow P6P13 AutomatedStakeholder interviews · 3/4 runs today · 2 controls 15Cost levers and model routing

Caching, routing, batching and compaction applied where they are safe for the data and the task.

You getSavings per lever and per step P6P11 AutomatedStakeholder interviews · 2/2 runs today · 1 control 16Budgets, caps and spend guardrails

Monthly budgets, daily limits and per-run caps set where AI traffic flows.

You getBudget, quota, rate limit and circuit breaker told apart P6 AutomatedStakeholder interviews · 2/2 runs today · 2 controls 17ROI and unit economics

Value and cost per resolved case, document or task, and seats that are actually used.

You getHard dollars, hours, outcomes and risk reduced, reported separately P3P16P15 AutomatedStakeholder interviews · 2/3 runs today · 2 controls

Run continuously

18Executable policy

Cost and governance rules compiled into policy your own gateway or cloud enforces. AICost stays out of the request path unless you choose the enforcing proxy.

You getGap between written policy and enforced policy P6P14 AutomatedStakeholder interviewsUses your existing assessments · 1/3 runs today · 3 controls 19Continuous monitoring and incidents

Cost, quality, drift and policy checked every day, with incidents handled to closure.

You getDaily report: what changed, spend, exceptions, new AI P18P6 AutomatedStakeholder interviews · 2/3 runs today · 3 controls 20Evidence, audit and executive reporting

A tamper-evident evidence journal, audit packs and board reporting from the same data.

You getOne-page report: found, means, recommend, unknown, decisions needed P9P20 AutomatedStakeholder interviewsUses your existing assessments · 2/3 runs today · 7 controls
Your systems in, one view out: identity, AI providers, cloud AI platforms, cloud bills, gateways, FinOps and GRC tools flow into AICost, which produces a daily report, an enterprise dashboard, compiled policy and an evidence journal.Open full size

How the assessment runs

Connect

Read-only Microsoft app, bill exports, gateway and vendor API access.

Interview

Short sessions with owners across the enterprise.

Import

Your existing registers and assessments, if you have them.

Score

Engines price every workflow and score every module.

Report

Findings, spend and fixes, with control numbers and owners.

Start your AI assessment

Tell us your identity provider, your AI vendors and your regulators. We send the read-only setup steps and the questionnaire, and walk you through the results.

Book an assessment call Price and govern a workflow Full guide →

Governance → · 20 modules · 43 controls · 126 engines

📖 Data sources & methodology 172 text models · 9 embeddings · 44 vision · 62 audio · 8 vector DBs across 10 vendor pages · last verified 2026-10-18

Methodology

  • All prices are USD per 1 million tokens, current as of 2026-10-18.
  • Vendor-published values have no mark. Inferred/extrapolated values are marked with * and listed below.
  • Batch API discounts are 50% off standard rates across providers that offer Batch mode.
  • Prompt caching discounts vary by provider (typically 80-90% off cached input tokens).
  • Regional data-residency surcharges (Anthropic 1.1x, OpenAI 1.1x, Google regional tiers) are NOT included in base rates.
  • Long-context pricing tiers apply when input exceeds model threshold.
  • Embedding prices are input-only (no output tokens generated).

Primary sources

Last-verified date is the most recent successful daily snapshot (aicost_pricing_snapshots) or, when no snapshot exists yet, the latest successful crawler run (aicost_crawler_runs). 10 of 10 vendors are currently verified. Aggregator services (TokenCost, AI Pricing Guru, etc.) are not listed.

Anthropic
2026-10-18
https://www.anthropic.com/pricing
Daily snapshot since Sep 2023 · 704 days captured
Anthropic Docs
2026-10-18
https://platform.claude.com/docs/en/about-claude/pricing
Daily snapshot since Sep 2023 · 704 days captured
OpenAI
2026-10-18
https://openai.com/api/pricing/
Daily snapshot since Sep 2023 · 705 days captured
Google AI
2026-10-18
https://ai.google.dev/gemini-api/docs/pricing
Daily snapshot since Dec 2023 · 680 days captured
Google Vertex
2026-10-18
https://cloud.google.com/vertex-ai/generative-ai/pricing
Daily snapshot since Dec 2023 · 680 days captured
DeepSeek
2026-10-18
https://api-docs.deepseek.com/quick_start/pricing
Daily snapshot since May 2024 · 619 days captured
xAI
2026-10-18
https://x.ai/api
Daily snapshot since Nov 2024 · 537 days captured
Mistral
2026-10-18
https://mistral.ai/pricing
Daily snapshot since Dec 2023 · 678 days captured
Cohere
2026-10-18
https://cohere.com/pricing
Daily snapshot since Sep 2023 · 704 days captured
Voyage AI
2026-10-18
https://docs.voyageai.com/docs/pricing

Inferred values (marked with * in calculator tables)

Derived from industry conventions, not directly published by the vendor. Typical conventions: cached input = 10% of base (90% off), Batch API = 50% of base (50% off).

Vendor / Model Field Why it’s inferred
Anthropic — Claude Sonnet 4.6 cachedInput Derived at 10% of input rate — Anthropic publishes 90% cache-hit discount on this tier.
Anthropic — Claude Sonnet 4.5 cachedInput Derived at 10% of input rate; same 90% cache-hit convention as Sonnet 4.6.
Anthropic — Claude Sonnet 4.5 batchInput Derived at 50% of standard input — Anthropic documents uniform 50% Batch discount.
Anthropic — Claude Sonnet 4.5 batchOutput Derived at 50% of standard output — Anthropic documents uniform 50% Batch discount.
Anthropic — Claude Haiku 4.5 cachedInput Derived at 10% of input rate — Anthropic 90% cache-hit discount convention.
OpenAI — GPT-5.4 Mini cachedInput Derived at 10% of input — OpenAI documents automatic 90% discount on cache hits across GPT-5.x tier.
OpenAI — GPT-5.4 Nano cachedInput Derived at 10% of input — OpenAI 90% cache-hit convention.
OpenAI — GPT-5.4 Nano batchInput Derived at 50% of input — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.4 Nano batchOutput Derived at 50% of output — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.4 Pro cachedInput Derived at 10% of input — OpenAI 90% cache-hit convention.
OpenAI — GPT-5.4 Pro batchInput Derived at 50% of input — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.4 Pro batchOutput Derived at 50% of output — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.2 cachedInput Derived at 10% of input; no residency uplift.
OpenAI — GPT-5.2 batchInput Derived at 50% of input.
OpenAI — GPT-5.2 batchOutput Derived at 50% of output.
OpenAI — GPT-5 cachedInput Derived at 10% of input.
OpenAI — GPT-5 batchInput Derived at 50% of input.
OpenAI — GPT-5 batchOutput Derived at 50% of output.
OpenAI — GPT-5.5 Pro cachedInput Derived at 10% of input — OpenAI does not publish a cached rate for *-pro models; using the family convention.
OpenAI — GPT-5.5 Pro batchInput Derived at 50% of input.
OpenAI — GPT-5.5 Pro batchOutput Derived at 50% of output.
OpenAI — GPT-5.2 Pro cachedInput Derived at 10% of input — pro-tier convention.
OpenAI — GPT-5.2 Pro batchInput Derived at 50% of input.
OpenAI — GPT-5.2 Pro batchOutput Derived at 50% of output.
OpenAI — GPT-5.1 batchInput Derived at 50% of input.
OpenAI — GPT-5.1 batchOutput Derived at 50% of output.
OpenAI — GPT-5 Pro batchInput Derived at 50% of input.
OpenAI — GPT-5 Pro batchOutput Derived at 50% of output.
OpenAI — GPT-5 Nano cachedInput Derived at 10% of input.
OpenAI — GPT-5 Nano batchInput Derived at 50% of input.
OpenAI — GPT-5 Nano batchOutput Derived at 50% of output.
Google — Gemini 3 Flash cachedInput Derived at 10% of input — Google caching discount convention ~90%.
Google — Gemini 3.1 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
Google — Gemini 3.1 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 3.1 Flash-Lite batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
Google — Gemini 2.5 Pro cachedInput Derived at 10% of input.
Google — Gemini 2.5 Flash cachedInput Derived at 10% of input.
Google — Gemini 2.5 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
Google — Gemini 2.5 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 2.5 Flash-Lite batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
xAI — Grok 4 (legacy) cachedInput Extrapolated at 25% of base.

Pricing is cross-verified against the LiteLLM community registry when available. Daily snapshots are kept in aicost_pricing_snapshots; every change is logged to aicost_price_changelog with old & new values for full audit trail. Read the full methodology →