Assessment · Governance · Assess and know

5Regulatory applicability

Which laws and standards apply to us, and to which systems?

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

Stakeholder interviewsAutomatedUses your existing assessments 3 controls 4 engines

How we collect

  • Stakeholder interviewsIntake: jurisdictions, sector, your role (provider or deployer), data classesRuns today
  • AutomatedEU AI Act classifier and US AI law classifier (California, Illinois, Texas, New York, Colorado, CMMC)Runs today
  • AutomatedData residency and model origin from usage dataRuns today
  • Uses your existing assessmentsPrior legal opinions and compliance assessmentsNeeds your export or setup

Status labels show what runs today, what needs an export or setup from you, and what is planned.

What you get

  • Obligations per system with effective dates
  • Missing intake facts listed as open questions, never assumed
  • Industry layer: HIPAA, legal privilege, financial rules

Questions we ask

  • Where are your users and data?
  • Do you build AI for others or use it yourselves?

We can start from

Legal memos and compliance assessments as evidence files

Data sources

SourceWhat we readStatus
QuestionnaireThe short interview for what data cannot show: purpose, owners, decisions AI informs, regulations in scope.Runs today

Built on governance engine modules

P9 LiveRegulation, Audit & Compliance

Which obligations apply to you, dated and watched?

Assess & Govern
P19 PlannedVertical Governance

What does your industry add on top, HIPAA, legal privilege, finance?

Assess & Govern

AICost governance controls in this module

AICost-GovControl202Partly automated
Regulatory obligations by jurisdiction
What it is

A map of the AI rules that apply by country, state, sector and use case, with dates and the strictest common requirement.

Why it is needed

Rules overlap and change: the EU AI Act timeline moved in 2026, US states keep adding laws, and sector regulators publish their own guidance.

Why enterprises need it

A company selling in several markets needs one program that meets the strictest rule instead of separate projects per country.

What you get:Obligations listed per systemUpcoming dates trackedOne program instead of one per country
Run by
Regulation, Audit and Compliance engineEU AI Act Readiness engineModel Origin Risk engineCompliance Cost engine
Data
Questionnaire
Evidence produced
Obligation map: system, jurisdiction, rule, obligation, effective date, status, owner.
Maps to
EU AI Act; US state AI laws; Sector rules (health, finance, employment)
AICost-GovControl906Wave 3
Sector requirements
What it is

Extra controls for regulated sectors such as healthcare, financial services and employment, mapped to each sector rule.

Why it is needed

Sector rules add duties on top of general AI law, such as clinical oversight or model risk management.

Why enterprises need it

Regulated buyers expect sector-specific evidence, not general claims.

What you get:Sector duties listed per systemEvidence in the regulator termsFaster sector reviews
Run by
Regulation, Audit and Compliance engineCompliance Cost engine
Data
Questionnaire
Evidence produced
Sector map: system, sector rule, duty, control, evidence.
Maps to
HIPAA; SR 11-7 model risk; Employment AI laws
AICost-GovControl904Wave 3
Engaging regulators and standards bodies
What it is

Taking part in consultations and standards work, and keeping a record of positions and changes that affect you.

Why it is needed

Rules are still being written. Early input and early warning reduce rework.

Why enterprises need it

Regulated firms benefit from knowing what is coming and having a voice in it.

What you get:Early warning on new rulesPositions recordedLess rework later
Run by
Regulation, Audit and Compliance engine
Data
Questionnaire
Evidence produced
Engagement log: body, topic, submission, date, outcome, impact.
Maps to
ISO/IEC 42001: context of the organization

Frameworks

EU AI ActCategory and role per system, prohibited uses, high-risk duties, transparency, AI literacy, incident reporting
Sector rulesHealthcare, financial model risk, employment AI laws

Stakeholders

General CounselCompliancePrivacy office
← 4. Risk tiering and risk register All modules 6. Data sensitivity, privacy and residency →
📖 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 →