▲ AICost Risk

so you don't pay later for what goes wrong

Quantify what could go wrong — before your board asks

Hallucinations create legal liability. Missed compliance brings regulatory fines. PII leakage triggers breach events. Model drift erodes quality silently. Vendor lock-in makes migration cost multiples of original build. AICost Risk quantifies AI-specific exposure in dollar terms — and maps each risk to the best-fit mitigation from 115,000+ vendor-neutral tools.

Enterprise engagement
Talk to our risk desk → Read risk playbooks →

WHO SHOWS UP HERE

If one of these sounds like you, keep reading

“Board wants an AI risk report by Q3. I have no methodology.”
CISO · Regulated industry
“EU AI Act deadline hits and we're not ready.”
Chief Compliance Officer · Financial services
“We had a hallucination-driven customer complaint. Legal is asking for exposure analysis.”
Chief Legal Officer · B2B SaaS
“PII is leaking through prompts. We don't know the blast radius.”
Head of Security · Healthcare tech

FREE · SELF-SERVE

Start here. No signup. No gate.

Every tool on this page runs live. Use them, share them, come back if you want us to do it for you.

📋
Playbook: Vendor lock-in risk
How to measure your exposure to a single-vendor AI strategy and what the migration cost really looks like.
Read playbook →
📋
Playbook: Price-change resilience
When vendors change pricing silently, what's your downside. Framework for commit structure and hedges.
Read playbook →
🗂️
Vendor-neutral risk tool catalog ↗
Curated directory from 115,000+ AI tools — filtered to compliance, security, observability, evaluation, governance categories.
Browse tools →
🧞
AICost Genie — risk triage
Describe the risk you're worried about — get routed to the right playbook, tool recommendations, and engagement tier.
Ask AICost Genie →

DONE-FOR-YOU

Want a human on it? Pick an engagement.

Productized engagements with clear scope, price, and deliverable. No custom SOW negotiation on the first call.

AI Risk Audit
$35,000 – $75,000
4–6 weeks

Board-ready risk posture assessment. Quantified dollar exposure per risk category. Mitigation roadmap with ranked tool recommendations. Designed to satisfy board and audit committee reporting requirements.

Learn more →
AI Risk Retainer
$10–20K/mo
Ongoing

Continuous risk monitoring. New regulation tracking (EU AI Act, state privacy laws). Quarterly posture reports. Emerging-risk alerts for your specific stack.

Learn more →
Compliance Readiness Sprint
$25,000
3 weeks

Targeted sprint for a specific framework: HIPAA, SOC2, GDPR, EU AI Act. Gap analysis + remediation plan.

Learn more →

DEEP DIVES

Playbooks that go with AICost Risk

Vendor lock-in risk Price-change resilience Hidden TCO of AI Agent loop runaway costs

FAQ

Questions we hear before people book a call

Is this a security product or a consulting service?

Consulting + decision support. We don't do detection (Wiz, Orca, Prisma do that). We quantify your AI-specific risk exposure and recommend best-fit tools from a vendor-neutral catalog of 115,000+.

What risk categories do you cover?

Seven: compliance (HIPAA, GDPR, SOC2, EU AI Act), security (prompt injection, PII leakage, API key exposure), hallucinations and legal liability, model drift, vendor lock-in, operational (agent loop runaway), reputational.

Who commissions these engagements?

Typically CISO, CRO, CLO, or Chief Compliance Officer — sometimes at board direction. VPs of Engineering and CFOs also commission when AI spend crosses material thresholds.

Is this compatible with our existing GRC platform?

Yes. Our deliverables are designed to feed into ServiceNow GRC, Archer, OneTrust, LogicGate, etc. We don't replace your GRC tooling — we feed AI-specific risk data into it.

Why does aicost.ai do risk? Isn't this a security firm's turf?

AI cost and AI risk are two sides of the same coin — every risk event has a dollar impact. We combine pricing intelligence (our crawler), vendor-neutral tool catalog (from toolsinfo.com, 115K+ tools), and partnership with CloudArmee (AWS Advanced Partner with security competency) to deliver what a pure-security firm can't: cost-quantified risk with specific mitigation procurement.

INSTANT ANSWERS

Not sure if AICost Risk is the right fit? Ask.

Describe your situation — we’ll route you to the exact playbook, tool, or engagement that matches.

🧞
AICost Genie — Frameworks · Tools · Playbooks

👋 Tell me what’s going on. I’ll surface the right frameworks, tools, and playbooks — and tell you which product line fits.

Pick the problem closest to yours:

THE OTHER FOUR

Five product lines, one platform

AICost Risk is one of five outcomes. Keep exploring:

◇ AICost Clarity
so you understand why your bill is what it is
 ✦ AICost Optimize
so you pay less — measurably
 ◎ AICost Forecast
so you know what you'll pay — before you ship
 ◢ AICost Leverage
so you negotiate like the Fortune 500 does

Get a board-ready AI risk posture in 4–6 weeks.

For enterprise teams with AI spend over $100K/month in regulated or compliance-sensitive contexts.

Talk to our risk desk → See consulting ladder
📖 Data sources & methodology 161 text models · 9 embeddings · 24 vision · 41 audio · 8 vector DBs across 10 vendor pages · last verified 2026-06-05

Methodology

  • All prices are USD per 1 million tokens, current as of 2026-06-05.
  • 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
2026-06-05
https://www.anthropic.com/pricing
Daily snapshot since Sep 2023 · 578 days captured
Anthropic Docs
2026-06-05
https://platform.claude.com/docs/en/about-claude/pricing
Daily snapshot since Sep 2023 · 578 days captured
OpenAI
2026-06-05
https://openai.com/api/pricing/
Daily snapshot since Sep 2023 · 579 days captured
Google AI
2026-06-05
https://ai.google.dev/gemini-api/docs/pricing
Daily snapshot since Dec 2023 · 554 days captured
Google Vertex
2026-06-05
https://cloud.google.com/vertex-ai/generative-ai/pricing
Daily snapshot since Dec 2023 · 554 days captured
DeepSeek
2026-06-05
https://api-docs.deepseek.com/quick_start/pricing
Daily snapshot since May 2024 · 493 days captured
xAI
2026-06-05
https://x.ai/api
Daily snapshot since Nov 2024 · 411 days captured
Mistral
2026-06-05
https://mistral.ai/pricing
Daily snapshot since Dec 2023 · 552 days captured
Cohere
2026-06-05
https://cohere.com/pricing
Daily snapshot since Sep 2023 · 578 days captured
Voyage AI
2026-06-05
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.
Google — Gemini 2.0 Flash cachedInput Derived at 25% of input per Google 2.0 family caching rates.
Google — Gemini 2.0 Flash batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 2.0 Flash batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
Google — Gemini 2.0 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
Google — Gemini 2.0 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 2.0 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 →