nuxt-appのLPで使われているフォントは？

Hanken Grotesk / IBM Plex Mono / Palette Mosaic

nuxt-appのLPの主要カラーは？

背景 #f4f3eb / テキスト #030303 / アクセント #030303

nuxt-appのLPのh1見出しのスペックは？

Hanken Grotesk / 100px / weight 900 / line 90px / tracking -6px

nuxt-appのLPのセクション余白は？

主要セクション上下余白 280px / 900px / 900px

Polar のWebデザイン | ASI Design Gallery

A billing platform for the intelligence era

Introducing the Polar Startup Program Features Docs Pricing Blog Company Sign in Get Started Turn Usage Into Revenue A billing platform for the intelligence era Get Started Why Polar Speakeasy Logo Speakeasy Logo 01 — Ingest Ingest usage & inference on behalf of your users. 02 — Aggregate Transform raw signals into aggregated units. 03 — Charge Generate charges & collect payments automatically. Watch your revenue happen Orders, subscriptions, and customers the moment they land. Made for teams moving as fast as the models. Any pricing model. Ships in an afternoon. Usage Billing Meter tokens, API calls, compute, storage. Bill with precision down to the event. Subscriptions Recurring plans with trials, upgrades, proration, and dunning built in. Seats Pricing that scales with your customer's teams. Add, remove, prorate automatically. Credits Prepay and draw down over time, like a wallet for your API. Trials Free or paid trials with automatic conversion, reminders, and grace periods. Discounts Coupons, promo codes, and volume tiers. Applied automatically at checkout. Event-based usage billing. Checkouts that convert. Realtime metrics. Worldwide tax handled. Polar is the financial layer for a new generation of intelligent software. Built for the shape of AI. From token-metered APIs to autonomous agents and GPU workloads. Polar fits how modern AI products actually charge. completions.ts agents.ts gpu.ts AI completions Wrap any model from the Vercel AI SDK with the Polar LLMStrategy. Token usage is metered and billed automatically on every call. Read the docs import { Ingestion } from '@polar-sh/ingestion' import { LLMStrategy } from '@polar-sh/ingestion/strategies/LLM' import { generateText } from 'ai' import { openai } from '@ai-sdk/openai' const llm = Ingestion({ accessToken: process.env.POLAR_ACCESS_TOKEN }) .strategy(new LLMStrategy(openai('gpt-4o'))) .ingest('openai-usage') const { text } = await generateText({ model: llm.client({ customerId: