Cover Image for Amberflo x Twill Present Monetizing AI: A Two-Part Hands-On Workshop on Unified AI Metering, Cost Tracking, and Usage-Based Billing (1 of 2)

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Amberflo x Twill Present Monetizing AI: A Two-Part Hands-On Workshop on Unified AI Metering, Cost Tracking, and Usage-Based Billing (1 of 2)

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About Event

🚀 Twill & Amberflo Present: Monetizing AI
(Two‑Part Workshop Series)

Part 1: Unified AI Interface & Cost Tracking
Part 2: Usage‑Based Billing

AI Monetization requires three (3) layers:

Standardized AI & LLM access layer
Unify usage tracking across every model, provider, and workflow.
Cost attribution and Optimization
Understand unit economics in real time.
Usage-Based Pricing
A flexible usage-based pricing and billing engine that turns AI consumption into revenue.

These aren't separate tools.
They form a single economic control plane for AI.

The companies that win in AI won't just build smarter AI Agents.
They'll build smarter monetization infrastructure around them.

Join Twill (a community of 7,000+ founders, executives, and tech professionals) and Amberflo (AI Monetization & Cost Tracking Platform) for a two-part, hands-on workshop series designed to help you build the economic control plane for AI products—starting from the foundations of unifying AI access and metering, cost tracking, then culminating into usage-based pricing and billing.

Why this series, why now

Modern AI monetization requires more than “tracking tokens.” You need an end-to-end system that connects:

How requests get served (models, providers, fallbacks, latency/cost tradeoffs)
How inference is optimized (unit economics, caching, guardrails, budgets, attribution)
How value becomes revenue (metering, pricing metrics, packaging, billing, and policy)

These aren’t separate projects. Together, they form one economic control plane for AI.

Series breakdown

Part 1 — Unified AI Interface & Cost Tracking

This kickoff session focuses on the practical foundations you need before you can price AI accurately and confidently.

You’ll learn how to:

Enable a unified access and metering layer across models/providers/workflows (without losing visibility)
Implement routing strategies (cost/performance tiers, failover, policy-based selection)
Measure real unit economics (per feature, per customer, per agent, per workflow)
Put guardrails in place: budgets, rate limits, showbacks/chargebacks, and governance
Identify quick wins to reduce spend while improving reliability (the “optimize before you monetize” playbook)

Hands-on focus: bring your laptop. We’ll walk through workflows you can adapt immediately.

Part 2 — Usage‑Based Pricing & Billing

Once unified tracking + optimization are in place, this session turns consumption into a scalable revenue model.

You’ll learn how to:

Choose the right pricing model (tokens, requests, tool calls, tasks, outcomes, agent actions)
Package AI capabilities into usage-based plans that match customer value
Handle the hard parts: multi-model attribution, agent-to-agent usage, internal “sub‑billing”
Design pricing that scales with agentic systems: limits, overages, tiers, commits, and controls
Build a billing engine that works even when “users” are autonomous agents

Outcome: leave with a monetization blueprint you can apply to your AI product—even as agent swarms become the default interaction pattern.

What to expect (both parts)

✅ Frameworks you can use immediately: proven patterns for operating AI in production while keeping costs tied to business outcomes

✅ Responsible scale: governance + control without slowing teams down

✅ Real-world lessons: hear from Amberflo leadership, including Founder & CEO Puneet Gupta (ex‑GM AWS), on building usage-based services and applying those lessons to AI monetization

✅ Live Q&A + discussion: get your questions answered by people building at the edge of AI infrastructure and pricing

Bonus: partner access

In collaboration with AI21 Labs, attendees will receive exclusive access to explore their latest LLM capabilities and enterprise use cases hands-on.

Who should attend

Founders and product leaders building AI-first or agentic products
Engineering, platform, and infra leaders owning LLM reliability + cost
FinOps RevOps billing teams preparing for usage-based pricing
Anyone shipping AI features who needs unit economics clarity fast

Reserve your spot

This is a hands-on kickoff to a two-part series, and space is limited. Register to secure your seat and get ready to build the monetization layer your AI product will depend on.