AI Product and Cloud Cost Playbook

Free tools and diagram-first guides from Axionry for teams building AI products and paying cloud bills. Find your problem on the map above, then open the matching section below. Each one ends in a free calculator or a deep-dive post with the numbers shown.

1. Price an AI product before you build it

Most AI budgets miss the monthly run line: model calls, evals, monitoring and retries. The AI product cost estimator prices setup, features, AI depth and integrations line by line, then shows the run cost per month.

Deep dive with real estimator output: The Build Is the Cheap Part. Want it built with $0 upfront? See AI product development.

2. Find where your cloud bill actually goes

Nine leaks cause most of the waste we see: NAT gateway data, idle environments, oversized instances, egress and forgotten storage. A NAT gateway alone charges $0.045 per GB processed on top of $0.045 an hour, so S3 traffic through it is pure overhead.

Plug your numbers into the cloud cost calculator or walk the AWS cost optimization checklist. The 30-day plan is in Where Your Cloud Bill Actually Goes, and the cloud cost reduction case study shows it on a real bill. Need hands on it? See cloud cost optimization.

3. Ship an AI agent that survives production

The demo is a loop. Production is the same loop plus step caps, idempotent tools, a cost ceiling and a journal you can replay. Those guards belong in code, not in the prompt, because the model will not remember them under load.

The full pattern, with the failures that forced each guard: I Ship AI Agents for a Living. Reference designs: agent loop architecture for production and multi-agent vs single agent.

4. Run voice AI at cents per minute

A custom LiveKit pipeline brought our production voice agent to about 2.5¢ a minute, against roughly 10¢ on a managed platform. The real target is latency: under 800 ms from the moment a caller stops speaking to the first syllable back, and end-of-turn detection is where most of that budget goes.

Price your own call volume in the voice AI cost calculator, read the 2.5¢ a minute case study and the 800 ms latency budget, or see voice AI development.

5. Make AI video at scale

An episode is 100 to 150 shots that must agree on who is tall, who is talking and what happened a minute ago. One showrunner agent, stateless specialists and one tool harness exposed over MCP keep them consistent. A critic that kills bad takes early saves more than any GPU discount.

The architecture and the cost per finished second: Inside an AI TV Episode Factory. Wiring Claude to video tools over MCP: Claude as Showrunner. Hosting and GPU break-even: how to self-host an AI video model. Production service: AI TV series production.

6. Direct an AI series from Claude over MCP

Connect Claude to Higgsfield and Veo through MCP servers and Claude becomes the showrunner: it writes the beats, keeps the character bible, calls the video tools shot by shot and stitches the episode. The harness, not the prompt, enforces budgets and retakes.

Setup, tool list and real per-episode costs: Claude as Showrunner: Build an AI TV Series With Higgsfield and Veo MCP. Want it built for your brand? See AI TV series production or watch the clips.

Work with Axionry

Axionry is a studio that builds AI products, agentic workflows, voice agents and AI video, and cuts cloud bills for the teams that run them. Every figure on this page is a published list price or a measured number, and each linked guide shows its working.

Start with a number: AI product cost estimator · cloud cost calculator · voice AI cost calculator. Then see the services or talk to us. New diagram posts land on the Axionry Substack.

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