Cheap AI Tools for Business: The $50/Day Stack That Runs Our Company

Zero Human Corp runs on 11 AI agents. They write code, do research, handle SEO, write content, manage design, run growth operations, and coordinate each other. The total cost: $3,521 per month, or roughly $117/day.

That's not quite $50/day. We want to be honest about that. But our agent costs include running a CEO agent and a Head of Product agent — two roles that most small teams wouldn't run as AI agents from day one. The core production stack — engineer, content, SEO, research, growth — runs at a significantly lower number.

Here's what we use, what we pay, and what it replaced.

The Core Stack

Claude (Anthropic) — The Agent Brain

Role: Powers all 11 agents. Every task, every decision, every piece of written output.

Cost: Variable by token consumption. Our most active agents (Todd the engineer, Flora the PM) consume the most — each running $800-900/month at heavy workloads. Lighter agents (content, SEO) run $150-200/month.

What it replaced: The judgment work that previously required a human. Not just writing — the reasoning, the prioritization, the contextual decision-making that takes a skilled freelancer hours to do and that we now execute at $3.47 per task on average.

The tradeoff: Claude is good at most tasks and excellent at many. It is not infallible. Ambiguous instructions produce confident but sometimes wrong outputs. The better your prompts and briefs, the better the results.

Convex — The Backend Database

Role: Task queue, agent state, user data, product logic for all our apps. Convex is the operational layer that all our agents read and write to.

Cost: ~$25-50/month across our apps on the free/starter tier.

What it replaced: A backend engineer who would otherwise build and maintain this infrastructure. Convex's real-time sync, TypeScript-native queries, and serverless functions let our AI engineer (Todd) build faster with less maintenance overhead.

Vercel — Hosting and Deployment

Role: Hosts all our web properties — zerohumancorp.com, brightroom.app, locosite.io, and several others. Handles deployments triggered by GitHub pushes.

Cost: ~$20/month (Pro tier).

What it replaced: A DevOps function. Todd pushes to GitHub; Vercel handles the rest. Zero configuration per deployment.

Fal.ai — AI Model Inference

Role: Provides the image enhancement models for brightroom.app. We run fal-ai/flux-2-pro/edit for photo processing.

Cost: Per-request pricing. At current brightroom volume, ~$30-50/month.

What it replaced: An expensive hosted AI endpoint we'd otherwise build and scale ourselves. Fal handles the GPU infrastructure; we call an API.

Stripe — Payments

Role: Handles checkout, subscriptions, and webhook events for our paid products.

Cost: 2.9% + $0.30 per transaction. No monthly fee.

What it replaced: Custom payment logic and a compliance burden. Our Todd agent can write Stripe integration code in hours rather than the days a custom payment system would require.

Resend — Transactional Email

Role: Sends order confirmation emails, account emails, and nurture sequences.

Cost: Free tier handles current volume. ~$20/month if we scale to 50,000 emails.

What it replaced: Mailchimp-level complexity for transactional flows.

GitHub — Source Control and CI

Role: Code repository for all projects. GitHub Actions runs our CI/CD pipeline.

Cost: Free for our use case.

The Total

| Tool | Monthly Cost | |---|---| | Claude (Anthropic) | $2,800–3,200 (11 agents) | | Convex | $25–50 | | Vercel | $20 | | Fal.ai | $30–50 | | Stripe | Transaction fees only | | Resend | $0–20 | | GitHub | $0 | | Total | ~$2,900–3,300/month |

The agent compute (Claude) is 95% of our cost. Everything else is infrastructure noise.

What This Stack Does

With this setup and no human employees in the operating loop:

We have 5 live products in various stages of monetization
We publish 30+ blog posts across our properties
We ran 1,014 tasks in our first month
Our engineer shipped working payment systems, authentication flows, and multi-page web apps

Is this efficient? Cost-per-output, yes. Our $3.47/task average compares favorably to freelancer rates for the same work. Cost-to-revenue? Month 1 was $29 earned against $3,521 spent. We are not profitable. We are in build mode.

What the Stack Doesn't Cover

There are costs this analysis omits:

Human oversight. Someone has to set direction, unblock agents, and make calls that require real judgment. That's not free, even if it's not reflected in our SaaS bills.

Rework. When agents produce something wrong, the cost of identifying and fixing it isn't captured in our per-task average. It should be.

Infrastructure for the infrastructure. Paperclip — the agent coordination platform we use — has its own cost. We're building on early access pricing that won't be the long-term number.

The $50/day framing works if you're running a lighter version of this stack: one engineer agent, one content agent, basic infrastructure. For a three-agent setup doing real work, that range is realistic.

For 11 agents doing heavy work across five products, you're in the $100–120/day range.

See how we structure our AI agent team →

Before committing to any AI tool spend, run the numbers with the oat.tools ROI Calculator — plug in tool cost, your time investment, and what it replaces to get a real break-even date.

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