Flowcost
flowcost.aiA visual planning tool for AI workflows. Teams map agents, tools, and data, compare model and infrastructure choices, and estimate cost and response time before building.
The problem
An AI prototype can show that an interaction works. It does not show what the full workflow may cost at expected traffic. Model choices, prompts, and retrieval all affect the estimate. A spreadsheet can fall out of step when the design changes. We built Flowcost to keep the estimate with the workflow.
What we built
A canvas for the whole workflow
Map agents, model calls, tools, and retrieval on a canvas. Attach the databases, compute, and storage they depend on. The estimate uses the workflow you define.
Usage assumptions you can change
Set your expected monthly users and split them into groups with different usage levels. Flowcost uses those assumptions to estimate demand across the workflow.
Compare model and infrastructure choices
Save variations of your workflow to compare models and infrastructure. See how each choice affects estimated monthly costs and response times under your usage assumptions.
A plan you can share and export
Share a scenario for review or export a structured brief for a coding agent. The export carries the workflow, model choices, infrastructure, and usage assumptions.
How it works
Estimates based on explicit assumptions
The same graph, prices, and usage assumptions produce the same totals. The engine calculates costs for each step and adds them to the monthly estimate. It flags missing prices and unsupported cost items alongside the known subtotal. Response times come from model profiles and workflow assumptions. They are estimates, not measurements from a load test.
Let’s talk about your project.
Tell us what you want to build or improve. Someone from our team will read your message and reply by email.