Buy tokens once. Keep every AI demo running.
MoonRouter gives builders, workshops, hackathons, and small AI teams one token wallet and gateway for model calls, budget control, and fast experiments.
Keep fast prototypes moving while switching between models and demos.
AI demos break when token ops becomes an afterthought.
Provider accounts, keys, cards, quotas, and model names pile up before the demo works.
Workshops and hackathons need participant access without exposing raw master keys.
Small teams need spend visibility before they build their own billing stack.
Build a workflow around AI API Gateway.
One wallet
Buy credits once and use one gateway key across demos, workshops, and small AI apps.
Model routing
Test cost, speed, and quality across model routes without rewriting your whole integration.
Event control
Give groups controlled token access with clearer budget limits than shared raw API keys.
The practical building blocks behind AI API Gateway.
Token credits
Recharge credits and consume them through a single AI gateway surface.
Gateway key
Swap one endpoint/key into demos, notebooks, agents, and prototype apps.
Budget caps
Keep usage predictable for live demos, classrooms, and early users.
Usage visibility
Review token consumption so teams can plan the next event or product stage.
Team wallet
Set up shared credit pools for workshops, hackathons, and small teams.
Model choice
Route requests by model fit instead of locking every prototype to one vendor.
Start with the workflow that hurts today.
Pick one workflow with repeated demand, visible ownership, and measurable output. Buda gives that team agents, memory, tools, and a shared workspace.
Vibe coding sessions
Keep fast prototypes moving while switching between models and demos.
AI workshops and events
Give participants controlled token access without exposing a master provider key.
Small AI app teams
Validate token usage and cost before building internal billing and metering.
Start with one useful workflow, then expand.
Choose one workflow
Start with Vibe coding sessions. Keep the scope narrow enough that the output is easy to review.
Assign agents and controls
Create the workspace, invite members, assign agents, define files, tools, and usage boundaries.
Measure output and spend
Review artifacts, credit usage, ownership, and execution history before expanding scope.
Expand or stop cleanly
If the workflow proves value, repeat the model in another team. If not, you still have a governed record.
Make token access the easiest part of your next AI demo.
Create a wallet, buy credits, run the quickstart, and keep the session moving.
Start with MoonRouter