Building a 4-Tier AI Cost Auto-Routing System with Supabase Edge Functions

What I Built

I added a provider.chat_auto action to the AI Hub Edge Function of my personal life management app.
It automatically routes AI requests through 4 cost tiers, escalating to more expensive providers only when cheaper ones fail.

The 4-Tier Architecture

Auto-Escalation Logic

const TIER_ORDER: Tier[] = ["free", "budget", "performance", "premium"];

async function callWithAutoEscalation(messages, preferredTier = "free") {
 for (const tier of TIER_ORDER.slice(TIER_ORDER.indexOf(preferredTier))) {
 for (const provider of TIER_PROVIDERS[tier]) {
 try {
 const result = await callSingleProvider(provider, messages);
 await logCost(provider, tier, true);
 return result;
 } catch {
 // Try next provider in tier, then escalate to next tier
 }
 }
 }
 throw new Error("All tiers exhausted");
}

If a provider fails (quota, network, API error), the system automatically:

1. Tries the next provider in the same tier
2. Escalates to the next tier if all providers in the current tier fail

Cost Tracking

Each request logs to ai_hub_chat_logs with provider, tier, estimated_cost_usd, so I can track:

• Which providers are actually being used
• When escalations happen (indicates quota issues)
• Monthly cost breakdown by tier

Key Refactor

The original provider.chat had all provider API calls inlined in a giant switch-case.
I extracted callSingleProvider() so both provider.chat and provider.chat_auto share the same calling logic — no code duplication.

Result

Free tier (DeepSeek/Groq free APIs) handles most requests at near-zero cost.
When Claude quota runs out, it automatically falls back to OpenAI → Google → DeepSeek.
AI feature uptime improved significantly.

Building in public: https://my-web-app-b67f4.web.app/

FlutterWeb #Supabase #buildinpublic #Deno