Every token you send to an LLM costs money. For small teams running agents daily, those costs add up fast. A naive implementation of text2report can burn through €200/day in API calls for a single active user. We engineered around this problem from day one: — Schema compression: Instead of sending your entire database schema on every query, we build a condensed context with only relevant tables, column types, and row counts. A 400-table database becomes a 2KB context payload. — Prompt caching: Repeated system instructions use cache_control headers, so you pay for them once per session, not once per message. — Fallback rotation: When primary API quotas hit limits, we rotate to secondary keys seamlessly — no failed queries, no wasted retry tokens. — Memory injection: Instead of re-explaining patterns every time, we inject learned shortcuts directly into the prompt. Fewer tokens in, better answers out. The result: our agents deliver enterprise-grade AI responses at startup-friendly costs. Most teams spend less on baachee in a month than they'd spend on one consultant for a day. Smart architecture beats brute-force token spending. Every time.