The economics

Every query is the cheap part.

RAG's cost is ~92% frontier tokens — your context through a premium model, every time. Everyday moves that into a one-time training step, then serves on open-model GPUs.

✓$0.0015 per query vs $0.025 for RAG
✓Flat as your corpus grows
✓Break-even in a few hundred queries

Estimate your savings ↓

Per-query cost

@ 100k queries / month

Everyday$0.0015

Prefill (warm cache)$0.0040

RAG → frontier model$0.0250

~16×

vs RAG

~2.6×

vs prefill

~450

queries to break even

Savings calculator

What you'd pay per query.

Drag to your monthly volume. Serving cost only — one-time training repays in ~450 queries.

Queries per month 100,000

1K10K100K1M10M

Everyday / mo

$150

RAG / mo

$2,500

You save / yr

$28,200

~16× less than RAG, and flat as your corpus grows.

How it stacks up

Everyday vs. the alternatives.

RAG, long-context, and fine-tuning each trade away cost, freshness, grounding, or scale.

	Everyday	RAG	Long-context	Fine-tuning
Per-query cost	Very low, flat	High (per-token)	Very high	Low
Cost as corpus grows	Flat	Grows	Grows fast / caps out	Flat
Grounded & sourced	Yes	Yes	Yes	No
Fresh on updates	Retrain affected shards	Instant re-index	Instant	Full retrain
Scales to huge corpora	Yes (sharded)	Yes	No (window limit)	Limited
Private on your cloud	Yes	Depends	Depends	Yes

RAG stays a strong baseline — Everyday's edge is flat cost at scale with comparable grounding.

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