Cachee is an AI-powered caching layer that eliminates data retrieval latency. It overlays your existing infrastructure — no migration, no rip-and-replace — and the economics are immediate: memory utilization goes up, server hits go down, infrastructure spend drops, and performance increases by orders of magnitude.
This is a real request lifecycle — a user action that requires data from your backend. Watch how latency accumulates at every hop, and then watch what happens when Cachee intercepts that chain.
Memory utilization rises because Cachee is actively using it. Everything else — server hits, infrastructure cost, response latency — drops dramatically. This is the tradeoff enterprises want: spend more on cheap RAM, spend radically less on expensive compute and database.
Representative enterprise running 100M requests/month across a standard AWS stack. These are the line items that change when Cachee deploys.
| Line Item | Before Cachee | After Cachee | Delta |
|---|---|---|---|
| Cache Cluster | $18,000/mo | $4,500/mo | −$13,500 |
| Database | $32,000/mo | $12,000/mo | −$20,000 |
| Compute | $24,000/mo | $10,000/mo | −$14,000 |
| Data Transfer / CDN | $11,000/mo | $4,500/mo | −$6,500 |
| DevOps Hours (cache mgmt) | 60 hrs/mo ($12,000) | 4 hrs/mo ($800) | −$11,200 |
| Cachee Platform | — | Contact Sales | Starting at competitive rates |
| NET MONTHLY IMPACT | $97,000/mo | $32,300/mo | −$64,700/mo |
Representative figures based on typical enterprise deployment. Actual results vary by infrastructure configuration, workload patterns, and scale.
Cachee deploys in under an hour as an overlay on your existing infrastructure. No migration. No downtime. The data your systems need is already waiting in L1 memory before they ask for it.