Gate
Confirm the request is deterministic and safe to cache. Random requests bypass the exact path.
Aero reduces repeated deterministic inference cost by serving byte-verified cached responses, then proves the savings with latency, cost, and cache-hit evidence.
Repeated request trace
Summarize the cache correctness contract.
X-Aero-Cache
hit
X-Aero-Verified
true
X-Aero-Tier
A
Upstream calls
0
Cached response served without model compute
0
model calls on an exact hit
Byte
verification before serving
Direct vs cached
evidence for every run
The repeated-call problem
Retries, eval reruns, classification jobs, extraction pipelines, and agent loops can send identical requests. If the request is deterministic, paying a model to reproduce the same bytes is avoidable waste.
The same model, prompt, and settings reach the inference provider again.
A provider invoice shows spend, but rarely proves which calls could have been skipped.
A hit-rate claim means little without verification state, timing, and a comparable baseline.
How Aero works
Aero only takes the exact path when it can preserve correctness. Everything else passes through.
Confirm the request is deterministic and safe to cache. Random requests bypass the exact path.
Look up the canonical key, then byte-check the stored request before any answer is served.
Return proof headers, latency, cost, and a receipt that AeroBench can inspect.
Correctness boundary: Tier A is exact and verified. Semantic matching and prefix-warmth heuristics are Tier B, opt-in, and never included in the exactness claim.
AeroBench
Fire one deterministic request twice. AeroBench shows the miss, verified hit, cache tier, measured latency, estimated cost, and receipt headers.
AeroBench is not a chat product. It is a controlled, read-only demonstration of the cache and benchmark system.
Prompt
Latest receipt
Architecture
The marketing site and proof preview work without a live backend. Real inference at bench.go-aero.net stays behind Google authentication and request limits.
go-aero.net
Public explanation
go-aero.net/bench
Read-only proof preview
bench.go-aero.net
Google-authenticated live bench
api.go-aero.net
Rate-limited backend
AeroCache
Determinism gate · canonical key · byte verification
L1 memory
hot entriesL2 Valkey
shared cacheFuture L3
object storageAeroCore placement
Choose the cheapest healthy rung that can meet the request deadline.
Local model
Free, best-effort Mac worker
Cloud provider
Paid fallback for heavy models
AeroCache is the correctness layer. AeroCore decides where misses go. AeroRig measures what happened.
Benchmark evidence
AeroRig measures what happened. It records latency, time to first token, success, answer stability, and verified hit count. The table is an interface preview, not a production benchmark.
BENCHMARK ARTIFACT / PREVIEW
VALUES PENDING| Measure | Direct | Verified hit | Delta |
|---|---|---|---|
| p50 latency | pending | pending | — |
| p95 latency | pending | pending | — |
| Time to first token | pending | pending | — |
| Verified hit count | 0 | pending | — |
| Answer stability | baseline | byte compare | — |
| Success rate | pending | pending | — |
Measured results will replace placeholders after the controlled benchmark study. Losses will be published alongside wins.
Build status
Roadmap
Bring up the always-on cache, proof, and observability host.
Record what each backend can run, what is warm, and measured latency.
Connect the Mac worker as the free, best-effort local inference rung.
Route heavy misses through protected cloud APIs with cost controls.
Add a clearly labeled Tier B prefix-warmth heuristic.
Publish the crossover: where exact caching wins, and where it does not.
See the exact path
Use the public demo without touching the live lab or spending inference budget.