Investor One‑Pager (print to PDF)
AethergenPlatform — Investor One‑Pager
Evidence‑efficient AI: same answers with less compute, lower latency, and stronger governance.
100%
Large‑model calls avoided
1,000,000,000
Queries at scale
Why now
- Compute and storage are the bottleneck; scaling alone is no longer viable.
- We deliver reliability with less compute using retrieval‑first and small‑model‑first.
How it works
- Retrieve, don’t memorize: hybrid search + budget packing.
- SLM‑first: small models handle most work; escalate rarely.
- Risk Guard: answer, fetch more, or abstain before generating.
- Compact memory: anchors, PQ vectors, deltas; no raw corpora.
- Evidence by default: metrics, provenance, crypto profile.
Results
- Open data (NYC anchors): 1B queries with the profile above.
- Closed data pilots typically see 60–90% fewer big‑model calls and 70–95% storage reduction.
What we’re raising
- Pre‑seed to fund 3–5 closed‑data pilots, proof packaging, and references.
- Productization: dashboard controls, evidence UX, offline kits; evaluator library expansion.
- Go‑to‑market: partnerships and Marketplace listings.