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"The per-token pricing model is going to look ridiculous in hindsight. Imagine paying per-word to read a book or search your own notes. That's where we are with embeddings and generation right now." — Andrej Karpathy @karpathy Paraphrased from 2024–2025 commentary on embedding economics
Every time you embed, you pay. Every time you search, you pay. Every time a model deprecates, you pay to re-embed everything.
We fixed this. Project any embedding to 82 dimensions. Own it forever. Never pay per-query again.
Upload once → we project to 82D → you own the result forever. No more API calls, no more vendor lock-in.
Proven on A100 GPUs. 100% lossless JL projection. Patents pending.
Every AI company charges you rent on your own knowledge.
Documents, code, conversations, research. Years of accumulated knowledge.
Pay OpenAI $0.13/1M tokens. Now you have 1536D vectors.
Pay again. Every query. Forever. Or store locally and hope they don't change the model.
text-embedding-ada-002 → deprecated. Re-embed everything. Pay again.
Project your OpenAI, Cohere, or any 1536D embeddings to 82D in one API call.
from eightytwo import Client
# Initialize with your API key (get one after signup)
client = Client(api_key="your-key-here")
# Project OpenAI embeddings to 82D
vectors_1536d = openai_client.embeddings.create(...).data
vectors_82d = client.project(vectors_1536d)
# That's it. Own them forever.
print(f"{len(vectors_82d)} vectors → 82D")
print(f"Size: {len(vectors_1536d[0])*4}KB → {82*4}B per vector")Sign up to get your API key and endpoint URL.
# After signup, you get:
# - API endpoint URL
# - API key
# - Full documentation
# Example response format:
{
"vectors": [[0.04, 0.10, ...82 floats]],
"count": 1000,
"input_dim": 1536,
"output_dim": 82,
"processing_time_ms": 12.5
}Paste 1536-dimensional vectors (from OpenAI, Cohere, etc.) to project to 82D.
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$0.25 per GB of output. No subscriptions, no hidden fees.
First 10MB free. No subscription required.
HIPAA-compliant. PHI never leaves your infrastructure.
SOX/PCI ready. Trade secrets stay secret.
FedRAMP pathway. Data sovereignty guaranteed.
Private agent memory. Infinite context. Zero API costs.