Cut your AI API bill 60–80% with one line of code

Most AI-powered apps pick one model and use it for everything — a frontier model for a simple “say hello” and for a complex reasoning task alike. That’s the equivalent of hiring a senior engineer to answer support emails. PRYSM’s routing engine measures ten intent signals per prompt and picks the right model for each call. Replacing your OpenAI client with PRYSM is a single-line change.

Before: one model for everything

from openai import OpenAI

client = OpenAI()  # every call hits gpt-5.2 at $21/MTok

resp = client.chat.completions.create(
    model="gpt-5.2-pro",
    messages=[{"role": "user", "content": "What's 2 + 2?"}],
)
print(resp.choices[0].message.content)

After: intent-aware routing

from prysm import Prysm

client = Prysm()  # same API, every call routed to the best-value model

resp = client.chat.completions.create(
    model="auto",          # ← this is the only change
    messages=[{"role": "user", "content": "What's 2 + 2?"}],
)
print(resp.choices[0].message.content)
# PRYSM routed to mistral-nemo ($0.02/MTok) — 1000× cheaper than gpt-5.2-pro

The model="auto" flag tells PRYSM to apply its routing engine. Your prompts are never stored — only an anonymous intent classification runs locally.

How intent routing works

PRYSM’s classifier scores each prompt on ten signals in under 5 ms:

Signal	Example prompt	Routed to
`simple`	”What’s the capital of France?”	Budget model
`code`	”Refactor this async handler…”	Code-specialized model
`reasoning`	”Prove that √2 is irrational”	Math/reasoning model
`analysis`	”Compare these three architectural patterns…”	Frontier model
`translate`	”Translate to French:“	Budget multilingual
`realtime`	”Today’s top news”	Search-grounded model

Dry-run: preview routing without calling a model

preview = client.route("Write unit tests for this function")
print(preview["routing"]["model"])        # e.g. "claude-sonnet-4.5"
print(preview["routing"]["why"])          # "code signal + medium complexity"
print(preview["estimated_cost"]["est_1k_tokens"])  # e.g. 0.003 USD

route() shows exactly which model would be chosen and why — no tokens consumed.

Measure your savings

savings = client.savings(baseline="gpt-5.2-pro")
print(f"Saved {savings['saved_pct']}% vs. sending everything to {savings['baseline_model']}")
# Saved 71.3% vs. sending everything to gpt-5.2-pro

Install

pip install prysm1
# or
npm install @prysmai/sdk

Get your API key at prysm1.com. The routing engine is OpenAI-compatible — every parameter, streaming, function-calling, and tool-use feature works unchanged. You change one word, the bill changes dramatically.

​Before: one model for everything

​After: intent-aware routing

​How intent routing works

​Dry-run: preview routing without calling a model

​Measure your savings

​Install