Real-time AI model calibration
Spend less on AI.
Trust it more.
Reality Signal™ calibrates any model's confidence into a true probability with uncertainty — so you can cut LLM costs, control agent actions, and catch drift before it costs you. Two API calls. No retraining.
What developers use Reality Signal™ for
Add calibrated confidence to any AI workflow in under 10 minutes.
Smart Model Rerouting
Stop paying for GPT-5.4 or Claude Opus when a smaller model is confident enough. Reality Signal™ tells you which model to use per-request — teams see 30–50% cost reduction on LLM spend.
use_model("gpt-5.3-instant")
else:
use_model("gpt-5.4-thinking")
RealityRouterrealityrouter.dev →
Stop paying Opus prices for Haiku tasks. Open-source proxy that plugs in between your agents and every LLM. Picks the cheapest model that will still nail each query — escalating only when it won't. Apache 2.0. Self-hosted.
openai.api_base = "http://localhost:8000/v1"
# routes each call to the cheapest model that works
Agent Action Gating
Before your agent books a flight, issues a refund, or sends an email — Reality Signal™ tells you if the model is actually sure. Green = automate. Yellow = verify. Red = escalate.
Production Drift Monitoring
Your model worked great last month. Is it still working? Reality Signal™ monitors calibration in real time and alerts you before bad decisions pile up.
model classifier-v3 reliability
dropped from 0.94 → 0.71
Your model says 85% confident. Is it really?
Raw confidence scores aren't probabilities. When you threshold on uncalibrated scores, you over-automate risky cases and escalate easy ones — silently burning money and your reputation on every decision.
Two API calls. That's it.
Send your score, get a calibrated decision. Send feedback, and it gets smarter. Fully optimized in 30–50 examples.
Send your score
POST your model's raw confidence to /decide
Get a decision
Receive true probability + uncertainty + a clear yes/no decision
Send feedback
POST the outcome to /feedback — calibration improves automatically
import requests
res = requests.post(
"https://api.realitysignal.ai/decide",
headers={"x-api-key": "YOUR_KEY"},
json={"features": {"score": 0.82}}
)
decision = res.json()
# decision["prob_est"] -> 0.94
# decision["uncertainty"] -> 0.02Stop guessing. Start deciding.
Get started for free. See calibrated decisions in under 5 minutes.