Relativities

Run EffectiveAI raters on your own book, in Python.

Relativities brings insurance raters from EffectiveAI, including competitors' rating plans rebuilt from their public rate filings, onto your machine and runs them on a native Rust engine. Rate one submission or an entire book, get exact premiums back, and keep every result to yourself.

Install

pip install relativities
export EFFECTIVE_API_KEY=sk-eai-...

Python 3.12 or newer on macOS, Linux and Windows. Prebuilt wheels, no compiler.

Rate your book

from relativities import Rater

rater = Rater.load("<rater-id>")                   # downloaded once, verified, cached
results = rater.rate(submissions, key="submission_id")  # a DataFrame, rated locally on every core

premiums = results.to_pandas()                     # one row per submission: status, reason, outcomes
premiums["premium"].mean()                         # then it's pandas

rater.explain(submissions, "S-1", key="submission_id")  # its inputs and every calculated value

What you get

• Exact premiums. Every premium is calculated in exact decimal arithmetic, with nothing rounded behind your back.
• Every submission accounted for. Each submission keeps its row. A submission the rater refuses comes back with the reason, never as a zero premium.
• Private by design. Raters run on your machine; your book and results are never uploaded.
• Reproducible. Pin a rater with revision= to rerun exactly, even offline.
• Fast. A whole book is rated in parallel on every core of your machine.
• Every step visible. rater.explain(book, submission_id) lists the inputs the rater received and each intermediate value behind a premium.

License and support

Relativities is proprietary software from EffectiveAI, licensed under the terms in the LICENSE file included with the package. Catalog raters and data are covered by separate agreements.

• Website: https://effectiveai.app
• Documentation: https://docs.effectiveai.app/relativities/index
• Support: support@effectiveailabs.com