Nexio Platform
Placement decisions that survive audit
Send a placement request. Get back ranked candidates with scoring rationale, confidence signals, and a complete audit trail. One API call. Every decision defensible.
import nexio
client = nexio.Client(
api_key="nx_live_k8s2..."
)
# Evaluate a placement in one call
result = client.evaluate(
profile={
"entity": "acme-manufacturing",
"state": "CA",
"line": "professional_liability",
"revenue": 12_000_000
},
pool="carriers:all"
)Placement Evaluation
Acme Manufacturing
Assessment: Strong fit for CA professional liability
The Problem
Your placement process cannot explain itself
The output works until someone asks you to defend it.
01
A single score hides every tradeoff
You collapsed a multi-dimensional decision into one number. Your team cannot see the tradeoffs. Your clients cannot understand the output. When the result is wrong, nobody can trace it back to the input that caused it.
02
Regulators ask, you improvise
A compliance officer asks why Client X was placed with Carrier Y. Your team reverse-engineers the reasoning from memory. The audit trail is a person, not a system.
03
Domain knowledge leaves when people do
Your best people carry the real evaluation logic in their heads. When they leave, years of placement knowledge leave with them. You cannot scale what you cannot encode.
Evaluation Pipeline
Hard rules first. Then structured inference. Then full reasoning.
The pipeline separates what’s verifiable from what requires judgment. Every exclusion justified. Every evaluation traceable.
STAGE 01
Thousands to dozensRelevance
Deterministic rules eliminate non-viable candidates. Licensing, jurisdiction, appetite gates, regulatory exclusions. Binary checks, no inference required. The candidate pool drops from thousands to dozens in milliseconds.
STAGE 02
6 × 4 categorical scorecardInference
Multivariate assessment across six dimensions, each scored on a four-level categorical scale. “Strong appetite fit” is more honest than 78 out of 100. The engine surfaces tradeoffs that binary rules cannot capture.
STAGE 03
Full audit trailReasoning
Per-candidate reasoning, confidence signals, and complete decision paths. Why A over B. What was considered. What was ruled out. Every output holds up under audit.
Try It
Watch the pipeline run
The three-stage pipeline described above, running live against sample data. No sign-up required.
Entity Profile
Press Run Evaluation to start
The Engine
Built to be interrogated
The evaluation is not the hard part. Defending it is.
Transparent by default
Every evaluation produces a permanent trace: inputs, inference steps, scoring rationale, and final output. Every score has a reason. Every exclusion has a rule. The trace is ready for compliance review or a courtroom.
Human in the loop
The engine augments human judgment. It does not replace it. Every recommendation surfaces full reasoning so your team can interrogate, override, and refine.
Learning loops
Placement outcomes feed back into the scoring model. Institutional knowledge compounds over time instead of leaving when people do.
See the full audit trail for a real placement
Walk through a live evaluation using your data. Inspect every score, exclusion, and reasoning step. No commitment required.