Capability / 01 / Match
Match
Two-sided pairing, fully reasoned. Ranked output with sourced rationale and evidence on every score.
Your matching process cannot explain itself
01
A single score hides every tradeoff
You collapsed a multi-dimensional analysis into one number. Your team cannot see the tradeoffs. Your clients cannot understand the output.
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 matching logic in their heads. When they leave, years of pattern knowledge leave with them. You cannot scale what you cannot encode.
How Match fits into your matching work
Input
A subject and a candidate set
A subject (a deal, an account, a candidate brief, a property) and a candidate pool (carriers, sellers, candidates, books). Plus your matching criteria: hard rules, scoring dimensions, exclusion logic.
Output
Ranked output, sourced rationale per pair
Each candidate scored across the dimensions your firm cares about, with sourced rationale per pair. Categorical scoring, not opaque numerics. Exclusions visible, reasoning attached, output ready to defend.
Configured
Your scoring, your appetite, your exclusions
Configured to your firm's dimensions, gates, and house standards. The platform learns from your historical determinations, not a generic baseline.
Integration
Reads from your stack, routes to your tools
Direct APIs into AMS, CRM, and candidate databases. MCP servers, partner feeds, and document parsing where systems aren't API-first. Routed output lands wherever your team already works.
One API call. Ranked output with sourced rationale
What you send to the platform, and what you get back. Categorical scoring across six dimensions, evidence per dimension, audit trail.
import nexio
client = nexio.Client(
api_key="nx_live_k8s2..."
)
# Run a match in one call
result = client.match(
profile={
"entity": "calder-manufacturing",
"state": "CA",
"line": "professional_liability",
"revenue": 12_000_000
},
pool="carriers:all"
)Match evaluation
Calder Manufacturing
Assessment: Strong fit for CA professional liability
An example run, step by step
Submission to ranked carriers, the way the platform walks through it. Sample data, no sign-up required.
Entity Profile
Press Run Evaluation to start
Questions teams ask
Does Match work outside insurance?
Yes. Match is two-sided pairing for any subject and candidate set: deals to buyers, candidates to roles, properties to mandates, accounts to carriers. The dimensions change by vertical; the ranked, sourced output does not.
Where does the candidate pool come from?
From your systems. Match reads the pool you already maintain, whether that is an account book, a carrier roster, a candidate database, or a deal pipeline. The platform does not maintain its own pool of candidates.
How is the ranking explained?
Every pair carries sourced rationale per dimension, not a single opaque number. Categorical scoring shows where a candidate is strong, where it is weak, and which exclusions applied, so the output is ready when a client or an auditor asks why.
Can we encode our own scoring and exclusions?
Yes. Your dimensions, hard rules, and house standards are configured in, and the platform learns from your historical determinations rather than a generic baseline. What surfaces is what your team would actually consider.
Book a demo
See Match in action
Walk through example deployments and how Match maps to your firm's pairing work. Inspect every score, exclusion, and reasoning step.