Upload Docker images, Pickle, or PMML files, map variables to LendAPI’s data layer, and execute scoring in sub-100 ms—inside a bank-grade, SOC 2 environment. |
Securely Upload your Model Artifact
Push any model—Python Pickle, PMML, or full Docker image—via CLI or UI; each file is fingerprint-hashed (SHA-256) and stored in an encrypted registry inside LendAPI’s VPC.
Map Model Output to Variables
Use the visual mapper to bind LendAPI or custom variables to your model’s expected schema, preview a sample payload, and validate types before publishing.
Test, Manage Versions & Publish
Call model scores from any workflow, shadow-test new versions on 1 % traffic, compare lift metrics, then promote or roll back with a single click—no downtime.
Model Run Time
Every model executes inside its own hardware-isolated enclave—no shared memory, no public IP, and full AES-256 at rest. Your data never leaves LendAPI’s private VPC, satisfying the most stringent bank, regulator, and SOC 2 requirements.
Push a new Docker, Pickle, or PMML file, shadow-test on 1 % traffic, then promote or revert with a single click. Built-in traffic splitting, latency monitors, and audit logs let risk teams refine models continuously—without waiting for a quarterly release cycle.
Frequently Asked Questions
Got questions, we have answers for you
