The Reslt Platform
AI-Powered Test Automation, LLM Assurance and Governance Readiness serve mortgage and insurance; the Data Exchange Engine and the On-Prem LLM are built for mortgage. Each runs in your environment — use one with your own team, or add Reslt AI engineering for the wider product.
The offerings
Start with the problem you need to solve. Each offering carries the domain with it — mortgage and insurance — and runs inside your environment, so none of them is a generic tool you would have to populate yourself.
AI-Powered Test Automation
AI writes the automation; deterministic engines run it. Playwright, Appium and BrowserStack in your own CI — with fixtures and suites for MISMO payloads, GSE delivery paths and pricing decisions already in the box.
How it works →LLM Assurance
Guardrails, retrieval context and response behavior tested against reviewed scenarios. Every model, prompt or knowledge change is compared against the baseline, and production findings become regression tests.
See LLM Assurance →Data Exchange Engine for MISMO
Bidirectional conversion between your proprietary model and MISMO — Reference Model 3.6.x and MCD v2.0. Every conversion emits its own evidence, and a mapping that cannot round-trip is not approved.
See the engine →On-Prem Customized LLM for Mortgage
Guardrails, retrieval and prompts engineered against your own documents and policy language at build time, then deployed into your environment to run there. It proposes; a named person decides.
See the On-Prem LLM →Governance Readiness
MISMO FRAME for mortgage and the NAIC AI Model Bulletin for insurance — inventory, control-to-evidence trace, monitoring and change log produced as you work. SOC 2 compliance support and CCPA and state privacy readiness. Readiness support, not a certification.
Governance Readiness →The proof: the same platform runs behind AI risk systems live inside Fortune 100 carriers, past their security review — and a mortgage lending platform built end to end, origination through servicing, for a customer whose entire engineering operation we run. Read the outcomes →
True of every offering
Everything runs inside your environment, on your infrastructure. The platform operates in your environment. Zero code transfer, and your security team can verify it.
No model sets a rate, an eligibility outcome or a disclosure. Those paths are ordinary reviewable code that returns the same result on the same input. Where a language model earns its place it proposes, and a named person approves.
Configured against your systems, your specs and your rules — not a generic product you bend to fit. The customization is the engineering, and it is the part you are actually buying.
What we hand off is standard, documented, production code — no runtime dependency on our platform, maintainable by your team or any team you choose. The delivered client code is yours; the Reslt Platform that builds and proves it stays with us.
AI in your product
The decision paths we deliver run deterministic in production — no model improvising a rate, an eligibility call or a disclosure. When a language model does earn its place, it ships contained: guardrails, retrieval and prompts engineered at build time, deployed into your environment to run there, and a human control point on every output it produces.
Default
Deterministic code
The decision path is ordinary, reviewable code. No model in the loop, so there is no generative output to govern on that path.
Input → logic → output, identical every time
Exception
AI, contained
When a runtime AI feature earns its place, it runs inside a boundary — and nothing reaches production without clearing every gate.
Contained, consistent, evidence a regulator can hold
The domain, in order
A platform only matters if the output is domain-correct, and a domain pack is only worth having if it is deep enough to be wrong about something. So the pack is mortgage today, and insurance follows once mortgage repeats. Our experts are fluent in both; the products are built out in that order, deliberately.
MISMO data standards — ULDD and iLAD — GSE delivery data, credit-bureau feeds and consumer PII are modeled on the spine, so every artifact and test is domain-correct and compliance-aware from the first commit.
Policy and claims data plus high-volume vehicle telemetry — sensor streams, event data and video — normalized and provenance-tracked at carrier scale, inside your environment.
A walkthrough shaped around your product, your stack, and your buyer's security questionnaire — or start with the four-week Enterprise-Readiness Engagement and see it working on your own product.
Discuss your use caseWant a structured start? The optional four-week engagement →
