SimpleINSPIRE closes the gap between business intent and IT execution — unifying human intent with automated technical execution so carriers configure, manage and deploy complex rules at scale. Proven today on Commercial Package Policy New Business; architected for every line and lifecycle stage, from underwriting to claims.
Fragmented legacy logic and message-to-logic drift make rules slow to change and impossible to trust. Unlike rigid traditional systems, SimpleINSPIRE unifies human intent with automated technical execution — ingesting legacy code, reverse-engineering it through an AI-assisted extract-and-review wizard, and emitting production-ready SQL, stored procedures and REST APIs, all under a tamper-evident hash-chained audit trail and a human-in-the-loop governance gate.
It closes the gap between business logic and technical deployment — turning compliance into an agile asset.
This is how the promise is delivered. Six modules read and write the same authoritative rule — classify it, turn intent into code, inherit your legacy logic, analyse the whole book, and answer questions in plain language. A fix in one module is evidence in another.
See the whole rulebook at last — one classified record per rule: number, line, area, severity, stage, version and coverage, all searchable.
Turn intent into execution — open any rule to run it, generate its query / SP / REST API, document it, and version it.
Catch the bad rule before it ships — author against the standard with a status workflow, a live simulator and parameters, not hard-coded values.
Modernise legacy logic without a big-bang rewrite — ingest deployed procedures, reverse-engineer them with confidence tags, keep PROD authoritative.
Surface what was buried — distribution, concentration, conflict worklists and RE-enablement & migration across the whole book.
Put the rulebook in everyone's hands — ask in plain language, get a grounded, cited answer linking the rule, its code and its tests.
Every change is versioned and supersedes — never overwrites. Each action lands on a tamper-evident, hash-chained audit trail, and a human-in-the-loop gate approves anything compliance-relevant before it ships.
Turning compliance into an agile asset only works if the foundations hold. These five tenets are what make the claims on the previous pages true — not slogans, but the way the platform is built.
Each rule is classified once across six dimensions; the library, analytics, generation, assistant and governance all read the same atom.
Classification surfaces the message-to-logic drift a read-through misses — contradictory windows, hard-coded ranges, rules that can never fire.
The engine doesn't just flag. It generates the query, procedure and API, drafts test cases, and proposes the fix — a human approves.
Modifying a rule creates a new version that supersedes the last; full lineage is preserved and coverage travels with each version — nothing is ever lost.
Imports stay the source of truth and the engine offers a candidate, never an overwrite; AI answers are grounded and cited, with a human-in-the-loop gate.
Validations live across deployed procedures, APIs and spreadsheets that disagree. The Rule Library makes one classified record per rule — number, line of business, area, severity, stage, version and coverage — searchable, sortable and exportable.
Open a rule and it stops being prose. The drawer turns its classifiers into a unit you can run, compile to three artifacts, document, and version — with production truth and the rule-engine candidate side by side.
Bring stored procedures and APIs in through one consistent intake, reverse-engineer them into conforming rules with confidence tags and a human gate, and keep the deployed code as the system of record — landing them on the same classified standard you author new rules against.
Author against the same standard your imported rules conform to, with a Draft → Verified → Approved → Published workflow, a simulator that traces every guard, and configurable parameters that keep message text and logic from drifting apart.
You have now seen both doors — Imports reverse-engineers what is already deployed, and the Configurator authors what is new. Step back and it is one journey: the old world of scattered code, baselined onto a single standard, then built forward on it — without ever disrupting what is running.
Two steps, one standard. Imports baselines the deployed past; the Configurator builds the future — both on the same governed model. Production keeps running until you choose to migrate, so there is no leap of faith.
Scattered across procedures, the portfolio view was impossible. RE Analytics reveals distribution, concentration and cadence, lists the conflicts and duplicates to act on, and tracks migration to the engine on a need basis.
A floating assistant on every screen answers plain-language questions only from the actual rules, cites each by number and version, and returns the connected picture — rule, its code, its tests — so knowledge no longer lives in a few heads.
Every rule carries its own regression suite. The engine derives structured unit cases per rule and version, each with a traceable ID, so go-live and every change after it are backed by evidence — not hope.
Every meaningful action — rule creation, generation, publication, exports, AI questions, workspace switches and configuration changes — is timestamped and hash-chained, so the record is complete and tampering is evident.
Behind the six modules sit the stores and controls that hold everything together: the generated code, the circulated specifications, and the multi-client administration that keeps each carrier's rulebook and AI configuration separate and governed.
The 725 New Business rules are the first reference set. Done well on logic SPRISKA knows intimately, they de-risk the whole platform — and everything here generalises to more lines, more transaction types, deeper analytics and AI-assisted authoring.
One LOB / NB validated on logic the client knows — the platform de-risked.
Connect to the SPRISKA datastore; coverage and analytics repoint with no rework.
More lines and transaction types; conflict detection, impact preview, parameter fast-path.
Shared patterns become reusable templates; non-experts compose test-covered bundles.