Compensa.

The problem

Sales commission changes arrive as messy, semi-structured language — spreadsheets, Slack messages, policy documents, and ad hoc explanations — that a BI / Data / RevOps analyst must interpret before any implementation can begin. The analyst assembles meaning from scattered sources, then loops back and forth with stakeholders to resolve ambiguities around thresholds, exceptions, timing, and ownership.

With no standardized intermediate artifact, BI jumps too quickly from business language to SQL, which increases rework and makes review harder. Intent is poorly traceable: it's difficult to preserve a clean record of what was asked, how it was interpreted, and what assumptions were made. These workflows are high-trust and high-consequence — errors in logic interpretation damage payout accuracy and stakeholder trust.

The solution

Compensa converts scattered commission-change intent into a BI-ready rule specification before implementation begins. A user manually starts a request, adds the sources they already work with — Google Sheets, uploaded files, pasted Slack context — and the system centralizes them into one working record.

The AI then drafts a structured rule spec with rule summary, plan scope, effective dates, eligibility logic, rates and thresholds, exceptions, timing, dependencies, assumptions, citations, and confidence markers. Instead of smoothing over uncertainty, it surfaces ambiguity explicitly and generates targeted clarification questions. The product intentionally stops short of execution — deterministic calculation, locking, and payout remain outside its scope so humans retain judgment over payout-impacting decisions.

How it works

Compensa is built around a structured, multi-layer master prompt that separates persistent system behavior from request-specific context, feeding inputs in clearly delimited XML sections — `business_context`, `request_metadata`, `user_request`, and `source_materials`. The model returns exactly one `rule_spec` block with a fixed schema, giving the UI a stable structure to render drafts and clarifications, and runs silent quality checks that separate confirmed facts from assumptions and detect conflicts across sources.

Retrieval grounds the draft in current policy and historical rules but is an enabling mechanism, not the primary product. The capstone uses a compact reasoning model (OpenAI gpt-5.4-mini) as a server-side drafting layer with schema-validated outputs; the deterministic commission backbone stays in the existing BigQuery-style pipeline. Good output requires at least 80% of material rule elements to cite a source or be labeled an assumption, and any attempt to calculate payouts or approve is an automatic fail.

Who it's for

Compensa is a B2B, internal operations product. The primary end user is the BI / Data / RevOps analyst responsible for turning commission-plan changes into implementation-ready logic. Secondary users are Commission Operations stakeholders who author and review requirements and answer clarification questions.

The economic buyers are senior sales and revenue operations sponsors — VP Sales, Head of RevOps, Head of BI — responsible for scaling operations while maintaining commission fairness and protecting margins. Executive approvers and downstream HR/Payroll teams are indirect stakeholders.

Why it matters

Commission operations remain spreadsheet-heavy and only partially automated, while plans grow more complex and change more frequently — increasing demand for faster requirements-to-logic translation. The company is at an established, scaling stage, but this product is at internal incubation: no centralized translator workflow exists today.

The value model is cost avoidance and operational leverage — reducing BI translation time, lowering rework, speeding plan-change implementation, and reducing governance risk — rather than direct revenue. The broader incentive-compensation software category is projected to grow at roughly 7–10% annually, supporting a possible future external productization path beyond the current internal scope.

At a glance

Project

Compensa

Built by

Luka Dujmovic

One-liner

Compensa converts scattered commission-change intent into BI-ready rule specifications before implementation begins.