Open-source model for the annual cost of fragmented, disconnected data — and the ROI of unifying it. For data and AI leaders (CDO, Head of Data, Head of AI) sizing the cost of data silos before an integration or knowledge-graph investment.
▶ Use the live tool: tools.langoptima.com/calculator
The live version adds a saved, shareable report. This repo is the open calculation engine underneath — the assumptions are transparent and yours to inspect.
The pricing figures here are illustrative placeholders, not a quote. Plug in your own numbers (see
config.example.json) before relying on the output.
- The annual cost of siloed data: duplicated effort, integration overhead, and analyst/scientist time lost to reconciliation.
- The ROI and payback period of moving to a unified, connected data layer.
npm install
npm run typecheck && npm testimport { calculateResults, DEFAULT_INPUTS } from "@langoptima/data-silo-cost-calculator";
const result = calculateResults(DEFAULT_INPUTS);
// → cost breakdown, ROI projection, payback period (or null if it never pays back)Framework-agnostic TypeScript, zero runtime dependencies.
LangOptima builds AI-ready data and knowledge-graph systems for enterprises. This is one of our open-source free tools — langoptima.com.
Apache-2.0. Free to use, modify, and redistribute. The LangOptima name and marks are not licensed — a fork may not imply endorsement (see NOTICE). Contributions: CONTRIBUTING.md · Support: SUPPORT.md.