Qarar: a Monte Carlo-powered business case platform with a natural-language AI copilot
A SaaS platform that replaces the Word-Excel-PowerPoint shuffle for business case modeling. Inputs support confidence intervals, Monte Carlo simulations stress-test outcomes, and an AI chatbot answers questions in natural language. Launched 2023 with Fortune 500 interest.
Company Background
A SaaS platform that replaces the Word-Excel-PowerPoint shuffle for business case modeling. Inputs support confidence intervals, Monte Carlo simulations stress-test outcomes, and an AI chatbot answers questions in natural language. Launched 2023 with Fortune 500 interest.
Organizations build business cases by stitching together Word, Excel, and PowerPoint — losing fidelity at every handoff. Qarar needed a single platform that could represent uncertainty honestly (not point estimates), simulate outcomes under variation, and let leadership build, share, benchmark, and approve cases without email chains.
Link to ProjectThe Challenge
Organizations build business cases by stitching together Word, Excel, and PowerPoint — losing fidelity at every handoff. Qarar needed a single platform that could represent uncertainty honestly (not point estimates), simulate outcomes under variation, and let leadership build, share, benchmark, and approve cases without email chains.
“Our relationship is more of a transparent partnership where we talk about how we can be successful together and don't have misaligned expectations”
How we approach this project
We built a unified platform with four pillars: an input system that accepts numerical ranges with confidence intervals (e.g., "$80K–$120K at 95% confidence"); a Monte Carlo simulation engine that assesses business case likelihood under that uncertainty; a report builder that compiles results, charts, and graphs for leadership approval; and an approval workflow that prevents scenarios from stalling in review. An AI-powered chatbot with a natural language interface lets users query their own business cases conversationally.
The challenge
Business cases get built across fragmented tooling — a Word narrative, an Excel model, a PowerPoint for the committee. That workflow destroys consistency, makes uncertainty invisible (point estimates masquerade as truth), and turns approval into an email thread. Qarar needed to collapse the whole process into a single platform that preserved analytical rigor and sped up decision-making.
What we built
- Range-based inputs with confidence intervals. Users enter ranges like "$80,000–$120,000 at 95% confidence" instead of false-precision point estimates.
- Monte Carlo simulation. Every scenario is stress-tested across the distribution of inputs to produce honest probability-of-success outcomes.
- Report builder. Results, charts, and graphs compile automatically into leadership-ready deliverables.
- Approval workflow. Scenarios move through structured review with clear accountability — no more cases stalling in an inbox.
- AI chatbot. A natural-language interface lets users query their business cases without learning a modeling DSL.
The outcome
Launched in 2023, Qarar is now live with paying customers and active inbound interest from Fortune 500 companies.
"Our relationship is more of a transparent partnership where we talk about how we can be successful together and don't have misaligned expectations."
— Nayyir Qutubuddin, Founder, Qarar
The result of our work
Launched in 2023 with paying customers and active inbound interest from multiple Fortune 500 companies.
This is what we achieved for Qarar
Launched in 2023 with paying customers and active inbound interest from multiple Fortune 500 companies.
- 01SaaS
- 02Financial Modeling
- 03NLP
- 04Monte Carlo
- 2023
- Launched
- Monte Carlo
- Simulation engine
- Fortune 500
- Pipeline
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