Outsmart your competitors with applied mathematics. These are the hard problems your BI tools can't answer — predictive models built from first principles on your actual data. The kind of quantitative work most BI shops genuinely can't do.
What We Build
Every model starts with a business question and ends with a deployable answer. We work with messy, real-world data — not clean textbook examples — and we document hypotheses and methodology throughout so the work is reproducible, auditable, and SR&ED eligible.
- • Demand & revenue forecasting — know what's coming before it arrives
- • Pricing optimization models — find the price point that maximizes revenue
- • Cohort survival analysis — understand churn-adjusted lifetime value
- • Scenario & simulation planning — test decisions before you make them
Techniques We Use
We apply the right method to the right problem — not the trendiest one. Our work draws on established statistical and mathematical frameworks, adapted to messy real-world conditions:
- • Kaplan-Meier survival curves for customer LTV and churn-adjusted revenue. Instead of guessing how long customers stick around, we model it empirically — accounting for censored data and time-varying hazard rates.
- • Holt-Winters triple exponential smoothing for seasonal demand forecasting. This captures level, trend, and seasonality simultaneously — critical for businesses with cyclical revenue patterns.
- • Bayesian posterior updating for supply-chain and pricing prediction. As new data arrives, the model updates its beliefs rather than being retrained from scratch — faster convergence, better calibration.
- • Price elasticity optimization for revenue-maximizing price points. We estimate demand curves from transaction data and find the price that maximizes contribution margin — not just revenue.
Not a Black Box
Every model we deliver includes full documentation: the methodology, the assumptions, the validation results, and the code. You own everything. If you want to extend or retrain the model later — with us or without us — you can. No vendor lock-in, no proprietary runtime, no monthly fee to keep the predictions running.
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Frequently Asked Questions
What types of models do you build?
Demand and revenue forecasting, pricing optimization, customer lifetime value via survival analysis, Bayesian inference models, and scenario simulation. If it involves applied mathematics on real business data, we can build it.
Do I need clean data to get started?
No. Working with messy, real-world data is standard. The engagement includes a data audit and cleaning phase. Perfect data is a prerequisite for textbook examples, not for building useful models.
Does modeling work qualify for SR&ED tax credits?
Often yes. Modeling work qualifies when it involves technological uncertainty — novel approaches to data processing, models targeting accuracy thresholds not achievable with known methods, or original statistical methodology.
Do I own the model and methodology?
Yes. Every model we deliver includes full documentation: methodology, assumptions, validation results, and the complete source code. No vendor lock-in, no proprietary runtime, no monthly fee to keep predictions running.
Interested? Let's talk →