Stop reporting on the past. Forecast the future.
We build predictive analytics dashboards that go beyond historical reporting — forecasting demand, churn, sales pipeline, revenue, inventory needs — so leadership can act on what’s coming, not just what already happened.
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The Problem
Most business dashboards are rear-view mirrors. They show you last quarter’s revenue, last month’s churn, last week’s pipeline. By the time you see the data, the decision opportunity has passed.
Worse, most dashboards drown leadership in metrics without highlighting what actually matters. The CEO scrolls through 47 KPIs trying to figure out what to do about any of them. Decision paralysis from data overload.
Predictive analytics flips this. Instead of ‘here’s what happened,’ you get ‘here’s what’s coming, and here’s what to do about it.’ Demand forecasts that drive inventory decisions. Churn predictions that trigger retention campaigns. Pipeline forecasts that tell you which deals need attention this week.
Curious if this fits your business?
Book a free 30-minute AI Audit. We’ll identify 1-3 specific opportunities with clear ROI estimates. No pitch, no slides.
Book Your Free Audit →What We Build
We build custom predictive analytics dashboards for executive teams. Each one combines your historical data with predictive AI models to surface what’s coming and what to do about it.
Common builds: revenue forecasts with deal-level confidence, churn predictions with retention recommendations, demand forecasts driving inventory and staffing, pipeline health with conversion probability per stage, customer LTV predictions for marketing budget allocation.
Built for results, not demos
Every system we build has measurable success criteria from day one. We don’t ship pretty UIs that no one uses — we ship outcomes.
Your team gets a working solution that fits the way you actually run, with full documentation, training, and our team on call when something needs tuning.
How It Works
Decision audit
We work with leadership to identify the 3-5 decisions that most need better forward visibility — the ones that move the business.
Data plumbing
We connect to your CRM, billing, product analytics, ERP, and any other source needed for the forecasts.
Build & validate models
We train predictive models on historical data and validate them against held-out periods. Accuracy reported transparently.
Deploy decision-grade dashboards
Clean, focused dashboards built for action — not data warehouses for browsing.
What It Looks Like
Where This Wins
Sales Leadership
Pipeline forecasting with deal-level confidence. See which deals to push, which are slipping, which are likely to close.
Customer Success
Churn predictions with recommended retention plays. Save accounts before they cancel.
Operations & Supply Chain
Demand forecasting for inventory, staffing, and capacity planning. Cut waste and stockouts.
Finance & FP&A
Revenue, expense, and cash flow forecasts that beat traditional spreadsheet models.
The compounding effect
Most AI projects deliver one-time gains. Ours compound. As more of your operations run through AI systems, the data they collect makes them sharper week over week.
Six months in, you’ll be running circles around competitors who are still doing the work the old way.
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Why demelos
Forward-looking
We predict what’s coming, not just report what happened. Decisions get made earlier, with more information.
Decision-focused
Each dashboard answers a specific business question. No metric soup, no dashboard sprawl.
Validated accuracy
We back-test every model and report accuracy honestly. You know what to trust and how much.
Questions, answered
Depends on data quality and what’s being forecast, but typically 80-95% within useful confidence intervals. We report accuracy transparently.
Salesforce, HubSpot, Stripe, your data warehouse (Snowflake, BigQuery, Redshift), product analytics (Mixpanel, Amplitude), Google Analytics, custom databases — basically any source with structured data.
BI tools (Looker, Tableau, Power BI) show what happened. We build models that predict what’s coming. Different category, complements existing BI.
No — it makes them dramatically more impactful. They go from building reports to interpreting predictions and recommending actions.
First dashboard typically live in 4-8 weeks. Quality improves as models see more data.
Yes — we use explainable AI techniques so dashboards show the drivers, not just the predictions. Critical for trust and action.
