Services
Time Series Forecasting for High‑Stakes Digital Projects

Time Series Forecasting for High‑Stakes Digital Projects in Dubai

Stralya designs and deploys production-grade time series forecasting models that plug seamlessly into your cloud-native web platforms. From traffic and demand prediction to revenue and risk, we help Dubai organisations turn historical data into reliable foresight—under fixed, predictable project scopes.

What you get

A Complete Time Series Forecasting Capability, Not Just a Model

Stralya’s time series forecasting service is designed for organisations that need more than a proof-of-concept. You get a fully engineered forecasting layer that plugs into your digital ecosystem and supports real decisions every day.

Core deliverables included in every engagement

Business and data scoping workshop tailored to your Dubai context and market dynamics.

Data audit, cleaning strategy, and feature engineering plan with clear quality metrics.

Benchmark of multiple forecasting approaches with transparent performance comparison.

Production-ready forecasting models with documented APIs and integration points.

Automated pipelines for data ingestion, retraining, and forecast generation.

Monitoring dashboards for model performance, drift, and data quality.

Knowledge transfer sessions for your technical and business teams.

Optional add-ons for strategic programmes

Real-time forecasting for high-frequency traffic or trading scenarios.

Advanced MLOps setup with CI/CD for models and data pipelines.

Integration with BI tools (Power BI, Tableau, Looker, Data Studio)."

Custom alerting and anomaly detection on top of forecasted ranges.

Dedicated senior data engineer or ML engineer embedded in your team.

Each project is scoped and priced based on your data maturity, forecasting horizons, and integration complexity. Our fixed-price approach ensures full transparency from day one, with no surprises—only measurable outcomes.

Key Benefits for Your Dubai Organisation

Sharper strategic planning

Use reliable forecasts of demand, traffic, and revenue to plan investments, marketing, and capacity with more confidence, reducing costly over- and under-allocation.

Faster, data-driven decisions

Move from reactive to proactive management with up-to-date forecasts embedded directly into your dashboards and operational tools.

Optimised costs and resources

Align staffing, infrastructure, and inventory with expected demand, improving margins and reducing waste across your digital operations.

Reduced operational risk

Identify potential drops or spikes early, simulate scenarios, and put safeguards in place before issues impact your customers or stakeholders.

Stronger digital products

Enrich your cloud-native web applications with intelligent features—dynamic pricing, smart capacity limits, personalised experiences—powered by robust forecasts.

How we work

A Structured, Fixed-Price Approach to Time Series Forecasting

Every forecasting engagement is run as a structured, project-first mission. We start by clarifying the business question and the data reality, then design and implement a solution that is robust enough for Dubai’s most demanding digital environments.

We align with your leadership and technical teams on the forecasting objective: which KPIs to predict, at what horizon and granularity, and how the forecasts will be consumed (dashboards, APIs, alerts, product features). We review your current data stack and constraints to define a realistic, fixed-price scope.

We explore your historical time series data, identify gaps, seasonality, trends, and anomalies, and design the right feature set (calendar events, promotions, weather, macro indicators, etc.). We then structure clean, versioned datasets ready for modelling, with clear data quality metrics.

We test multiple forecasting approaches (classical models, ML, and, when relevant, deep learning) and benchmark them using rigorous backtesting. We evaluate accuracy, stability, and business impact, selecting the model family that best balances performance, explainability, and operational cost.

We deploy the chosen models into your cloud-native environment with automated data ingestion, scheduled retraining, and real-time or batch inference. Forecasts are exposed via APIs, dashboards, or embedded product features, with logging and monitoring for drift and performance.

We put in place clear monitoring dashboards and alerts, fine-tune models based on live performance, and document everything. Your teams receive training on how to interpret and use the forecasts, ensuring long-term autonomy and reliable decision-making.

Find Commonly Asked Questions

We work on forecasting projects that are directly tied to business-critical outcomes: traffic and load forecasting for web platforms, demand and booking prediction for marketplaces and hospitality, revenue and cashflow forecasting, subscription and churn prediction, and operational forecasting (support tickets, logistics volumes, capacity planning). If the forecast affects a strategic decision or a core digital product, it is in our scope.

Deployment is a core part of our mandate. We design models and the surrounding data pipelines so they can run reliably in production, within your existing cloud environment (AWS, Azure, or GCP). We expose forecasts through APIs, dashboards, or direct integrations into your web applications, with monitoring and automated retraining where needed.

Accuracy depends on data quality, history length, external factors, and the volatility of your business. During the scoping phase, we define realistic accuracy targets and evaluation metrics (MAPE, RMSE, etc.) and validate them through backtesting. We always show you how the model would have performed on your past data, and we do not overpromise beyond what your data can support.

Yes, many real-world time series are messy. We invest time in data cleaning, anomaly detection, and feature engineering to extract as much signal as possible. Where data is too limited for advanced models, we design simpler, more robust approaches and clearly communicate their limitations so you can make informed decisions.

Yes. Fixed-price, well-scoped projects are our primary model. After an initial assessment, we define a clear scope, deliverables, timeline, and budget. For larger or ongoing forecasting programmes, we can combine fixed-price phases with selective staff augmentation of senior experts.

Absolutely. Our “project rescue” capability extends to data and forecasting initiatives. We can audit your current models, pipelines, and infrastructure, stabilise what is salvageable, and redesign what is not. The goal is always the same: deliver a forecasting capability that your organisation can rely on.

Case Studies