You will get Predictive AI Systems for Demand Forecasting and Time Series Analysis
Project details
Forecasting shouldn’t be guesswork —> it should be a strategic advantage. This sprint delivers custom-built forecasting systems that transform your historical data into clear, reliable predictions for demand, sales, and inventory planning.
I combine robust statistical techniques such as ARIMA, SARIMAX, ETS, and TS-PCA with advanced deep learning models including LSTM, 1D CNN Scan, and Temporal Fusion Transformers. The result: high-precision forecasts that adapt to seasonality, trends, and real-world variability in your data.
Deliverables include:
• A transparent accuracy and model comparison report (MAPE, RMSE, MAE)
• A forecast visualization dashboard for decision-making clarity
• Actionable insights on demand drivers and optimization opportunities
• Recommendations for automation or integration into your analytics pipeline
This sprint gives you more than numbers —> it delivers a decision-ready forecasting framework that evolves with your data and provides a measurable edge in efficiency, cost savings, and market responsiveness.
I combine robust statistical techniques such as ARIMA, SARIMAX, ETS, and TS-PCA with advanced deep learning models including LSTM, 1D CNN Scan, and Temporal Fusion Transformers. The result: high-precision forecasts that adapt to seasonality, trends, and real-world variability in your data.
Deliverables include:
• A transparent accuracy and model comparison report (MAPE, RMSE, MAE)
• A forecast visualization dashboard for decision-making clarity
• Actionable insights on demand drivers and optimization opportunities
• Recommendations for automation or integration into your analytics pipeline
This sprint gives you more than numbers —> it delivers a decision-ready forecasting framework that evolves with your data and provides a measurable edge in efficiency, cost savings, and market responsiveness.
AI Development Type
Deep Learning, Model TuningAI Tools
Amazon SageMaker, Keras, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$595
|
Standard
$1,250
|
Advanced
$2,400
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 10 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | - | - | |
Detailed Code Comments | - | - | |
Knowledge Graph | - | - | - |
Model Documentation | |||
Ontology | |||
Source Code | - | ||
Taxonomy |
Optional add-ons
You can add these on the next page.
Additional Revision
+$225Frequently asked questions
About Rodrigo
Senior Data Scientist & AI Founder
Tokyo, Japan - 7:35 am local time
Over the past decade, I’ve co-founded and led AI ventures across Europe, the US, and Japan, building systems that search smarter, predict demand accurately, and personalize user experiences.
My expertise focuses on three applied AI pillars:
1. RAG & LLM Systems – Architecting retrieval-augmented generation pipelines that make enterprise knowledge instantly accessible, reducing manual search time and LLM inference costs.
2. Time-Series Forecasting – Designing demand prediction and stock optimization models for retail, logistics, and energy, driving efficiency and reducing waste.
3. Recommendation Engines – Delivering personalization systems that increase engagement and retention for media, SaaS, and e-commerce platforms.
Deep technical understanding (Python, PyTorch, TensorFlow, Qdrant, ColBERT, AWS/GCP) with business acumen from years of founding and scaling startups, fridging data science and product strategy to turn AI into tangible ROI.
Currently, Co-Founder & CTO of WhiteNarwhal Japan K.K. / Ikkaku AI Lab, an applied-AI company and incubator that helps startups and enterprises deploy production-ready AI systems; and of our first AI Lab spin-off company: Monju AI, a document-centered workspace powered by retrieval and multimodal AI.
Steps for completing your project
After purchasing the project, send requirements so Rodrigo can start the project.
Delivery time starts when Rodrigo receives requirements from you.
Rodrigo works on your project following the steps below.
Revisions may occur after the delivery date.
Data Review & Preprocessing
Check data quality, trends, and structure. Handle missing values and outliers.
Model Design & Training
Choose best-fit models (Prophet, ARIMA, or Neural Networks) and train.