Build robust forecasting & ML solutions
We bring a wide variety of experience in machine learning and statistical modeling to solve unique forecasting challenges.
Most forecasting models fail because they're built on generic assumptions or use out-of-the-box tools that don't fit the problem. We develop custom models that leverage the right tools and technologies for the task at hand.
Learn how we built a markov chain funnel forecast model to simulate daily conversion behavior
The big picture
Forecasting is more than a model
We don't just build models, we build and deploy production-ready forecasting systems that integrate with your stack. From data ingestion to transformation, modeling, deployment, and testing we handle the full ML lifecycle.
- Data Ingestion
- One of the biggest challenges to forecasting is often data ingestion. Ensuring that data is aggregated and available is fundamentally a data engineering problem.
- Model Development
- Our experience in a variety of different forecasting techniques allows us to recommend a solution that balances accuracy with robustness.
- Performance Evaluation
- Rigorous backtesting and validation to ensure model accuracy. We measure and report forecast error so you know exactly what to expect.
- Production Deployment
- Models deployed to your cloud environment with automated retraining pipelines so forecasts stay accurate as your business evolves.
- Testing & Reporting
- No system is expected to run perfectly forever. We focus on integrating acceptance tests and output reporting into all of our models to proactively flag the need for maintenance or improvement.
- Documentation & Training
- A project isn't complete until it's documented and offboarded. We place a high level of importance on thorough documentation and knowledge transfer as part of our work.
Need forecasting expertise?
Let's discuss your forecasting challenges and build a custom solution together.