AI & Machine Learning Services
It can be challenging to translate ideas into AI solutions without the full range of experience that a seasoned team like Blue Orange provides. Our team is here to help your business design and deliver true value from its AI Agenda.
The Blue Orange Approach.
Book a call
-
Use Case
We'll team up to map your business, find top-value uses, and identify key data.
Prioritization -
ML/AI
Validate the viability of the ML/AI solution through rapid prototyping.
Prototyping -
Generative
With expert input from our data platform solutions specialists.
AI Solutions -
ML Pipeline
Build out robust, repeatable machine learning pipelines.
Creation -
Production ML
Design a fitting ML architecture for your ecosystem, offering cost-effective scalability.
Architecture -
MLOps
Operate your machine learning system at scale.
Implementation
Data Science & AI with Databricks
Design and deliver your Data Science and AI solutions on top of the Databricks Lakehouse platform to take advantage of the streamlined, end-to-end data science workflow and scalable machine learning platform architecture. With Databricks, your Data Science team can spend less time worrying about data infrastructure, how to get their data, and how to translate their models into production and spend more time understanding the business problem and translating it into high-quality models.
Case Studies
Learn More
Frequently
asked questions
How long does a Machine Learning Proof of Concept Last?
While it generally depends on the scope of the POC, we try to keep ML POCs to 8 weeks.
What is included in a machine learning POC?
- Translate business use case to ML solution
- Exploratory data analysis
- Featurization
- Scalable model training and evaluation
- Model Tracking & Model Registry (Usually with MLFlow)
- Knowledge transfer
- Deliver a Working ML model, and documentation, and Identify of next steps
What is out of scope for a Machine Learning POC?
- Data integration, ETL, and data cleansing outside of what is needed for the featurization.
- Improving any existing benchmark models.
- Front-end applications.
- CI/CD pipelines.
- Infrastructure setup and configuration.