Solving Technical Debt in the Energy Sector’s Machine Learning Systems

If you would like to begin evaluating your AI/ML needs, our Engineers are here to help.
Hidden Technical Debt in Machine Learning Systems: Google, 2015

The most mature AI/ML companies have spent years building their own AI layers such as Uber’s Michelangelo, Google’s Tensorflow TFX, and Facebook’s FBLearner. This infrastructure enables them to deploy AI at scale and is vital to realizing AI’s potential impact. Algorithmia’s Enterprise Services provides that infrastructure for your organization. We help you leapfrog the infrastructure development phase and enable you to deploy your AI, at scale.

"As someone that has spent years designing and deploying Machine Learning systems, I'm impressed by Algorithmia's serverless microservice architecture – it's a great solution for organizations that want to deploy AI at any scale."

VP of Engineering, Artificial Intelligence at Google

Our engineers have focused on developing the capabilities that will enable you to finally see the ROI on AI. The AI layer is:


Every algorithm can be shared across your organization, according your permissions, and can be run with a simple REST API call—eliminating duplicate efforts.


Our serverless layer automatically scales up or down to meet fluctuating throughput needs and reduce costs.


Our AI layer is data agnostic, stack agnostic, and supports the 7 most prevalent coding languages eliminating any interoperability challenges. By also being cloud agnostic, we empower you to switch vendors at will while maintaining operability.

Regulation Compliant

We specialize in operating in highly regulated industries and meet the most stringent government regulations.

"Algorithmia empowers U.S. Government agencies to rapidly deploy new capabilities to the AI layer. The platform delivers security, scalability and discoverability so data scientists can focus on problem solving."

Partner at In-Q-Tel

The energy sector faces a unique set of challenges when developing the appropriate infrastructure for AI and Algorithmia is positioned to help solve these challenges.

Migrating to the Cloud and Hybrid Clusters

Our cloud agnostic processes and scalable and compatible AI layer pulls models and data from any cloud or combination of sources. This can help analyze the benefits of a supergrid, unite data from various regions, and ensure your models are running with all relevant data. The serverless AI layer allows you to automatically scale in response to fluctuating demand thereby optimizing your hybrid clusters operations.

Moving deep learning to production

Our serverless layer lets you horizontally deploy and scale deep learning models over GPU clusters. The discoverable algorithm registry and automatically generated REST APIs allow data scientists to quickly find, run, and build on existing models. This gives you the compute power to regularly train and refine your models, such as demand forecasting and solar/wind energy production forecasting.

Streamlining AI enabled solutions

Algorithmia’s universal REST APIs, and compatible and composable AI layer allow each of your AI enabled solutions to be run by a universal REST API call. This allows you to integrate new algorithms and expand their impact throughout the organization.

Migrating to modern technology stacks

Algorithmia’s compatible and composable AI layer allows your data scientists to work in Java, Scala, Python, Ruby, NodeJS, Rust, or R. The AI layer is stack agnostic and can be compatible with any configuration you choose to work with.

Adapting to Domestic and International Regulations

Algorithmia’s lineage, discoverability, API generation, security expertise, and advanced monitoring will keep you compliant with any regulations and can be updated in real time. Our advanced monitoring will allow you to monitor cluster-wide health metrics and user-specific audit trails, facilitating compliance with various regulations around the world.


How do you measure success?

Algorithmia provides:
  • Data about your data with a metric based dashboard for your entire AI portfolio.

Data Scientists

How do you collaborate and innovate on AI within your organization?

The AI layer:
  • generates automated versioning and scaling.
  • allows for seamless interoperability & reusability across technology stacks.
  • generates a one click REST API call for every algorithm

IT Engineers

How do you efficiently run and monitor your ever-evolving infrastructure?

Serverless microservices:
  • reduce data center costs with flexible scaling.
  • enable customizable authorizations and security monitoring.
  • create algorithm versioning.

For more information regarding AI challenges and how Algorithmia can help please check out some of the latest research below as well as our technical FAQ and blog posts regarding developing AI platforms.