(Re) Introducing Anaconda Services

Matt Thornell

A black background with a green ombre diagonal. At the top right of the image the blog title: "Reintroducting Anaconda Services. Below that, surrounded by a bright green frame: "Kickstart AI projects with dedicated help from the Anaconda Services Team"

Since our founding in 2012, Anaconda has completed service projects for hundreds of clients. In fact, we started as a services-only company for the first couple of years, as we built out our Anaconda software product offerings such as the Anaconda repository. So in some sense, we have been a services company longer than we have been a software company.

Fast forward to today, and while our services-to-software revenue mix has flipped dramatically, we retain a core team of data science, machine learning, and AI experts dedicated to providing exceptional client-focused work. Most of our current projects center on a few key areas: 

  • Kickstart Services: These are 100-hour time boxed engagements for specific deliverables, such as data visualizations, Jupyter notebooks, APIs, executables, deployed applications). These services are great for exploration that can lead to beneficial large-scale change in how your organization works.
  •  Open-Source Package Development: Anaconda experts created and maintain a number of open-source software (OSS) packages, like Conda, Panel, Numba, HoloViz, Jupyter, PyScript, and BeeWare and others. Sometimes a business use case will fall just outside a package capability, and an organization turns to Anaconda to develop solutions to directly address their use case, solving their needs and contributing back to the community at the same time.
  • Hardware Platform Advisory: Manufacturers of chips or computer systems have recognized the importance of enabling Python users on their products. If it’s not supported, easy to use, or faster than the status quo, new users won’t make the switch or the purchase, so we work with manufacturers to make Python easy to use and performant on that platform.

Anaconda is now focused on delivering the Operating System for AI, and this means enabling a wide range of use cases for our clients and building on new core capabilities of our team. Along with all of our previously offered services, we’re excited to add the following capabilities:

  • Custom LLM and ML Annotation: You can build on top of large language models (LLMs), such as ChatGPT, Llama, Bard, and others with our experts and your data. We can also create easy-button user interfaces (UIs) for labeling and automation, even for complex data types, enabling your tools to employ ML at scale.
  • Spark or SAS Migration to Python: Convert legacy code to repeatable AI-ready models and packages, opening further enhancements from the Python and ML/AI ecosystem.
  • Python to Snowflake Snowpark Integration and Migration: Move your models into the world’s most popular database, leveraging Anaconda’s partnership with Snowflake and  the help of our experts, and ensure that your workflow is defined and repeatable for future use.
  • A host of other services are available (see the bottom of our Services page for a full list), including model management deployment, Kubernetes or Dask cluster management, and working with geographic and geospatial data.

And some of our favorite offerings that you may already know about:

  • Performance Python: Make your Python code run faster and scale up to much larger datasets using the right data structures, algorithms, libraries, and compilers to support efficient, scalable distributed computing.
  • Pipeline Workflow: Coordinate machines (including GPUs) and jobs, including directed acyclic graphs (DAGs), integrated with your in-place software or OSS packages.

Anaconda’s professional services team focuses on enabling you and your team to achieve your business goals, as memorialized in one of services pillars: To enable the client to produce their own artifacts, workflows, and services in the future. 

Anaconda focuses on the tools to enable and empower, while our customers are the masters of their data and their domains. To achieve this, we leverage open-source packages (non-siloed code), setting up repeatable workflows, and empowering your users with training notebooks and sessions. While we love our customers and the work we’re able to complete for them, the best engagements happen when we empower clients to self-serve.

As we continue to expand our offerings, we look forward to tackling new problems with new and existing customers and are always open to taking on novel problems and use cases.

If any of these projects or services are a fit for your needs, please reach out to us for more information. 

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