Frequently Asked Questions

There is no "typical" engagement. Team d²l customizes services based on where clients are in their data journey. The consulting team is handpicked for each engagement, as each member of Team d²l has unique expertise.Services often include:Design and implementation of data collection infrastructure (e.g., app data ingestion, text scraping, lead generation forms)Automation of data processing, transformation, and warehousingOptimizing data storage for process efficiency - anything from contact data in a brand new CRM to millions of rows stored on a cloudDesigning dashboards and reports with guidance on identifying key performance indicatorsProviding executive-level insights from complex data analysisTraining, documentation, and hiring supportFor specific examples, see Project Examples on the Consulting Services page.

Alkemy started as a structured framework designed to reduce the common risks in machine learning (ML) projects - things like unreproducible results, fragile pipelines, and messy code. Until recently, it was primarily a tool for Team d²l to use across consulting engagements to support consistency, reliability, and scale. Now, as coding agents become the norm for engineering teams everywhere, we see these ML project issues increasing in both volume and severity. Team d²l has seen first hand that AI can build reliable ML projects with the help of Alkemy.

Alkemy is a structured operating layer that makes general-purpose AI coding agents dependable for machine learning (ML). It integrates with the coding agent you already use and gives every ML project the same structure: a standard layout and a fixed sequence of steps covering datasets, experimentation, validation, deployment, and ongoing operations.The agent writes the code; Alkemy ensures it follows the right steps in the right order. This same structure allows agents to execute machine learning operations (MLOps) reliably - connecting the model to live data and scheduled runs, and tracking versions so you always know which model produced which result.

Alkemy isn't another platform to adopt; it integrates with the AI coding agent your team already uses, helping you discover meaningful patterns in your data and turn them into actionable predictions.Integrating Alkemy into an existing engineering team is quick and straightforward. If you're new to modeling, Alkemy offers a machine learning (ML) tutorial to help you build your first model, along with a structured framework that helps ensure agents follow critical modeling steps. If you're an experienced modeler, you'll see ML projects move faster than ever - less boilerplate code, compatibility with any ML library, and the ability to deploy the same model you tested.Beyond building models, Alkemy supports ongoing machine learning operations (MLOps). Getting a model into production and keeping it accurate can often take a dedicated engineering team. Alkemy handles that operational work so that a small team can deliver ML projects faster and with greater confidence.

You can familiarize yourself with Alkemy and get up and running with an initialized project within a couple of hours.

Alkemy has been applied to a wide variety of predictive modeling scenarios including website analytics, demand forecasting, dynamic pricing, stock trading, prediction markets, text classification, sentiment analysis, and much more.Alkemy provides a broadly applicable framework that can support predictive use cases across industries.  If you provide the data and the domain expertise, Alkemy will help you produce reliable models.

With Alkemy and your preferred AI coding agent, the most valuable skill you bring to a machine learning (ML) project is knowledge of your business and its data.If you're new to ML, Alkemy's embedded tutorial walks you through a real-world example using public data. When you're ready to work with your own data, Alkemy gives your agent a structured path to build and test your first model. All you need to get started is a clearly defined problem and an understanding of your data.Experienced technical users can take Alkemy even further. If you're comfortable with Python, SQL, configuration files, and reproducible workflows using Git and DVC, Alkemy streamlines production packaging so you can deploy models faster.

Operating System: macOS, LinuxMemory: 16 GB RAM or higher

In short, no. Team d²l provides access to the latest release and a comprehensive developer site with key concepts, guides, technical references, installation instructions, and a hands-on tutorial to help you get started.Fill out the contact form to gain access and get started.

Our pricing is simple and predictable, with subscriptions based on the number of users and optional training packages. Visit the Alkemy page for details.