--- title: "Introducing SD Labs: what Smart Data people build in between" url: https://www.smartdata.net/blog/introducing-sd-labs description: "SD Labs is where Smart Data engineers share what they build between client projects: internal tools, open source, side projects and talks." source: "Smart Data (smartdata.net). Markdown copy of the page; the HTML page is canonical." --- Announcement # Introducing SD Labs: what Smart Data people build in between Smart Data October 28, 2026 3 min read On this page - What’s on it - Why we’re sharing it - How it stays current - Take a look Share A guide from Smart Data The AI Enablement Guide Where your data stands, and which AI use cases it can support today. [A guide from Smart Data The AI Enablement Guide Where your data stands, and which AI use cases it can support today.…](https://www.smartdata.net/ai-enablement) SD Labs is now live at [labs.smartdata.net](https://labs.smartdata.net). It’s where we share what Smart Data people build between client projects and on their own time: internal software we now run the company on, open-source projects, side projects someone couldn’t stop thinking about, and the talks our engineers give. Some of it is internal Smart Data work and some of it belongs to the people who built it, but all of it comes from people in our ecosystem. There are 15 projects on it today, and more on the way. ## What’s on it The projects fall into four kinds, and you can filter by each on [the work page](https://labs.smartdata.net/work/). **Built here.** Tools we built for ourselves and now use every day. Our timekeeping, invoicing and project costs run on [apps we built ourselves](https://labs.smartdata.net/work/time-and-ops-apps/), written mostly by AI coding agents with a team around them. Our recruiting paperwork runs on an automation stack where you drag a candidate card and the documents send, sign and file themselves. **Open source.** Projects anyone can use. [Smartfire](https://labs.smartdata.net/work/smartfire/) is a self-hosted workspace where people and AI agents share rooms, threads, boards and huddles, and our own team chat is migrating to it. ETLPlus is a Python ETL package and command-line tool, MIT licensed and on PyPI. **Side projects.** Things people build because they want to. Ace Trace turns a short phone video of a tennis stroke into a technique report a coach can use. [MockingBoard](https://labs.smartdata.net/work/mockingboard/) is an NFL Draft site where fans run mock drafts and write scouting reports, and Smart Data’s own fantasy football league runs on its fantasy site this season. **Talks.** What our engineers present at conferences and community events, from three questions to ask before you build AI on a dataset to schema-grounded SQL generation for enterprise analytics. Our medallion architecture session at [Taste of IT on November 18](https://www.smartdata.net/events/taste-of-it-2026) is on there too. ## Why we’re sharing it Most of what we do for clients stays private, and it should. That makes it hard to show how our people work, and Labs fills that gap. The engineers who build data platforms and AI systems for clients are the same people who build these tools, and the habits carry over: start from the real workflow, keep the data trustworthy, and own what you build. It also says something about where software is heading. Several of these projects replaced software we used to pay for. With AI coding agents doing much of the typing, a small team can now build and run tools shaped exactly to how a company works. We’re using that on ourselves first, and it changes the build-or-buy question for a lot of teams. If that’s a conversation you want to have, our page on [how we build with AI](https://www.smartdata.net/services/how-we-build-with-ai) is a good place to start. ## How it stays current Projects get added as they ship, and the [Lab log](https://labs.smartdata.net/log/) shows what changed and when, newest first. Each project page says what it is, how it was built and who it’s for, with a link to the code where the code is public. You’ll also meet a small pixel character around the site. He shows up on project cards and in the launch video, and he’s the closest thing Labs has to a mascot. ## Take a look Start at [labs.smartdata.net](https://labs.smartdata.net) and click into anything that looks interesting. If you’re an engineer who likes building this kind of thing, we’re [hiring](https://www.smartdata.net/work-here). And if you see something you’d want built for your team, [let’s talk](https://www.smartdata.net/contact-us). ## Questions this raises ### What is SD Labs? SD Labs (labs.smartdata.net) is where Smart Data shares what its engineers build between client projects and on their own time: internal tools the company runs on, open-source projects, side projects and conference talks. ### Is SD Labs a separate product or company? No. It is part of Smart Data. Nothing on it is sold as a product; it shows the work of the same people who deliver data platform and AI projects for clients. ### Can I use the open-source projects? Yes. The open-source projects, such as Smartfire and ETLPlus, are public, and each project page links to its code and license. ### Can Smart Data build something like this for my team? Yes. Several Labs projects replaced software Smart Data used to pay for. If your team is paying for software it could own, talk with us about what that would take. Keep reading ## Related posts ### Smart Data at Dayton AI Day 2026: Getting Verifiable Answers Out of Enterprise Data Chris St. Amand · Aug 18, 2026 [Smart Data at Dayton AI Day 2026: Getting Verifiable Answers Out of Enterprise Data](https://www.smartdata.net/blog/dayton-ai-day-2026) ### Smart Data Joins the Databricks Partner Network Chris St. Amand · May 28, 2026 [Smart Data Joins the Databricks Partner Network](https://www.smartdata.net/blog/smart-data-joins-the-databricks-partner-network) ### Smart Data at Taste of IT 2025: Hype or Help? Real-World Lessons from Applying AI Chris St. Amand · Oct 29, 2025 [Smart Data at Taste of IT 2025: Hype or Help? Real-World Lessons from Applying AI](https://www.smartdata.net/blog/taste-of-it-2025) Go further ## Not sure your data is ready for AI? The guide covers data maturity, use cases by readiness level and industry perspectives, so you can see where your platform stands before you pick a model.