Building data pipelines can feel like solving a puzzle, with pieces scattered across tabs, tickets, and different people’s heads across your organization. You need clean, governed outputs on a tight deadline, but instead you’re bouncing between SQL, documentation, and lineage to reconstruct how things fit together. It’s still technically productive work, but it doesn’t always feel like progress.
Coalesce Copilot changes that dynamic by introducing a helpful AI assistant into your Coalesce workspace that understands your environment and helps you turn intent into working pipelines. Describe what you want, and Copilot helps you build it faster while keeping your standards and trust intact.
Because Copilot lives in Coalesce, the results land where your team already collaborates. Changes are auditable, documentation stays with the work, and your catalog reflects what actually happened. This means you reach production faster while cutting down on rework. Any risk stays in check because contracts, approvals, testing practices, and impact analysis are part of the process. Outputs are documented, discoverable, and easy to trust.
Copilot complements the AI assistant embedded within Coalesce Catalog, each addressing different needs in the data lifecycle with AI. Copilot lives in the build path, turning intent into governed transformations, drafting SQL, scaffolding nodes, and preserving lineage under your existing roles and audit. Catalog’s AI assistant lives in the discovery path, letting anyone ask natural language questions about definitions, lineage, ownership, and usage, and returning answers grounded in the same metadata.
Because both draw from one source of truth, changes made with Copilot appear instantly in Catalog with accurate documentation and context, so business teams can self-serve insights while data teams stay focused.
Changing the game for day-to-day development (and more ambitious projects)
The early phase of any project can be slow, starting with setting up patterns, rewriting familiar logic, and reconstructing lineage. Copilot accelerates the initial development phase by drafting staging, dimension, fact, and view layers from plain language so you can review an initial model rather than starting from zero with a blank canvas. And when you need to adjust an existing graph, Copilot plans the steps and executes safely within your guardrails.
When it comes to more daunting projects like migrating from legacy systems, Copilot cuts migrations from multiple months to weeks while significantly reducing manual rework. By parsing legacy code with LLM-driven translation, Copilot accelerates pipeline rebuilds with full context and helps you build an upgraded and AI-ready data foundation, not just brittle pipelines that have been ported over.
“Using AI Copilot in Coalesce, we reduced the overall completion time for a recent complex project by about 30%.”
— Sarah Tolfrey, Head of Data Operations, Jaja Finance
The best way to build an AI-ready foundation and a successful data program? With AI
Jaja Finance is a digital-first, ethical, insights-driven lender in the U.K. with a focus on using AI and technology to better understand and engage with customers. Data operations plays a central role in their customer-first approach, and the data team leans on Coalesce to bring transparency to their daily operations. Copilot has become a valuable resource, simplifying and accelerating dev time on a complex project when the team was still new to Coalesce. “This was a very big project for us as a data team, and that was a huge gain—more than I was expecting to get from a first attempt,” says Sarah Tolfrey, Head of Data Operations. In addition to Copilot’s productivity gains, the team reports they can commit to 5x faster delivery on structured and unstructured data and have seen a 47% reduction in compute costs on their data models.
Take off with Copilot today
Copilot is generally available. Contact us to see Copilot live, or reach out to your Coalesce account team to get started.