Founded in 2013, Lightricks is a global leader in creativity tools, with cutting-edge apps like Facetune, Videoleap, and Photoleap. In 2022, Lightricks acquired US-based Popular Pays and has continued to gain significant traction with products like AI-powered LTX Studio and the release of its video generation model LTXV. Backed by $130M in Series D funding, the company has accumulated over 730 million downloads worldwide.
Lightricks uses dbt for data modeling and transformation, alongside Tableau and ThoughtSpot for business intelligence, and Slack for team communication. Before Foundational, their workflows relied on manual processes for tracing data lineage.
As Lightricks expanded their suite of AI-powered creative apps, the company’s data infrastructure and analytics needs grew increasingly complex. With a global workforce of around 550, Lightricks relied on its data team of 30 to drive critical business decisions and empower product innovation at scale. Eyal El-Bahar, VP of BI & Analytics, and BI Team Lead Ori Avner realized they lacked the tools to trace data lineage, understand database field logic, or implement fixes efficiently — creating bottlenecks that made it difficult to maintain efficient workflows.
Lightricks used a modern data stack, including dbt and Tableau. The BI team also relied on manual lineage processes and Slack for communication, leading to missed messages and delayed responses. While dbt handled table-level transformations, the lack of column-level lineage made it difficult to track changes precisely, forcing the team to manually verify impacts before deploying updates.
Tracing data lineage was labor-intensive — figuring out the root cause of issues required sorting through legacy pipelines and old code. Without field-level lineage capabilities, developers often spent hours manually tracking downstream issues. “It could take quite a while to trace back to the source of a field, sometimes as many as 10 steps,” says Ori.
Changes made in one repository often caused downstream issues for teams working on other repositories. For example, when building infrastructure for the data science team, who work in a separate repository, changes in one repo broke workflows in another. This lack of visibility into cross-repo dependencies sometimes disrupted production systems, creating additional headaches for Lightricks’ BI team. All these challenges, combined with dbt’s data lineage limitations, required an efficient data management solution.
That’s when Lightricks joined Foundational.
“Mistakes happen when it comes to human dependency and human error. We needed a platform like Foundational to avoid issues by automating this process.” - Ori Avner, BI Team Lead, Lightricks
Foundational’s fully automated, real-time solution provides column-level lineage and shift-left data quality across Lightricks’ entire data ecosystem, including dbt and Tableau. Eyal and Ori now have a clear, continuously updated view of upstream and downstream dependencies at build time, ensuring every transformation and data flow is tracked and discoverable across all repositories.
Lightricks’ developers no longer waste time on manual impact analysis or chasing down Slack messages. Foundational inspects every pull request automatically for code changes and surfaces a full impact analysis before merging — preventing data issues before they happen and reducing time spent debugging.
Legacy pipeline headaches and the uncertainty of old code are gone. With Foundational’s data governance features — such as automated column-level lineage and discoverability across pipelines — the team quickly pinpoints the origin and usage of any field. It’s now easier and faster to resolve issues, roll out fixes, and maintain compliance.
Another breakthrough is Foundational’s ability to make cross-repo data dependencies visible and manageable. This allows Lightricks to identify downstream impacts across their BI and analytics stack and prevent cross-team workflow disruptions.
By automating lineage tracking, impact analysis, and data contract enforcement across their analytics stack, Foundational has enabled the Lightricks team to resolve data issues faster and confidently scale workflows.
“Before Foundational, one change in our repo could break the data science team’s production overnight — because we simply couldn’t see the downstream impact.” - Ori Avner, BI Team Lead, Lightricks
As an early design partner, Lightricks has worked closely with Foundational, providing feedback and suggesting new ideas to enhance the platform. With Foundational’s automated lineage tracking, the Lightricks team confidently makes changes without worrying about downstream dependencies, leading to:
Foundational is currently working on integrating ThoughtSpot for Lightricks, an AI-powered BI and analytics platform that will enable instant, search-driven insights. Ori is also excited about the new cost optimization feature, which will help Lightricks spot unused pipelines and tables — freeing up time and cutting unnecessary costs.
“Our ongoing collaboration with Foundational will help us solve our pain points and make our workflows more efficient.” - Ori Avner, BI Team Lead, Lightricks
