The team that makes your data AI-ready.

"Without this context we would have spent months/years manually updating the metadata required for these efforts and would not let us move at the speed we can now."

Bernie Daley

Director of Data Management, Nelnet Servicing, LLC

"With single-digit hours of effort from our team, we were able to accomplish work that would have taken months for a larger team to finish — and realistically, we likely would not have ever started it."

"If we tried to map and document this data estate manually, it would have taken years for an entire team. I joked internally that I'd be ready to retire before we finished. Automation turned a multi-year hurdle into an immediate win."

"Our pilot proved that automated context drafting makes our entire documentation process infinitely more efficient. The results show that it is significantly faster for our producers to review and fix an existing draft than to write one from scratch."

"This serves as an excellent accelerator to get critical governance conversations going across the company. It instantly provides rich content for our teams to discuss and refine, rather than leaving them staring at empty pages."

"This completely jump-started the population of our descriptions, allowing us to permanently overcome the 'cold start' issue that stalls out most traditional enterprise governance initiatives."

"The ability to quickly prefill initial descriptions and READMEs is extremely beneficial because taking that first manual step is always the most time-consuming. Once the baseline is established, you can focus human energy strictly on refining your highest-value assets."

"I expected boilerplate — instead, it inferred business context I never explicitly provided, correctly describing how an asset fit into our customer journey just from column names and lineage. That's when I realized this was knowledge synthesis, not just documentation."

Swatilekha Saha

Data Architect, DAT Freight & Analytics

"The output shifted from solid generic descriptions to something that felt like it had been written by someone who understands our business. That's the moment I stopped thinking about this as a time-saving tool and started seeing it as a strategic capability."

Izabela Wilczynska

Data Governance Manager, PayU

"It picked up on the nuance of our underlying database structures, successfully defining audit columns and system attributes that human stewards usually ignore out of fatigue. It proved we can move past line-by-line micromanagement."

"We have highly custom, specialized domain terminology that standard dictionaries completely miss. The system parsed our query behavior and accurately translated that unique jargon right out of the box, without heavy manual training."

"Operating in heavy manufacturing means our data carries highly specific operational context. The agents interpreted and documented these industry-specific assets flawlessly, showing a deep understanding of our business logic without manual fine-tuning."

"The specialized documentation and structural context that the agents generated were surprisingly accurate. They captured our data architecture so cleanly that, with only a few minor corrections, they were completely production-ready."

"The depth of the context it pulled automatically was incredible. It successfully mapped out highly complex, specialized tables that are notoriously difficult to track manually, giving us a level of baseline precision we couldn't maintain on our own."

"We were stunned with the quality of the content that was produced by these AI agents. We were perplexed. How could it create such high-quality context from lineage, from SQL logic, from dbt logic. It really shows how much business information is hidden in the metadata following a lineage that we simply cannot see with human eyes. But agents pick it up, consume it all, and spit it out in an organized way."

Kenneth Jebjerg

Head of Data Engineering

"The AI enables us to do things we wouldn't be able to do otherwise. I don't know if we would ever get to this level of quality with descriptions. Getting a consistent definition when different lines of business describe things differently? Everyone ends up learning more about the data than they knew."

Cody Brees

Data Governance Lead, The Bancorp

"This provided an exceptional opportunity to generate deep technical insights via SQL Intelligence that would be incredibly difficult and labor-intensive to gather manually across our core data pipelines."

"We put the automated descriptions in front of our most rigorous enterprise data gatekeepers, and it cleared an 80% accuracy baseline immediately. It proved that automated context can meet the strict standards of a global corporate data office."

"Instead of just filling in blank text boxes, the system decodes the inner logic of our data through actual usage footprints. It turns documentation into a live, continuous feedback loop that evaluates our overall platform health."

"By reverse-engineering raw query footprints, the system automatically captured the exact business questions our users naturally ask. It understands human intent far better than a static data dictionary ever could."

"The natural language questions surfaced by the SQL Intelligence feature were a major milestone for us. Seeing the machine reverse-translate complex SQL queries back into clear, user-friendly business logic was highly impressive."

"Once we showed this to our BI team, you could see the attitude shift — from 'another tool, more work' to excited to get in and start looking around. The instant value just changed everything."

Sayali Avalakki

BI & Analytics Lead, Brightspeed

"This system gives us an incredibly solid foundation to build our new data governance culture. By automatically generating initial context, it completely eliminates the 'blank page effect' that stops users from adopting tools."

"This pilot gave our team clear reassurance that a massive portion of the administrative heavy lifting that used to derail data governance can now be completely and safely automated."

"We completely bypassed the uphill battle of chasing down busy business analysts for definitions. We generated a highly accurate, reviewable baseline of our data estate in an hour — a process that normally takes weeks of corporate coordination."

"This successfully moves the organizational bottleneck from motivating busy stewards to document, to building efficient human-in-the-loop review processes. It saves time on manual creation and focuses energy on strategic verification."

"At the start of any data catalog journey, getting definitions for physical data is a massive hurdle. These agents give us a great starting point to engage business users, shifting their role from writing definitions to simply reviewing them."