Reality before simulation
Customer facts, policies, tools, rights, and valid outcomes come from approved sources and qualified experts. Missing reality remains a blocker; the platform does not fill it with plausible industry lore.
About Gradia
The evidence layer for enterprise AI agents.
Start with evidence from an agent you already run. Gradia connects Guard, governance, evaluation, and Gradia Universes so you can inspect what an agent did, test it against approved work, and understand where it failed.
Workflow Observer brings permitted browser, desktop and service activity into one case. Review its history, approve the business rules and evaluation rights, then create an executable Universe where you can inspect an agent attempt and branch from a recorded checkpoint.
01 · Work
What the platform produces
A structured discovery process compiles approved expert reality into a versioned specification. The same contract drives custom universes, tasks, model runs, human review, failure analysis, benchmark maintenance proposals, training-ready exports when rights permit, and signed evidence that can be checked offline.
Worlds may also change while an agent works. Those changes are declared, controlled, replayable, and bound to before-and-after world roots so an interruption is evidence—not theatre.
02 · Standard
How Gradia works
Evaluation before promotion
AI can discover, propose, generate, and diagnose. A separate accountable human approves scope, releases evidence, or changes an operating benchmark.
Evidence before a headline
A result binds the exact task, world, model, scaffold, judge, runtime, and evidence used to produce it. Infrastructure failures and unassessable work are not counted as model failures.
03 · Team
The people building Gradia
Gradia is founder-led, combining applied AI research with more than a decade of enterprise production experience so pilots can move from expert reality to accountable production evidence.
Rudy Celekli
Founder & CEO · CTO · Research Engineer
Rudy built Gradia and leads product, engineering, and research. He has spent more than a decade taking applied AI from workflow framing through production, across analytics consulting, enterprise machine learning, and forward-deployed evaluation work.
04 · Company
Built with in Charlotte and SF
Gradia is being built between Charlotte and San Francisco, close to the enterprises putting AI to work and the researchers pushing it forward. We are starting with hands-on pilots because the details that matter live with the people who do the work. Our job is to listen carefully, build responsibly, and make what works easier to see.
The founder works directly across product, research, and pilot delivery. Specialists and qualified experts join each engagement when the work requires them.