Why Tovix
AI systems now interact directly with customers, employees, and users. When those interactions fail, responsibility does not belong to the model. It belongs to the organization running it.
Tovix helps companies understand how AI behaves in the real world, where outcomes, trust, and compliance actually matter. Designed for the teams accountable for AI outcomes. We focus on what happens in real conversations, not what models promise in isolation.
Tovix changes that.
Tools explain systems. Accountability explains outcomes.
Optimized for debugging systems, not owning outcomes
Built for leaders accountable for safety, trust, and ROI
Tovix extracts the factual claims your AI makes and ranks them by repeat risk across real interactions.
Teams verify the few claims that matter most against their source of truth and eliminate recurring errors.
Dev tools tell you if the AI ran. Tovix tells you if the AI did the right thing.
AI interactions only make sense in context. Tovix identifies why users reached out in the first place, then evaluates whether the interaction actually delivered the intended outcome.
This shifts risk scanning from "Did the model respond?" to "Did we actually help?"
Not every failure is obvious. Some interactions appear successful but quietly create risk, confusion, or compliance exposure. Tovix highlights the conversations where human judgment is required.
Tovix makes judgment failures visible, not just accuracy errors.
Answers alone do not determine success. Tovix evaluates conversations based on outcomes, customer experience, and downstream impact.
Leadership-grade risk scan of behavior, reasoning, and results.
AI systems often appear confident even when information is incomplete or incorrect. Tovix surfaces disagreement between what the agent says and what is actually true or expected.
Those decisions become ground truth, improving agents, prompts, policies, and future risk scans.
The result is a scan loop leaders already understand.
Tovix helps companies scale AI without giving up accountability, so you can trust how your agents behave when it matters most. Designed for the teams accountable for AI outcomes.