VALTRIX
Audit-aware AI for scientific screening and materials discovery. Built for reproducible candidate prioritization and benchmark-governed evidence reporting.
AcuVizionAI builds reproducibility-first AI systems for scientific candidate prioritization. Its flagship platform, VALTRIX, helps R&D teams decide which materials or molecular candidates deserve costly validation.
VALTRIX is not presented as a finished enterprise platform. It is a benchmark-validated, early-stage scientific ML engine for screening workflows, reproducible evaluation, and partner-ready technical review.
One parent brand, one flagship product, and two supporting public-safe pages.
Audit-aware AI for scientific screening and materials discovery. Built for reproducible candidate prioritization and benchmark-governed evidence reporting.
A training-time meta-controller for curriculum and sampling decisions under audit constraints. The public page is patent-safe and intentionally non-enabling.
A separate browser demo showing how risk scores and evidence can be turned into human-readable investigation narratives. Not the VALTRIX product.
Kamran Soleimani is building AcuVizionAI in Belgium as an independent deeptech effort focused on audit-aware scientific ML, benchmark discipline, and reproducible decision infrastructure. Current work centers on VALTRIX for scientific screening and materials discovery.
AcuVizionAI also maintains confidential exploratory work in computational drug discovery and other high-stakes scientific screening settings. Details are not publicly disclosed; high-level technical briefings can be shared selectively under NDA.
Open to strategic pilot partners, research collaborators, non-dilutive funding conversations, and deeptech investment discussions.
Email: [email protected]
Website: acuvizionai.com