Meet SAINT

Modular AI Architecture

Selectable analysis engines

A versatile library of modular AI models. From case prioritization support to targeted pattern recognition (for example H. pylori or spindle cell features), engines can be used individually or in combination to support existing tools or internal research workflows.

Longitudinal Discovery Support

Supports drug discovery research with models designed to work on longitudinal datasets, enabling exploration of potential biomarkers, cohort behavior, and observed risk patterns over time for research and pharmaceutical teams.

Built with pathology expertise

SAINT’s algorithms are developed in collaboration with board-certified pathologists and research partners, using expert-reviewed datasets and protocols to support rigorous research evaluation and study design.

WHY IT MATTERS

The Strategic Advantage

The Automated Truth Loop

Smarter AI, powered by Vertical Integration

Most AI models are trained on static datasets that may become outdated over time. Santovia takes a different approach. By integrating with the molecular LIS, SAINT can associate H&E slides with corresponding molecular results and related study data. This structured feedback framework supports continued model development within research environments.

INGESTION

Dual-Mode Processing
Prospective case review in the foreground, with background analysis used to refine models over time in research settings.

THE TRIGGER

The LIS Handshake
Molecular test orders can be linked with corresponding histology cases to support comparison and evaluation in research workflows.

THE OVERRIDE

Human-in-the-Loop
Pathologist feedback and corrections can be captured and incorporated into ongoing model development over time within research settings.

THE STRONGHOLD ENGINE

One platform. Two Missions.

Response Insights

Explore model-derived scores related to recurrence risk and treatment response within a research setting. SAINT surfaces patterns in pathology and associated datasets to support internal studies, scenario analysis, and multidisciplinary research discussion, including retrospective comparisons of treatment approaches such as FOLFOX vs FOLFIRI.

Trial enrichment and real-world evidence

Support trial and biomarker research by identifying candidate cohorts, including potential “MSS-hot” patterns that may not be captured by standard criteria. Outputs can be exported and combined with other study data to support evidence generation and trial design in research environments.

EVIDENCE, NOT ANECDOTES

Performance is evaluated against peer-reviewed markers and longitudinal study data, not slide screenshots.

Efficient Review

SAINT is being developed to support research grounded in peer-reviewed science and longitudinal datasets rather than isolated slide examples.

Biomarker Discovery

SAINT is designed to assist with case prioritization by identifying slides that may require closer attention while allowing clearly benign cases to be reviewed more efficiently within research workflows.

Longitudinal Insights

SAINT is being developed to support analysis of longitudinal datasets, enabling researchers to explore relationships between histologic patterns, treatment response, and patient outcomes over time.

VIEW STUDIES & DATA

SAINT is backed by world-class institutions

Developed in collaboration with academic and clinical research partners and supported by unique real-world data sources.

LEADERSHIP & PEDIGREE

One Platform. Two Critical Missions

Santovia Path AI was founded on a simple belief: artificial intelligence, when responsibly developed and grounded in research, can advance digital pathology analysis.

Built upon real-world data from a large healthcare network, Prima CARE, and developed in collaboration with leading AI research institutions in the United States, the platform reflects a commitment to scientific rigor, responsible development, and practical application.

The goal is not simply to build algorithms, but to develop analytical tools that support pathology research workflows and data exploration.

Santovia Path AI is guided by a collaborative team of AI scientists, pathologists, and healthcare leaders working together to advance computational pathology.

The initiative is led by Alexander Kouspakian, MBA, Chief Executive Officer, alongside Prof. Saeed Amal, Chief Scientific Officer, Prof. Gene Tunik, Dr. Jim Lu, Dr. Usama Fayyad, Scott Kilcoyne, Dr. Kabeer Shah, and additional collaborators in artificial intelligence and pathology research.

Together, the team is developing a platform grounded in partnership, transparency, and responsible scientific development.

The Longitudinal Data Platform.

Connecting clinical pathology data and research workflows to support oncology discovery and translational research.

Email: info@santoviapath.ai
Location: Boston, MA