ASCEND

ASCEND by BenchSci is an AI-powered co-pilot designed for preclinical research teams in drug discovery. It combines BenchSci's Biological Evidence Knowledge Graph (BEKG) with neuro-symbolic AI to help scientists surface relevant evidence, assess project feasibility, and accelerate experiment design. By acting as a trusted research partner, ASCEND improves decision-making, boosts productivity, and increases experimental success by drawing on evidence across millions of data sources.

At the core of ASCEND and BenchSci's broader product suite is the BEKG — a living, unified map of biological insights and relationships built from publications, clinical trials, and datasets. This knowledge graph powers AI-driven reasoning, hypothesis generation, and automation across the preclinical R&D workflow, enabling scientists to cut through information overload and focus on breakthrough science.

What Makes the BEKG Unique

• Engineered for Trust: Built on advanced high-fidelity data extraction, delivering precise and reliable insights without the risk of hallucinations.
• Multi-Layered Biological Insights: Captures correlation, causation, and scientific methodology informed by biomedical evidence, omics datasets, and proven protocols and reagents.
• Foundation for Scientific Reasoning: Provides an expansive map of biological relationships grounded in ontological knowledge and biomedical research, with every connection traceable back to scientific evidence.
• Scientifically Validated: Refined through expert human-in-the-loop curation, ensuring unmatched accuracy, consistency, and confidence in every insight.
• Customizable: Seamlessly integrates with an organization's internal data to create a proprietary knowledge graph tailored to unique research needs.

Core Product Capabilities

• Co-pilot (ASCEND): Acts as a co-pilot for preclinical research by surfacing relevant evidence, assessing project feasibility, and accelerating experiment design to improve scientific decision-making and productivity.
• Co-scientist: Uses the BEKG as an evidence backbone to make scientific predictions and generate hypotheses. By applying logic, context, and domain expertise, it enables R&D teams to move from reactive evidence review to proactive discovery — uncovering novel insights, proposing testable hypotheses, and designing optimal studies with the right experiments and best reagents.
• Programmatic Access: APIs provide structured access to the BEKG, enabling dedicated AI agents to retrieve permissioned evidence and insights with speed and precision. MCP servers act as universal connectors, allowing AI agents to access authorized tools, APIs, and data to orchestrate complex tasks and adapt to diverse scientific use cases.
• Data Integration: A continuous feedback cycle flows evidence-backed hypotheses and strategies from the BEKG into automated lab platforms, runs experiments autonomously, and returns results to the BEKG to refine inferences and strengthen future insights — accelerating discovery and enhancing every step of the R&D process.

Automation and the Path to Autonomous Drug Discovery

• Transforms and automates repetitive but evidence-heavy tasks such as literature search, target due diligence, and experiment planning.
• Embeds automation across preclinical R&D so scientists can focus on innovation and breakthrough science.
• Helps organizations accelerate timelines, reduce costs, and lay the foundation for a faster, more effective, and more impactful future of life-saving research.
• Supports an agentic lab-in-the-loop model that continuously strengthens predictive power and moves toward fully autonomous drug discovery.

BenchSci's solutions are designed to integrate with both internal organizational data and external automated lab platforms, creating a flexible and intelligent ecosystem suited to the evolving demands of AI-powered pharmaceutical and biomedical R&D.