Trusted Data Lineage. Actionable Insights.
At TraceLine Solutions, we build AI-ready data foundations for Biotech and Life Sciences.
We turn fragmented research data into semantically enriched, machine-interpretable assets that reliably power predictive models, generative AI, and automated analytics.
By combining semantic data architecture, end-to-end lineage, and standards harmonization, we enable organizations to trust their data at scale, automate with confidence, and deploy AI without losing regulatory control.
Our Mission and Expertise
Our expertise in semantic data modeling, provenance, and harmonization builds AI-ready ecosystems that accelerate digital transformation across research pipelines. We help organizations standardize and contextualize data to support machine learning, generative inference, AI governance, and automated decisioning, while reducing compliance risk and enabling real-time insights.
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We deliver value through:
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Applying semantic data architecture and FAIR principles to ensure datasets are interoperable and trustworthy
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Integrating multi-study and distributed datasets to provide a unified, actionable view of complex research data
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Designing practical, workflow-ready solutions that fit seamlessly into existing enterprise operations
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Partnering with research consortia and biotech organizations to deliver reliable insights that accelerate decision-making
Our Core Services
Strategic Information Architecture Engagements
We design enterprise information architectures for AI-scale decision-making. By structuring data with explicit semantics, lineage, and shared meaning, we enable AI agents, machine learning models, and generative systems to operate reliably in highly regulated life sciences environments.
Semantic Modeling &
Standards Harmonization
We design and align semantic models, metadata structures, and controlled standards to enforce consistent meaning across studies, systems, and organizations. This semantic layer underpins metadata registries, catalogs, and harmonized standards, ensuring that analytical pipelines, machine learning models, and AI agents operate on unambiguous, reusable data as methods and technologies evolve.
Data Lineage, Provenance &
Trust Frameworks
We establish end-to-end data lineage and provenance across distributed data pipelines, making data context explicit, traceable, and auditable by design. These trust frameworks create the transparency required for explainable analytics, governed automation, and AI systems that can be confidently deployed in regulated life sciences environments.
Who we are
Dr. Selena Baset
Founder & CEO
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Selena Baset founded TraceLine Solutions to help life sciences and biotech organizations establish durable data foundations in environments where scale, regulation, and complexity collide. With over 15 years of experience spanning academia and industry, she designs semantic architectures and metadata systems that enable alignment across domains, platforms, and functions.
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Her approach combines systems thinking, deep semantic expertise, and practical delivery. Selena works with organizations to make data context explicit, unlock deterministic automation, and support advanced analytics through traceable, interoperable, and governance-aware information architectures.
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Get in Touch
Have a question or need assistance? Feel free to reach out to us. We are here to help you with any inquiries regarding our services or solutions.