Partner Spotlight Series with CSols Inc. and ZONTAL – Exploring Scientific Data Platforms

In our first Fireside Chat Series with CSols Inc., we explored how organizations gain the most value when they are data-driven and have moved beyond siloed systems such as LIMS or ELN.

Throughout the series, we discussed how ZONTAL enables organizations unlock data across systems—supporting compliance, IP protection, and AI/ML enablement—for optimized and seamless data-driven efforts across research, operations, and innovation.

Part 1: Data Preservation

We opened the series by highlighting the role of digital preservation in supporting long-term data accessibility and scientific reproducibility. ZONTAL preserves raw data in immutable, vendor-neutral formats while enriching it with metadata and context. This modern approach enables organizations to maintain data integrity even as systems evolve, retire outdated infrastructure, and reduce total cost of ownership over time.

A shift to digital preservation is the modern approach to scientific data management systems. Explore how digital preservation future-proofs research data by ensuring long-term accessibility, reducing costs, and retiring outdated systems.

Part 2: IP Protection

ZONTAL demonstrated how scientific data platforms play a critical role in IP protection by ensuring data is preserved, searchable, and legally defensible. We shared examples of how ZONTAL recovered signed records that were previously inaccessible in legacy systems—showcasing the value of standardized data in audits and litigation. With full visibility across data producers and experiment histories, organizations can confidently protect valuable patents and respond quickly to external requests.

Learn how the inherent accessibility and searchability of a platform supports your intellectual property portfolio.

Part 3: Decommissioning Legacy Systems and System Rationalization

ZONTAL enables faster system decommissioning by ingesting and preserving complete datasets from legacy environments—without requiring full migrations. It supports rationalization efforts through real-time integrations, chemistry-aware searchability, and access-based controls. By transforming legacy and current data into a unified, human-readable format, organizations reduce reliance on obsolete infrastructure while improving accessibility and usability across teams.

Hear how decommissioning legacy systems can be done quicker than migration efforts without losing access to data or analytic capabilities across legacy and current data.

Part 4: Artificial Intelligence and Machine Learning

In the final session, we explored how standardized data enables true AI and ML readiness. While ZONTAL doesn’t create AI models, it prepares scientific data in a clean, consistent format that integrates seamlessly with third-party AI tools. By aggregating data from ELNs, instruments, and external systems into a single FAIR-compliant platform, organizations can streamline model development, improve traceability of inputs and outputs, and future-proof their digital strategies.

Understand how making data findable, accessible, interoperable, and reusable (FAIR) in a platform supports the use of artificial intelligence and machine learning (AI and ML), allowing for true data-driven decision-making.

ZONTAL is proud to partner with leading organizations to unlock scientific data across enterprises. If you’re ready to take the next step in your digital transformation, we’re here to help.