Endpoint Clinical Embeds ThoughtSpot for Clinical Insights

Impact Statistics

• Accelerated implementation time down to just 3 months
• Dramatically minimized development overhead, requiring only 3 fractional FTEs compared to a full team
• 3x faster time to insight

The Challenge

Moving past static reporting in a high-stakes, data-intensive industry

In the highly specialized realm of RTSM, data is fast-moving, continuous, and heavily transactional. Managing this information requires navigating granular row- and cell-level permissions to strictly protect Patient Health Information (PHI), Personally Identifiable Information (PII), and study blinding protocol requirements.

Endpoint Clinical previously spent considerable time and engineering capital building out internal, homegrown dashboarding features. However, those early-generation solutions were static, difficult to seamlessly white-label, and quickly created an inefficient "report factory" loop.

Six years ago, our prior experiences with dashboarding were completely static. It took excessive time to curate and craft content, and ultimately we had relatively little adoption—despite spending a good amount of money. It was tough to white label, didn't look native, and our delivery time to push out new content took way too long.

Jeff RubesinVice President, Product StrategyEndpoint Clinical

Because the existing setup lacked flexibility, customers routinely requested specific adjustments, forcing engineering to continuously code customized permutations. This internal strain delayed core product roadmaps while failing to deliver the dynamic analytical autonomy that modern healthcare professionals require.

The Solution

Buying a mature platform solution to build deep, validated AI data models

Endpoint Clinical adopted a strategic approach: buy and embed a mature framework rather than spending valuable years reinventing an entire business intelligence infrastructure from scratch. After evaluating four separate vendors, the company chose ThoughtSpot Embedded to natively power their new analytics offering, ELO Insights.

A primary differentiator was ThoughtSpot's enterprise-ready AI capabilities through Spotter. In the clinical trial ecosystem, data accuracy is absolutely non-negotiable. Mistakes can directly impact patient care, making it necessary to implement a platform that offers total transparency over how an LLM handles insights.

When we provide analytics, our data cannot be inaccurate. You cannot get it wrong when dispensing cancer medication to patients. ThoughtSpot allowed us to carefully build out and validate our data models, and it gives users a view of the complete rationale and lineage behind how Spotter calculated its answer. That human-in-the-loop validation is massive for us.

Jeff RubesinVice President, Product StrategyEndpoint Clinical

By extending ThoughtSpot’s permission framework to map to cell-level RTSM security needs, Endpoint Clinical successfully integrated interactive Search and GenAI features straight into the user interface.

The Results

Extreme time-to-market savings and real-world clinical impact

Partnering with ThoughtSpot enabled Endpoint Clinical to bypass complex AI infrastructure design hurdles and bring a polished product to market ahead of the competition.

• Leapfrogged engineering complexity and saved FTE overhead
  By leveraging ThoughtSpot Embedded, Endpoint Clinical completed their full integration and data modeling pipeline in 3.5 months without standing up a large, cross-functional team. Instead of an 8–10 month build requiring developers, product managers, and specialists, the work needed just three fractional resources: a half-time front-end developer, a quarter-time architect, and a data specialist. The result was significantly lower upfront development costs and freed the broader product team to stay focused on mission-critical features.
• Designed for a diverse, non-technical user base
  The platform serves a massive range of users including nurses, clinical trial investigators, and internal supply teams. ThoughtSpot Embedded provides a highly adaptable experience: users who need simple monitoring can interact with pre-packaged reference dashboards, while power users can independently type natural language queries directly into Spotter to run complex, longitudinal data analysis.
• Evolving features with continuous delivery As ThoughtSpot upgrades its underlying technology, Endpoint Clinical instantly benefits without writing new code. For example, upgrading smoothly from early generations of Spotter to Spotter 3 provided immediate improvements in deep data analysis capabilities, which Endpoint Clinical absorbed directly as an automatic product feature upgrade for their customers.
• Shifting the ROI focus to customer outcomes The real success of ELO Insights lies in the financial and clinical efficiency it unlocks for study sponsors. By allowing users to spot longitudinal data trends across massive historical data sets, sponsors can optimize clinical trial designs, adjust dose titrations, map out better supply management, and reduce logistics costs. Ultimately, these efficiency gains help pharmaceutical companies minimize waste and bring lifesaving medications to market much faster.

Looking Ahead

Endpoint Clinical's journey from static dashboards to a fully embedded, AI-powered analytics experience in just three months stands as a compelling proof point for the build-versus-buy debate in enterprise software. Looking ahead, Jeff Rubesin and his team are far from finished — with a dedicated roadmap for data, AI, and analytics that includes additional capabilities like live boards and deeper data model integration, Endpoint sees its partnership with ThoughtSpot as an ongoing foundation for innovation rather than a one-time implementation. By offloading the complexity of analytics infrastructure to a mature, continuously evolving platform, Endpoint's engineering teams are now free to direct their energy toward what only they can build: the mission-critical clinical trial technology that helps pharmaceutical sponsors bring lifesaving medications to patients faster. As the broader industry races to close the gap between AI ambition and production reality, Endpoint Clinical has already moved on to the next challenge — building on top of a framework that grows with them.