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VerifiedSoftware Development· Founded 2022

Unipr

Life sciences companies don’t stall because of a lack of innovation — growth slows because of operational drag. Fragmented systems. Siloed teams. Slow decisions. These aren’t technical problems. They’re organizational ones. At Unipr, we build AI to turn operational complexity into a competitive advantage. Unipr AI Agents Autonomous, role-focused AI agents built to perform real operational work — from portfolio analysis to resource forecasting to launch readiness. For emerging biotechs, Unipr AI Agents act as a force multiplier — scaling operational capacity when teams are lean and resources are limited. For large pharma, Unipr AI Agents drive operational excellence at scale — improving collaboration, optimizing resource utilization, and accelerating decision-making across regions. Unipr AI Ecosystem A real-time alignment and coordination layer that unifies fragmented execution across internal systems, external tools, and functional workflows — giving leaders a single source of truth for operational visibility. Unipr AI Platform A collection of purpose-built Operations AI apps designed for how R&D, Commercial, and Supply Chain teams actually work — enabling organizations to plan, execute, and adapt faster. How Leaders Use Unipr AI: • Streamline development programs and accelerate time-to-market. • Execute complex launches faster, smarter, and at a global scale. • Forecast budgets, resources, and risks with confidence. • Prioritize research portfolios with data-driven clarity. • Adapt tactics in real-time as scenarios evolve. Powered by: – Predictive AI for proactive, data-informed decision-making. – Generative AI for workflow automation and operational scale. With Unipr AI, operational excellence isn't a back-office function anymore — it’s a core growth driver. It’s how we help life science companies accelerate medicines — for the patients waiting for them.

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HeadquartersSan Jose, United StatesEmployees4(11 to 50)Founded year2022Websiteunipr.comLinkedIn profileLinkedIn

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