Unified Gemini Enterprise
for Life Sciences AI
Faster trials. Connected supply chain and manufacturing. Stronger commercial outcomes.
Tredence acquires KMK Consulting to accelerate growth in Healthcare and Life Sciences — Read More
Fragmentation is the real constraint on Life Sciences AI
Life sciences organizations are tackling fragmented AI workflows that work in silos, but not as an enterprise AI layer. The result is scaling issues, increased operational complexity, and AI investments that never reach their full potential. Tredence brings the deep Life Sciences expertise, pre-built accelerators, and implementation depth to change that. We build a governed, enterprise-ready AI foundation on Gemini that connects R&D, clinical operations, manufacturing, commercial, and real-world evidence into one coherent system.
Purpose-built for pharma. Deployed across every function
From protocol to production line, Gemini Enterprise agents plug into the moments that matter most.
Clinical Trials
Gemini Enterprise unifies protocols, patient data, and trial reports so managers spend less time hunting for information and more time on patient outcomes. The agent taskforce accesses clinical trial protocols across sites, summarizes key patient data both in and outside the trial, and performs analysis across trial progress reports matched to patient feedback.
Research & Documentation
Researchers and clinicians reclaim hours lost to documentation and literature review, with multimodal AI grounded in real clinical data. Ambient medical documentation reduces the burden of manual charting, while imaging data is unlocked and made interoperable for clinical teams to include in trials. Agents rapidly analyze massive, multimodal data from electronic health records, imaging, and genomic repositories to accelerate medical research, and synthesize external data and health trends into actionable, patient-centric insights.
AI-First Coding
Generative, AI-first coding helps product and IT teams ship better experiences for patients and researchers, with fewer errors. Enhanced, automated QA processes help minimize customer service issues for both patients and researchers, while easier refactoring of complex legacy code reduces tech debt and improves scalability, making launching and testing new consumer and researcher experiences faster.
Pharma supply chain command centre
Gain real-time visibility across planning, sourcing, and fulfillment with AI-powered alerts and decision support. Achieve 48× faster analytics and 98% lower query time through a scalable, real-time architecture that delivers actionable inventory insights, automated root-cause analysis, and financial projections, enabling smarter, faster, and more connected supply chain decisions from a single command center.
Manufacturing Intelligence
Simulate your manufacturing shop floor in a digital twin environment to predict problems before they occur and take proactive corrective action. AI agents and LLMs automate data reviews, SOP checks, and exception identification across batch release, speeding up release cycles by up to 60% while maintaining compliance, consistency, and full audit traceability.
Unified Data Model (UDM)
Modernize legacy systems to enable seamless interoperability across R&D lab instruments, omics platforms, supply chain planning, manufacturing systems, and commercial CRM and sales data sources, bringing everything into a single, consistent data model. Gain omnichannel analytics, performance tracking, and clearer insights into HCP and patient engagement, so every team works from the same trusted foundation and makes decisions faster.
Commercial Excellence
Equip field teams with AI-driven targeting, territory alignment, call planning, and next-best-action guidance across HCPs, HCOs, and payers, drawing on omnichannel engagement data, prescription trends, and market intelligence to sharpen coverage and call quality. Enabling transparent, compliant incentive compensation so field behavior stays aligned to business objectives.
Real-World Evidence & Scientific Communications
Generate evidence from real-world data to demonstrate clinical, economic, and patient outcomes across the product lifecycle, from pre-launch burden-of-illness and treatment pathway studies to post-launch analytics on claims, EMR, and registry data. Shaping into congress abstracts, posters, and manuscripts, combining clinical, biostatistical, and epidemiological expertise with AI-assisted literature review and development, increasing publication impact and accelerating regulatory and payer discussions.
What the bold say about us: Clients. Partners. Analysts.
Our partnership with Tredence has played an important role in advancing BioMarin into a data-driven organization. Their deep expertise in data and AI, combined with a collaborative approach, has given us stronger control and governance over our data and decisions across commercial, supply chain, R&D, and other functions, enabling us to generate intelligent insights in near real time and make better, more confident decisions at scale.
What Tredence has done well for some of our customers is not only reduce their total cost of ownership by leveraging BigQuery, but also drive top-line impact by delivering insights that enabled them to transform business processes and unlock analytics that have improved overall performance.
Last mile impact stories
Transforming molecule-to-market decision-making with a unified Enterprise Data & AI Platform
A global biopharma unified molecule-to-market decision-making across Commercials, R&D, Supply Chain, and Corporate. Tredence built a modular Enterprise Data & AI Platform, anchored by a unified Marketing Customer 360 platform, to replace fragmented legacy systems, power R&D analytics for biomarker discovery, and run AI-driven predictive supply chain operations, all while enabling ROI-driven, single-source-of-truth decision-making.
Transforming supply chain decision-making with a unified, AI-driven insights platform
A US-based pharma needed a single, real-time platform for end-to-end supply chain visibility, but was held back by fragmented analytics, hundreds of disconnected Tableau dashboards, and no unified view of insights, KPIs, and actions. Tredence built a future-ready, scalable platform, centralizing KPIs and dashboards, adding a conversational AI interface for natural-language insights, and developing AI-driven root cause analysis using LLMs and graph-based reasoning.
Deploying Agentic AI as digital co-workers to transform manufacturing quality and speed-to-patient
A global biopharma's manufacturing and quality operations faced compounding bottlenecks from fragmented data and manual processes, unpredictable tech transfer cycles, subjective deviation management, manual document extraction slowing batch release, and no systematic way to monitor line efficiency. Tredence deployed purpose-built Agentic AI as digital co-workers, including a Tech Transfer agent team for knowledge extraction and risk summarization, a deviation management suite for CAPA recommendation and effectiveness validation, LLM-based document extraction agents, and Reliability Engineering agents for scorecards and bottleneck identification.
Automating document intelligence across business personas with a GenAI-powered system
A MedTech company faced inefficiencies across Project Management, Customer Care & Delivery, and Usability, driven by heavy reliance on manual processes, large volumes of unstructured documents, manual search and extraction, and regulatory constraints like GDPR and the EU AI Act complicating automation. Tredence implemented a GenAI-powered system combining rule-engine logic for structured data with GenAI agents for contextual reasoning, enabling intelligent document search, knowledge-based Q&A, and a conversational chatbot interface for user interaction and refinement.
Incentive Compensation Redesign for a Rare Disease Sales Team
A life sciences company's outsourced incentive compensation plan for its rare-disease biologic sales team was significantly missing corporate targets. Tredence surveyed the field organization and found low morale, only one in five reps who felt fairly compensated, and 93% preferring an individual plan over the existing divisional one. The redesigned plan shifted to individual performance, weighting payout 75% to Start Form and patient performance and 25% to unit performance, replacing prior kickers with a corporate performance multiplier for a simpler, more attainable plan.
