AI and Automation That Support Real Work in Regulated Operations
AI only creates value when it supports how work is actually done.
We help Life Science companies turn AI and automation into practical tools that reduce manual work, strengthen oversight and deliver value today – without vendor lock-in or unnecessary complexity.
Common challenges within AI and automation
Ambition without operational grounding
Many organizations want to apply AI, but initiatives often start without a clear link to daily work. Leadership often pushes for AI-driven insight, while business teams struggle to define where automation will actually reduce effort or improve decisions. This means AI becomes experimentation rather than execution.
Manual work persists due to weak data foundations
Across quality, regulatory, and clinical operations, much of the daily work follows repeatable rules – but still relies on manual effort. Data is scattered across RIM, QMS, TMF, ERP, and clinical systems, with inconsistent metadata and unclear ownership.
As a result, teams waste time exporting spreadsheets, manually reconciling data, and double-checking reports. Symptoms of systems built for compliance, not automation.
Regulatory uncertainty slows adoption
Even when use cases and data begin to align, uncertainty around validation, auditability and governance holds AI back. Often vendor-led tools promise speed but introduce lock-in and force processes to adapt to product limitations.
The result is technology management instead of operational improvement.
We solve this by
Use cases rooted in real work
We observe how teams operate, clarify where effort is spent and identify repeatable patterns AI can handle today.
Use cases emerge from concrete needs such as document classification in TMF, metadata validation across systems, regulatory translations, content summarization and on-demand support for regulated documentation.
Technology chosen for fit, not lock-in
We do not sell AI products. This means technology is selected to match your operational needs across models, platforms and vendors. You maintain control and flexibility as requirements evolve without being dependent on a single vendor's roadmap or pricing.
Automated data and AI pipelines you can trust
We assess data quality before automation begins. When metadata is inconsistent or business logic is unclear, we make sure the data is cleaned and enriched first.
Then we build pipelines, teams trust and deploy AI for document review, translation, classification and quality checks in controlled environments trained on your own data.
Adoption supported by training and governance
AI only works when people trust it. We train teams and leadership on what AI can deliver today and design workflows that support adoption. Automation reduces effort, removes bottlenecks and strengthens oversight instead of adding uncertainty.
Ready to explore practical AI and automation for your operations?
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What effective AI and automation look like in practice
Less manual work, more reliable execution
Dashboards pull from governed sources, refresh automatically and reflect operational reality rather than requiring manual reconciliation. Teams stop validating spreadsheets and start acting on insights.
Automation in document-heavy processes
Document intake, review, translation and classification run automatically with human oversight. Processing times drop from minutes to seconds, freeing capacity for higher-value work.
Measurable ROI from targeted use cases
Translation cycles accelerate. Document throughput increases. Metadata quality improves. Teams track hours saved, cost avoided, and errors prevented.
Technology that adapts as needs evolve
With no vendor lock-in, AI capabilities can scale, change or be replaced. Technology follows operational needs, not the other way around.
Hear from our clients
Practical results delivered through deep life science expertise.
Why life science companies choose Epista
Technology-agnostic by design
We do not sell AI products. Recommendations follow your priorities, not vendor incentives, giving long-term flexibility.
Business and technical expertise combined
Our consultants have worked inside regulatory, quality and clinical operations. They understand where AI creates value because they know the work it must support.
Domain knowledge translated into automation
We translate regulatory requirements into data structures and technical capabilities into operational value. AI becomes explainable, auditable and safe to use in regulated environments.
Value delivered today, not promised tomorrow
We focus on use cases that work now – document review, translation, metadata enrichment, content generation, audit trail analytics and automated reporting – not speculative future models.