Scale your
scientific expertise
across drug development.
Automate routine analytical review in DMPK, CMC, and QC.
The decision layer that
scales scientific understanding.
Review the Exceptions.
Not the Whole Batch.
50×
Workflow Capacity
Raw instrument data to signed, LIMS-ready output
across every method and site.
Analyst-Validated,
Production-Proven.
99.9%
Accuracy
Exception-based review with full traceability
eliminates manual decision drift.
Consistent Analysis.
Run After Run.
7×
Fewer Reruns
One platform across fragmented instruments, software, and data.
Move at the Speed of Discovery. Trust Every Result.
AI has made the front of drug development faster than ever. Validating those candidates hasn't kept up. Analytical decisions are still made by hand and siloed by stage, so the pipeline moves at the speed of its slowest handoff, and the AI tools meant to help can't be trusted in a regulated workflow.
Expert Intelligence weaves those decisions into one analytical fabric across the pipeline. It scales and accelerates every analytical decision with regulatory-grade accuracy, connects them from discovery to manufacturing, and flags risk before it reaches release, scientist-trained, signed, and never hallucinated. Your programs move faster, and every result holds up.
One Platform. Every Instrument.
EI works across your existing instruments, methods, and sites, no rip-and-replace, with standard connectors into your LIMS and enterprise systems. Every result is confidence-calibrated, exception-routed, and regulatory-grade, with full traceability from raw data to signed output.
Your Data Stays Yours
EI deploys into your own environment, cloud, on-premises, or hybrid, so your data never leaves the place it was generated. No new hardware, validated configurations supported, nothing to rip out and replace.
Trained on Your Data. Owned by You.
Your scientists train the model inside your environment, no code required. About 50 examples is enough for it to learn your targets and your decision logic. From there, every analyst correction feeds back through active learning, refining it toward 99.9% accuracy, and the trained model is your institutional IP.
See it in action.
Request a demo and see how trusted results compress the time and cost of drug development.
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