Sparse Data.

Serious Accuracy.

Logo for SLAS 2026 International Conference and Exhibition, featuring bold black and white text with a large number 2026 and the initials SLAS.

Booth #1266

Feb 7-11

Boston, MA

Expert Intelligence is the decision layer across the lab,
delivering fewer re-runs, defensible results,
and faster throughput.

Minutes,
Not Months.

50×

Faster Reviews
Batch review cycles are significantly shortened while maintaining rigor and traceability.

High Precision,
Fewer Reruns.

Fewer Errors
Exception-only review reduces errors by removing repetitive manual decisions.

Actionable Results,

In Real Time.

10×

Faster Time to Value
Operational impact is achieved in days, not months by turning instrument data into action.

For Pharma leaders eliminating deviations, remediation, and regulatory drag in lab operations.

What We’re Showing
at SLAS 2026

Come see what purpose-built AI looks like in the analytical lab. Expert Intelligence applies AI as a governed decision layer that learns from expert review, operates across instruments and modalities, and delivers 99% accuracy with full traceability. It supports GMP workflows end-to-end and integrates directly into existing SOPs and review processes; so analysts move faster without adding risk, re-runs, or investigation overhead.

See your analytical methods running with AI

LC-MS and LC-MS/MS
Quantitative decisions with audit-ready outputs and governed review logic.

Proteomics and Biomarkers (DDA, DIA)
Protein-level confidence through alignment, interference handling, and reproducible identification.

QC ADC, Intact Mass, AS-MS
Deconvolution, proteoform analysis,
DAR calculation, and microheterogeneity assessment

icIEF, CE, SEC
Consistent peak identification, integration, and release logic.

Glycan Analysis
Isomer resolution, ambiguity management, and scalable expert annotation.

Titration
Automated curve fitting and endpoint determination.

Decision automation for exception-only review.
Reduce re-runs and shorten review cycles by focusing human attention only where it’s needed.

Cross-lab visibility across methods and modalities.
Surface  patterns and inconsistencies across runs, instruments, and data types.

Governed AI for regulated environments.
Traceable, reviewable, and controllable by design to support validation, audit, and release workflows.

Our View on the Future of AI in the Lab

AI in the lab is moving beyond tools, dashboards, and automation scripts. The next phase is an AI decision layer — an operating system for the lab that standardizes how decisions are made, executed, and governed across instruments, workflows, and teams.

In this short series, we share our perspective on how AI is reshaping lab operations — not by replacing experts, but by making expert decisions consistent, defensible, and scalable.

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AI’s Real Value in Pharma Isn’t Speed. It’s Consistency.

Why decision consistency is the foundation of trust in regulated labs.

A person working at a desk with a large monitor, surrounded by office supplies and binders, in a modern office environment.

Why Labs Need a Different Kind of AI

Why language models fall short — and what decision-grade AI requires.

Three healthcare professionals in lab coats having a meeting around a table in a well-lit office.

AI in the Lab Is a Leadership Decision

Why governing AI matters more than deploying it.

If you’re attending SLAS and evaluating AI for regulated lab operations, let’s connect.

Book time with Expert Intelligence at Booth 1266.

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