Not a single application — a generative capability. The intelligence engine produces personalized, use-case-specific experiences from the governed context beneath it. A QC lead gets accelerated investigation with full context traversal. A process engineer gets tech transfer readiness across sites. A stability scientist gets trending and cross-program signals.
Analyze provides SQL and API access to all governed data, with native integration into the analytics tools your teams already use.
SQL and API access to all governed data — the analytics-first interface for data scientists and analysts. Connect your existing Tableau, Spotfire, Power BI, Databricks, Snowflake, or Jupyter environments directly to the governed context graph. No CSV exports. No manual assembly. Live, governed, traceable data access at portfolio scale.
With governed data access in place, the following capabilities become possible.
Scientific data processing and visualization for spectrometry and spectroscopy. Once Integrate ingests raw instrument data and Contextualize governs its context, SciYNova applies technique-specific algorithms to extract chemical knowledge: peak identification, spectral deconvolution, quantification, and structure elucidation.
SciYNova is available as a desktop application (with structure elucidation, spectral database, and molecular formula determination) and a browser-based edition (NMR, MS, and optical spectroscopy viewer embedded in ZONTAL or third-party applications like ELNs). SciYGears automates analytical reprocessing, analysis, and reporting pipelines — enabling closed-loop workflows where data from instruments is automatically processed, evaluated, and documented without manual intervention.
Real-time process control and Process Analytical Technology (PAT) knowledge management. While ZONTAL governs analytical data at rest, synTQ orchestrates process data in motion: multivariate process control, PAT instrument coordination, and real-time quality prediction across batch and continuous manufacturing workflows.
Today's analytical teams operate on CSV exports, Excel aggregations, and isolated LIMS reports. Every cross-program question requires weeks of manual data assembly — and the answers arrive too late to change the decision.
Stability trending, comparability analysis, and cross-program signals all start the same way: export data from LIMS, clean it in Excel, copy it into a separate analytics tool. The analysis is disconnected from the governed source — and stale before it's finished.
A degradation signal detected in one program may be invisible to teams working on structurally similar molecules in other programs. Without connected context across the portfolio, each program operates as an island — rediscovering risks that the organization already encountered.
By the time a cross-program trend report is assembled, reviewed, and delivered, the filing window has narrowed or the manufacturing decision has already been made. Insight that arrives after the decision point is documentation, not intelligence.
The analytics foundation above is deployed. These capabilities are what governed, connected data makes uniquely possible — Analyze operates on the governed context graph — not on disconnected exports — producing intelligence that compounds with every program added to the platform.
When an out-of-specification result, process deviation, or quality event occurs, the investigation starts immediately — not after weeks of data gathering. The intelligence engine traverses the context graph to identify related batches, materials, methods, and prior events, producing a structured investigation package that includes the full lineage of every entity involved.
Technology transfer between sites today requires 12–18 months of PDF-based batch record reconciliation. The intelligence engine packages the complete analytical context — methods, results, process parameters, equipment qualifications — into a structured transfer package with full lineage. Receiving sites get comparable data from day one, not after months of manual reconstruction.
ICH Q1A and Q5C stability programs generate continuous data across batches, temperatures, and timepoints. At portfolio scale, hundreds of active stability studies produce thousands of data points per quarter. The intelligence engine provides monomer trending, HMW aggregate alerts, proactive CQA monitoring, and cross-program degradation signal detection — all on governed, traceable data.
Comparability analysis, method transfer tracking, and filing readiness gap detection across programs. CMC Readiness is a Decide outcome that draws on Analyze intelligence for cross-program pattern detection, then adding AI-enabled filing assembly. Surface the gaps before the FDA does — with full traceability from every data point back to its source instrument, method, and operator.
The intelligence engine does not deliver a monolithic dashboard. It produces personalized, use-case-specific experiences, each tuned to the role — personalized to the customer's data, compounding over time, and becoming indispensable.
Purpose-built for QC leads managing release testing across sites and products.
Purpose-built for development scientists executing site-to-site technology transfers.
Purpose-built for the stability lead managing hundreds of active studies across the portfolio.
Purpose-built for the CMC lead responsible for regulatory-grade data packages across programs.
Scientific Intelligence surfaces analytical insight across programs, sites, and time — turning governed data into decision-ready views. Explore the interactive experience below to see how each capability works.
Browse the governed context graph to surface evidence completeness, identify gaps in CTD module coverage, and assess traceability chains — the intelligence foundation that feeds into Decide IND compilation.
Full ICH Q1A accelerated stability study: 3 temperatures × 7 timepoints × 3 replicates. Monomer trending, HMW aggregate alerts, charge variant monitoring by IEX. Degradation signal detection across programs from governed stability data.
Side-by-side analytical comparison across batches, sites, and time periods. SEC monomer purity, size variants, charge variants, and process parameters — all rendered from the governed context graph with full lineage to source instruments and methods.
Critical quality attributes tracked across the portfolio: SEC monomer at 25°C, HMW aggregates, titer, PS-20 degradation — with trend direction, risk level, and alert thresholds. PS-20 degradation flagged as a risk signal across 3 IgG1 programs.
Analyze intelligence — cross-program analytics, anomaly detection, and predictive signals — becomes the foundation for AI-enabled decisions. Without validated intelligence, Decide AI workflows operate on unverified assumptions.
This is the critical transition: from intelligence that informs scientists to supervised autonomy that acts alongside them. Every pattern identified, every signal validated in Analyze trains the AI workflows above to produce decisions that regulators accept and scientists trust.
Analyze establishes the INTELLIGENT stage. Your governed data produces cross-program analysis, stability prediction, and submission-ready evidence — intelligence that compounds with every program added to the platform.
Instruments integrated, data flowing, metadata enriched
Scientific context graph, governed lineage, reconciled identifiers
Accelerated investigations and tech transfer
Portfolio intelligence, AI decisions, supervised automation
Scientific intelligence requires governed context (Contextualize) and industrialized integration (Principle 1). Without the foundation, intelligence produces noise, not insight. With it, every program added makes every capability stronger.
Governed factories that compound with every build
The connected scientific context graph
Accelerated investigations and tech transfer
Agentic workflows & configurable automation
“The first thing a structured digital method does is create a complete, consistent documentation of the analytical experiment. From there you can do many things.”
See how the intelligence engine transforms governed context into stability prediction, accelerated investigations, and submission-ready evidence — personalized to your portfolio.
