The AI engines that power every RxAmplify solution.
A reusable technology stack of specialised engines, applications, evaluation systems and governed workflows—deployed in your cloud and configured for each pharma function.
One technology foundation, configured for many pharma decisions.
Each solution combines a task-specific application with reusable AI engines, validation methods and your organisation’s data, rules and approvals.
Commercial, medical, market access, regulatory, strategy or operations.
A purpose-built experience for the team, workflow and decision.
Content Authoring, AutoML and AgentML supply reusable intelligence.
Evaluation, human approval and auditability inside your cloud.
Ready-made starting points for high-value pharma workflows.
Each application packages a proven workflow, interface and set of specialised skills. It can be configured for a brand, market or business process without rebuilding the underlying technology.
Dossier Authoring
HTA dossiers and regulatory documents, drafted by agents your experts control.
Marketing Content
One brief becomes on-brand, claim-checked content for every channel.
Brand Strategy Planning
Specialist agents assemble the evidence and draft the annual plan for human decision.
Atlas KOL Intelligence
Every expert in your indication, resolved to one profile and ranked on evidence.
Forecast IQ
Revenue forecasts built from evidence or your existing Excel models, in hours.
BYOB Conversational Analytics
Plain-English answers, charts and reasoning from your own governed data.
Reusable engines, specialised for pharma.
The engines supply the authoring, modelling and agentic capabilities reused across RxAmplify applications and custom solutions.
Seven cooperating agents learn templates, gather evidence, draft, check and support expert review.
Template · ingestion · retrieval · guidance · authoring · evaluation · co-pilotAutomates data ingestion, pharma-specific features, training, deployment and explanation.
Explore AutoML → AgentMLAgentic data science with guardrailsRuns analysis through a governed loop, with reusable skills and a person approving each step.
Explore AgentML →Built to be signed off.
Quality checks and impact measurement are part of the technology, so regulated outputs can be reviewed and business claims can be defended.
Known factual, formatting and visual errors are inserted to measure how reliably the system catches them.
Matched controls and difference-in-differences help distinguish programme impact from background change.
Experts review, edit and approve regulated outputs and critical decisions.
Sources, steps and approvals are recorded inside the client’s AWS or Databricks environment.