Proactive AI pharma research agents.
Build research prompts and workflows around the markets that matter to your team.
RxClarity agents read your defined context including priority companies, assets, indications, targets, mechanisms, and competitors then monitor for relevant change and investigate it using connected, source-linked evidence.
Outcome: your team spends less time searching for updates and more time deciding what to do next.
Build repeatable workflows, not one-off prompts.
General AI often starts from scratch. RxClarity lets teams create repeatable workflows around recurring intelligence needs.
Outcome: a consistent intelligence process that can be revisited as the market evolves.
Set the context once. Get relevant intelligence continuously.
Create your own prompts and workflows, such as:
“Alert me when a competitor advances an asset in atopic dermatitis.”
“Review new Phase 2 or Phase 3 trial activity in our target indication.”
“Identify upcoming clinical, regulatory, or patent catalysts for this market.”
“Summarise meaningful changes across our competitor watchlist.”
“Assess whether a new data readout changes the competitive landscape.”
RxClarity agents use that context to focus research on what is relevant to your priorities.
Outcome: fewer generic alerts, less manual monitoring, and a more focused competitive view.
Triangulated, source-linked intelligence.
RxClarity agents validate signals across connected sources—not just one press release, news article, or registry record.
Every output is connected to the underlying companies, drugs, trials, approvals, publications, patents, and news records.
Outcome: faster research with evidence your team can inspect before acting.
Put proactive agents to work for your team.
Turn your priority questions into repeatable, context-aware workflows that keep up with the market.