AI for pharma that survives inspection.

Not under a named pharma logo, and we will not pretend otherwise. What we do run in production is every building block a pharmacovigilance and regulatory program needs: document intelligence that reads long documents and surfaces findings traceable to their source, high-throughput transcription that turns call-center audio into structured text, conversational personas that answer within boundaries and escalate, and human review queues run by trained reviewers. Pharma is a priority vertical for us because those primitives map onto adverse-event intake, medical information and submission work almost one to one. You get proven engineering and an honest read on what the first pharma build has to prove.

No, and that is a hard design rule, not a setting. Digital workers do the intake, triage and MedDRA coding and draft the case, but a qualified person reviews and submits every ICSR. The system never auto-submits, and it never downgrades a seriousness assessment on its own: if anything points to a serious case, it routes up, never down. Every step is logged with who saw what and when, so the case holds up when an inspector replays it.

As a design constraint, not a disclaimer. Every action is logged with an attributable, time-stamped trail, approvals sit behind electronic sign-off, case data follows ICH E2B structure, and patient data is masked before models see it. The posture is built to support GxP and GVP expectations, 21 CFR Part 11 on electronic records and signatures, and India's DPDP Act. We do not claim your system is validated; we build so your validation and your inspectors have the evidence they expect.

It can propose the coding, which is where the volume is. Digital workers read the source report, extract the case, and propose MedDRA terms and a seriousness assessment, calibrated against your conventions. A coder or qualified person confirms every code, disputed terms route to review, and the system never downgrades seriousness on its own. The goal is to take the manual keying off skilled people, not to replace the judgment a regulator expects from a human.

Within boundaries, yes. We build conversational responders that answer from approved reference documents only, cite the source, refuse off-label and unapproved questions, and hand off to a medical-information specialist when a request crosses defined lines. Every interaction is logged, and anything that looks like an adverse event or product complaint is captured and routed into the safety workflow, not just answered.

Yes, that is a common starting point. Most pilots die between demo and production because the boring half was never built: evals, guardrails, the audit trail, escalation paths and a data-handling story that survives an inspection. We audit what exists, add that layer, and either productionize the pilot or tell you plainly why it will not pass.