AI for healthcare and emergency-response operations

The challenge

These operations run all day and handle sensitive data. A failure of the AI must not stop a call or a care record.

Health data is sensitive personal data under the LGPD, the Brazilian data protection law. Access, logs and providers need strict control.

Architecture

• The AI runs outside the real-time telephony server. Audio goes to a separate processing queue.
• Transcription and summaries run on private GPUs.
• Clinical text, transcripts and personal data stay out of logs.
• Design rule: the model proposes, and a person confirms before any record or action.
• Integration with the telephony platform uses its management interface, with events and reconnection.

In production

I build and operate systems for healthcare and emergency-response operations: SIP telephony with softphones and desktop applications, transcription and summaries on private GPUs, and integration with the systems that already exist.

Client names and patient data stay confidential.

Limits

• In healthcare, the AI output is a draft for a professional. It does not replace clinical judgement.
• A telephony change needs a maintenance window and a rollback plan agreed with the operation.

Hire me for this

• An assessment of where AI helps the operation without risk to calls or records.
• Transcription and summaries on private infrastructure, with access control and an audit trail.
• Integration with telephony, with a staged deployment and a rollback plan.