Aivar puts governed AI agents to work across payer operations, claims processing, pharmacovigilance, and patient engagement. Deployed inside your own cloud, audited at every step, and live in weeks.
Healthcare and life sciences run on documentation, and documentation runs on precision. Every claim needs to be coded correctly, every adverse event needs to be reported on time, and every patient interaction needs to hold up to a payer or a regulator. Aivar brings frontier AI models into production for RCM, pharmacovigilance, and patient engagement teams, wrapped in governance that satisfies compliance and audit from day one.
Every accelerator deploys inside your own AWS account, so patient and case data never leaves your infrastructure.
From payer operations to drug safety, each accelerator is tuned to the workflows and regulations that define your business.
Claims processing, prior authorization, and payer-provider conversations, automated end to end and coded correctly the first time.
Adverse-event intake, triage, and regulatory reporting that keep pace with MedDRA and FDA timelines.
Clinical documentation, prior-auth support, and provider servicing that free up time for patient care.
Personalized coaching and engagement for digital-first health and wellness platforms.
Three accelerators, two foundations, one architecture built to survive an audit.
Handles payer-provider conversations, appointment scheduling, and patient engagement across voice, chat, and in-app, with every interaction logged for HIPAA-aware compliance review.
>> Conversational AI for payer, provider, and patient interactions <<
Runs document-heavy processes such as claims processing, prior authorization, and pharmacovigilance adverse-event reporting end to end, with every decision traced back to the policy or regulation that produced it.
>> Governed automation for claims and drug-safety workflows <<
Trains and serves clinical NLP, radiology AI, and drug-discovery models inside your own VPC, with full audit trails and cost visibility built in.
>> Infrastructure for clinical and life sciences models <<
A sample of the engagements we've shipped.
A serverless, voice-enabled meal logging and nutrition analysis platform for chronic disease management, built on Amazon Bedrock with a HIPAA-aligned security architecture.
A secure multi-account AWS foundation, automated IoT device onboarding, and a GPU-accelerated 3D reconstruction pipeline for a next-generation intraoral X-ray platform.
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No. Every Aivar accelerator deploys inside your own AWS account or VPC. Patient records, case data, and model inputs stay on your infrastructure throughout.
ReVAct, our governance foundation, gates every agent action before it reaches a system of record and logs the reasoning behind it, giving your compliance team a full audit trail for every claim, case, or report an agent touches.
Most engagements move from discovery to a working proof of concept in one to two weeks, and into production within another six to eight, depending on integration scope. We build for production from day one rather than treating pilots as throwaway work.
General AI tools are built for productivity tasks like drafting and summarizing. Aivar's accelerators are built for regulated decisions such as claims adjudication, prior authorization, and adverse-event reporting, with the governance and audit trail healthcare and life sciences regulators expect, and priced against the outcome delivered rather than tokens or seats.
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