Lorikeet builds AI agent infrastructure for customer support in complex, regulated environments where traditional chatbot deflection fails. The platform handles end-to-end resolution across voice, chat, and email channels, with agents that query backend systems, execute actions, and navigate multi-step decision trees rather than routing to self-service. The architecture is designed for flexibility in high-stakes scenarios - financial services disputes, healthcare eligibility determinations, compliance-sensitive transactions - where precision in data retrieval and action execution is non-negotiable.
The system serves fintechs, healthtechs, crypto marketplaces, delivery platforms, and energy providers - sectors where support tickets frequently require cross-system lookups, stateful workflows, and regulatory constraint adherence. Lorikeet's positioning centers on solving tickets that involve both complex decision logic and the operational risk of incorrect system mutations, rather than optimizing for deflection rates or simple FAQ coverage. The platform's value proposition scales with ticket complexity: environments where support resolution requires chaining multiple API calls, interpreting policy logic, and maintaining audit trails under regulatory oversight.
Headquartered in Australia with a global customer base, Lorikeet targets organizations where support automation must balance throughput gains against the operational and compliance costs of failure modes in agent reasoning or action execution. The technical challenge space includes latency management across synchronous system integrations, reliability in multi-turn voice interactions, and maintaining accuracy bounds when agents operate with partial information or ambiguous customer intent.