FAQ from Thunai
What is Thunai?
Thunai is an Agentic AI Platform that transforms unstructured, decentralized organizational knowledge into intelligent, task-executing AI agents — enabling teams to automate workflows, amplify productivity, and scale institutional expertise without dependency on individual specialists.
How to use Thunai?
Upload your knowledge sources once — no labeling, no prompts, no engineering required. Thunai’s AI analyzes context, intent, and relationships, then deploys ready-to-act agents across your stack. From day one, they reduce manual load, accelerate response times, and surface expert-level answers — anywhere your team works.
What exactly does Thunai do?
Thunai operationalizes knowledge. It doesn’t just retrieve information — it interprets, reasons, acts, learns, and evolves alongside your organization. Whether you’re onboarding new hires, launching a product, or scaling support, Thunai turns what you *know* into what your systems *do*.
What makes Thunai different from other enterprise search solutions?
Search finds. Thunai understands, decides, and executes. While traditional tools return documents, Thunai delivers actions — like drafting a reply, updating a ticket status, or booking a meeting — grounded in your proprietary knowledge and aligned with your business logic.
How does Thunai handle sensitive customer data?
Data residency, encryption-in-transit-and-at-rest, role-based access controls, SOC 2-aligned architecture, and optional private-cloud or air-gapped deployments ensure full compliance with GDPR, HIPAA, and regional data sovereignty requirements.
Do you offer on-premises deployment options?
Yes. Thunai supports fully managed on-prem, private cloud, and hybrid deployments — giving enterprises complete control over infrastructure, data governance, and integration architecture.
How can Thunai help in customer support automation?
By equipping support agents with real-time AI co-pilots — and empowering customers with 24/7 self-service agents that resolve ~70% of Tier-1 issues instantly, escalate intelligently, and feed learnings back into the system — continuously improving accuracy and coverage.