How it works
Hire the role. Train it once. Put it everywhere.
Aivah turns existing business knowledge into managed AI employees: role-based agents with voice, avatar presence, tools, deployment channels, memory, and performance visibility.
Start freeWorkflow
From first role to always-on operations.
The setup path follows the way a real business would hire, train, equip, deploy, and manage a new employee.Hire the role
Start with the AI employee your business needs most: sales, support, onboarding, training, phone, content, or operations.
Choose a curated template or build a custom role from scratch. Aivah helps shape the prompt, persona, presenter mode, and connected tools.Train it on your business
Upload documents, add URLs, paste text, or train on media so the employee can answer from trusted source material.
Supported knowledge sources include websites, PDFs, Word files, spreadsheets, slides, images, audio, video, JSON, XML, Markdown, and pasted content.Give it a voice and face
Choose a model, voice, avatar, image character, and scene so the employee can be text-first, voice-first, avatar-led, or presentation-ready.
Teams can use built-in voices, preview voices, private voices, 3D companion avatars, uploaded image characters, and branded scenes.Equip it with tools
Connect MCP tools or custom MCP servers so your AI employee can work with authorized systems instead of only answering questions.
Tool connections can use OAuth, API keys, bearer tokens, no-auth tools, custom authentication flows, and custom MCP URLs.Deploy it across channels
Publish it as a direct link, website iframe, chat bubble, realtime avatar experience, phone agent, Slack assistant, or WhatsApp assistant.
Public visitors can use shared agents without an Aivah account while teams control mode, branding, logos, backgrounds, and lead capture.Manage performance
Track conversations, leads, calls, transcriptions, quiz results, credit usage, and agent-level insights.
Improve the employee as your business, content, and customer questions change.Operating model
Train once. Deploy everywhere. Measure every conversation.
01Knowledge
02Presence
03Tools
04Channels
05Memory
06Insights
Enterprise rollout
Turn implementation into a controlled pilot, not a leap of faith.
Business teams should know the workflow, data scope, approval path, tool boundaries, and measurement plan before an AI employee goes live.Map the workflow
Choose one repeat function with clear demand, source material, owners, and a measurable business outcome.
Approve the knowledge
Define trusted documents, URLs, policies, scripts, media, and escalation rules before launch.
Pilot one AI employee
Deploy a focused role to one or two channels so teams can validate quality, safety, and handoff behavior.
Connect tools carefully
Add MCP tools, phone, Slack, WhatsApp, CRM, calendar, or custom workflows once the operating boundary is clear.
Measure and expand
Review outcomes, conversation quality, captured leads, call logs, usage, and team feedback before scaling.