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NewZalo, Messenger & WhatsApp channels

AI assistants that talk, remember, and get things done.

One runtime for voice, memory, knowledge, and tools. Ship the same assistant to your website, Zalo, Messenger, apps, and ESP32 devices, built Vietnamese-first.

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Free plan · No credit card · Vietnamese & English

Simulated run

User: Remind me to water the plants at 7 tomorrow morning. Assistant: Done! At 7:00 tomorrow I'll remind you to water the three orchids on the balcony.

Assistants deployed in production
50+
To first audio in Realtime voice
~0.7s
LLM providers, switch per assistant
6
Messaging channels, including Zalo OA
6

Built on the models and voices you already trust

  • OpenAI
  • Anthropic
  • Google
  • xAI
  • DeepSeek
  • Xiaomi
  • ElevenLabs
  • Soniox

Provider and model availability depends on deployment configuration.

Ship everywhere

One assistant. Everywhere your users already are.

Configure the assistant once. Its knowledge, memory, and tools follow it to every channel.

Messaging channels

Connect Zalo OA, Messenger, Instagram, WhatsApp Business, Telegram, and TikTok Shop from the admin panel. Customers chat where they already are.

  • Zalo OA
  • Messenger
  • Instagram
  • WhatsApp
  • Telegram
  • TikTok Shop

Website widget

One script tag, isolated in Shadow DOM. Visitors can attach images and documents when you enable it.

Voice, two modes

Realtime mode talks speech-to-speech; Standard mode runs an ASR → LLM → TTS pipeline you tune per assistant. Users can interrupt naturally in both.

Time to first audio

Realtime
~0.7s
Standard
~1.8s
  • xAI Grok Voice
  • Gemini Live
  • OpenAI Realtime

ESP32 devices

The device keeps the mic, speaker, and sensors. The cloud does the thinking.

  1. 01

    Flash

    Firmware for ESP32 and ESP32-S3 boards

  2. 02

    Activate

    Bind to an owner with a 6-character code

  3. 03

    Talk

    Audio over MQTT + UDP, AES-128 encrypted

  4. 04

    Act

    Sensors and controls exposed as MCP tools

Roadmap: education robots, smart toys, in-car assistants.

Device guide
Agent runtime

Not just answers. Real work.

Every assistant gets memory, your private knowledge, and tools, with nothing to wire together yourself.

Long-term memory

Learns facts in the background and keeps their history. Users can view, edit, or reset what it remembers. Long conversations are summarized automatically to stay in context.

Knowledge base

Upload documents or crawl websites. Scanned PDFs are read with OCR, then searched on every turn.

Tools & MCP

Call your APIs, MCP servers, and devices.

  • Web search
  • Custom REST APIs
  • MCP servers
  • Device MCP
New

Scheduled tasks

Ask once, and the assistant runs the task on schedule. Results land in their own conversation, with an optional email.

Voice pipeline, your mix

Pick speech-to-text, LLM, and text-to-speech per assistant, or switch to realtime. Change providers in configuration, not architecture.

Every turn traced

Tokens, latency, tool calls, and prompt cache hit rate for every message, in the admin dashboard.

For developers

From one script tag to full API control.

Start with the widget. Move to the streaming Chat API or Voice API when you need your own UI.

  • Zero-dependency widget, isolated in Shadow DOM
  • Chat over Server-Sent Events, with idempotent retries
  • Voice sessions over WebSocket
  • Origin allowlist for every assistant
Read the developer docs
<script
  src="https://cdn.assistantcore.com/embed/embed.js"
  data-assistant-id="YOUR_ASSISTANT_ID"
  data-api-base="https://api.assistantcore.com"
  async
></script>
Built for Vietnam

Vietnamese-first, not translated later.

Built and operated for Vietnamese users and products, from voice and payments to data protection.

Vietnamese voice in production

Vietnamese speech recognition and synthesis run in the live voice pipeline, including realtime calls.

Zalo OA, natively

Answer customers on Zalo with the same knowledge and tools as your website.

Vietnamese product and docs

The web app, admin panel, and documentation are available in Vietnamese and English.

Decree 13/2023 alignment

Personal data handled in line with Decree 13/2023/ND-CP.

Security at every layer

  • HTTPS / WSS
  • AES-128 device audio
  • JWT / OAuth 2.0
  • RBAC
  • KMS-encrypted credentials
  • Rate limits
  • Embed allowlist
How we secure assistants
FAQ

Questions teams ask before they build

Do I need to write code?

No. You create and configure an assistant in the admin panel, connect channels there, and embed the website widget with one script tag. The APIs are there when you want your own interface.

Which languages does it speak?

Vietnamese and English are first-class across voice, the web app, the admin panel, and the docs. The LLMs handle many more languages in text.

Do I need my own model API keys?

No. Every model, voice, and tool runs on the platform's providers and draws from one credit balance, so there are no provider keys or separate bills to manage.

Which hardware is supported?

ESP32 and ESP32-S3 boards running our firmware, built on the open-source xiaozhi-esp32 project. Devices stream audio to the cloud runtime, which does the reasoning.

Which messaging channels can I connect?

Zalo OA, Facebook Messenger, Instagram, WhatsApp Business, Telegram, and TikTok Shop. Each connection uses the same assistant, knowledge, and tools.

How is my data protected?

Traffic is encrypted in transit, tool credentials are encrypted with KMS, access is role-based, and personal data is handled in line with Vietnam's Decree 13/2023/ND-CP. Users can view, edit, and reset their memory.

Blog

Insights from the team

Technical deep-dives, product updates, and best practices for building AI-powered products.

View all posts
Voice

AEC: Why AI Voice Assistants Need Echo Cancellation

Explaining Acoustic Echo Cancellation from the NLMS algorithm to real-world deployment in the browser (AEC3) and on ESP32 (ESP-ADF). Includes a comparison of AEC support across OpenAI, Gemini Live, and xAI Grok.

10 min
Architecture

Multi-LLM Architecture: 6 Providers, 14 Models, 1 Codebase

How we integrated OpenAI, Anthropic, Google, xAI, DeepSeek, and Xiaomi through native SDKs — letting users switch models mid-conversation, saving up to 90% on input-token costs with prompt caching, and deploying with zero downtime.

12 min
Architecture

Building a Real-World RAG Pipeline with pgvector

How we built a retrieval-augmented generation pipeline handling PDF, DOCX, and web URLs with chunking, embedding, and cosine search — reaching 91% accuracy compared to 34% with a plain LLM.

8 min

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