Your brand · any use case · one AI platform

The AI you brand as your own.

AI Assistant is a universal, configurable AI you ship under your own name — on your domain and embedded in your product. Support, sales, docs, ops, or a copilot: one platform, configured per tenant — and it acts, not just answers.

Build with AI Assistant See it live White-label integration guide

Hosted web
Web embed
iPhone
Android
Desktop

Live AI experience · support configuration

account · bp_2048

Why is my payout still pending?

I found your latest payout. It is waiting for the device verification that started 18 minutes ago.

busyproxy.get_payout_status

Policy event

Verification exceeds 15 min

Human handoff

Operator notified

Ana joined the conversation

AI context and tool results included

LIVE

Running in production

Real products already run on AI Assistant.

Each of these is a live white-label deployment — its own brand, domain, tools, and users. Open one and talk to it.

Busymate DevTools

An engineer’s copilot for a developer-tools product — embedded in the product’s own dashboard, acting through the product’s MCP tools.

bro.busymate.aiOpen live

BusyProxy

Customer support and real account actions for a proxy platform — payouts, devices, and verification, answered through its own API.

support.busyproxy.netOpen live

BusySMS

Support and onboarding for an SMS-gateway product — from enrolling phones to OTP capture, live on its own support domain.

bro.busysms.netOpen live

Every brand is its own isolated tenant — one platform underneath them all.

One platform, every piece

Everything a branded AI needs — built in.

Configure a tenant once. The same brand, policy, tools, identity, knowledge, history, and human workflow travel to every surface.

White-label by default

Your name, colors, and voice on your own domain — and embedded in your site. The full rich chat experience, not a widget-sized bot.

Universal, not support-only

Support is one configuration, not the product. Sales, docs, onboarding, operations, or an in-product copilot — the same platform, configured per tenant.

Connected to your tools

Attach MCP servers, skills, and knowledge. With per-user authorization the AI acts on each customer’s behalf through your own API — answers come from your product, not a copied help center.

Customer-aware and safe

Bring the signed-in identity you already have. Tenant policy decides what the AI may read, change, or automate — and sensitive actions pause for an explicit confirmation.

Human handoff built in

Escalation triggers notify operators, and a person joins the live conversation with full AI context — no lost thread, no second tool.

History and model choice

Complete conversation history for users and operators, and per-tenant model policy — you decide which models serve your traffic.

Operate and govern

You govern it — even conversationally.

AI Assistant is operated like a product: models, limits, and features are tenant policy, usage is measured per provider, and the assistant itself is a console.

Models and limits are policy

Choose which models serve each tenant, cap usage, and turn features on or off — no redeploy, no code change.

Usage you can bill against

Calls, tokens, and spend by model provider — today, 7 days, 30 days, or all time — per tenant and per user.

Manage it in chat

Ask the assistant to update branding, invite an operator, or read usage — the same governed actions, conversationally.

Self-service onboarding

A guided wizard takes a new tenant from name and colors to a live assistant on its own subdomain — TLS and domain provisioning included.

Tenant governance

Model policy

2 providers · 3 models allowed

Monthly conversations

10,000

Features

Human handoffChat insightsWhite-label

Spend by provider

Today7 days30 daysAll time

anthropic

72%

openai

23%

google

Your product remains the source of truth.

Connect tenant MCP servers, publish only the tools each experience should use, and exchange your existing signed-in identity for a short-lived, tenant-bound session. Secrets stay write-only and cross-tenant fallback is denied.

MCP servers and selective tool publishing

Signed customer identity with replay protection

Per-tool confirmation and human-intervention policy

Launch an identified AI Assistant session

support-launch.jsJavaScript

const session = await fetch(
  "https://api.busymate.net/functions/v1/support-launch",
  {
    method: "POST",
    headers: { "content-type": "application/json" },
    body: JSON.stringify({
      assistant: "your-tenant",
      channel: "hosted_web",
      origin: window.location.origin,
      token: await yourApp.issueSupportToken(),
      nonce: crypto.randomUUID()
    })
  }
).then(response => response.json());

Conversation intelligence

Every AI interaction becomes product intelligence.

AI Assistant audits the complete conversation history — not isolated ratings — to reveal what users repeatedly struggle with, where automation stalls, why humans intervene, and which improvement will have the highest impact.

Evidence, not guesses

Open the exact conversations and turns behind every finding.

Catch emerging issues

Separate recurring friction, incidents, knowledge gaps, and human-escalation pressure.

Turn signals into work

Attach a recommended product, content, automation, or support action to each cluster.

Measure the response

Track whether a shipped change reduces repeats, escalations, and unresolved conversations.

Open the AI workspace

Example insight report

Last 30 days · clustered from AI conversations

Analysis current

Chats analyzed

Issue clusters

31%

Human escalation

Withdrawal verification confusion

38 chats+42%

Evidence · Escalation risk

Customers cannot tell whether verification blocks payout eligibility.

Recommended action

Clarify the withdrawal screen and trigger proactive guidance before cash-out.

Android setup permission friction

21 chats+18%

Evidence · Setup blocker

Permission questions repeat immediately after first-device activation.

Recommended action

Add a contextual permission explainer to Android onboarding.

Pricing explanation missing from onboarding

13 chatsNew

Evidence · Knowledge gap

People understand rates only after contacting support.

Recommended action

Surface rate examples before the first sharing session.

01Capture

02Cluster

03Verify evidence

04Measure impact