System: MWMS
Document Type: Framework
Authority Level: MCR Source Of Truth
Status: Draft For MCR
Version: v1.0
Primary Location: MCR
Future Operational Destination: AIBS Brain, Customer Brain, Sales Brain, Automation Brain, Data Brain, Client AIOS Systems
Parent Page: AIBS Brain
Owner: Martyn
Developer Boundary: Do Not Touch M’s Active Build Areas Unless Specifically Assigned
Source Of Truth: MCR
Last Reviewed: 2026-06-01
Source / Origin: AI Automations by Jack — WhatsApp / VAPI / Chatbot / Customer Communication Automation Block
MWMS Classification: Client Communication Automation Framework / AI Customer Interaction System / Voice And Messaging Automation Standard / Client-Facing AIOS Communication Layer
Primary Brain: AIBS Brain
Supporting Brains: Customer Brain, Sales Brain, Automation Brain, Data Brain, Risk Brain, Compliance Brain, SIT Brain, Product Brain, HeadOffice Brain
Related Pages: MWMS n8n Operating And Deployment Standard, MWMS Lead Intake Qualification And Follow-Up Automation Framework, MWMS Client Intelligence Report Automation Framework, MWMS AI Agent Memory And Context Framework, MWMS Supabase RAG And Vector Memory Framework, MWMS Client AI Interface Selection Framework, MWMS AI Dashboard Capability Framework, MWMS AI Tool Permission And Access Framework, MWMS AI Automation Security And Risk Checklist, MWMS Advanced AI Capability Activation Registry, MWMS AI Agent Operations Core, MWMS Automation Build Planning Framework, MWMS Automation Client Demo And Handover Framework

Purpose

The purpose of the MWMS Client Communication Automation Framework is to define how MWMS should design, govern, automate, package, and safely deploy AI-assisted communication workflows for clients and internal systems.

This framework covers communication channels such as:

WhatsApp
voice AI
chatbots
website chat
SMS-style messaging
customer support messages
sales inquiries
group messages
inbound customer questions
AI receptionist flows
AI support assistants
AI sales assistants
AI follow-up systems

This framework exists because communication automation is one of the most commercially powerful AIBS opportunities.

Businesses lose money when they:

miss messages
reply too slowly
answer inconsistently
fail to qualify inquiries
forget follow-ups
lose customer context
repeat the same answers manually
fail to escalate urgent issues
fail to learn from repeated customer questions

AI communication automation can help solve these problems.

But communication automation is also risky.

It touches real customers, real prospects, real messages, private information, business reputation, and sometimes regulated topics.

Therefore, MWMS must treat communication automation as a governed client-facing system, not a casual chatbot or quick n8n workflow.

Core Doctrine

The MWMS doctrine is:

AI communication systems must respond usefully, route safely, remember carefully, escalate quickly, and improve the business over time.

A client communication system should not only answer messages.

It should:

understand the message type
classify intent
retrieve approved knowledge
route to the right path
respond within scope
collect missing details
hand off when needed
log the interaction
identify repeated issues
create business intelligence
improve future FAQs, offers, content, and support systems

Communication automation becomes valuable when it creates better customer experience and better business intelligence.

Strategic Importance

This framework is strategically important because communication systems sit close to revenue and customer trust.

AIBS client packages can use communication automation for:

lead qualification
customer support
appointment confirmation
missed-call recovery
sales inquiry handling
onboarding support
FAQ handling
WhatsApp group reporting
voice receptionist workflows
service business response systems
post-call intelligence reports

This gives AIBS strong future product opportunities.

The strongest future client packages may include:

AI WhatsApp Customer Assistant
AI Voice Receptionist
AI Sales Inquiry Assistant
AI Customer Support Router
AI Appointment Confirmation Agent
AI Lead Qualification Chatbot
AI Customer Intelligence Digest
AI FAQ Improvement System

These are easy for clients to understand because they connect directly to customers.

Definition

A Client Communication Automation is a workflow or AI system that receives, interprets, responds to, routes, logs, or analyses messages, calls, chats, inquiries, or customer conversations.

MWMS Definition

An MWMS Client Communication Automation is:

A governed AI-assisted communication workflow that receives messages or calls, classifies intent, retrieves approved context, responds or routes safely, logs the interaction, and creates business value through faster response, better qualification, improved support, or customer intelligence.

Communication Channels

MWMS recognises the following communication channels.

1. WhatsApp

WhatsApp is useful for:

customer inquiries
sales messages
service coordination
group discussions
support follow-up
appointment reminders
community intelligence
client team communication

Benefits

familiar to many users
high open rates
conversational
strong in many markets
useful for service businesses
good for quick follow-up

Risks

account/session risk
privacy risk
wrong-chat response
group-message sensitivity
customer consent issues
unofficial API/provider risk
message volume/spam risk
accidental response to wrong person or group

MWMS Rule

WhatsApp automation must filter by approved contact, chat, group, or workflow scope.

Do not let automation respond to every incoming WhatsApp message by default.

2. Voice AI

Voice AI is useful for:

AI receptionists
missed-call recovery
appointment confirmation
inbound FAQs
lead qualification
customer support triage
booking reminders
sales inquiry handling

Benefits

natural interface
fast customer experience
useful for phone-heavy businesses
high perceived value
strong AIBS commercial potential

Risks

consent/recording rules
customer frustration
incorrect spoken answers
poor escalation
sensitive topics
brand reputation
call logging privacy
accent/language issues
hallucinated policy or pricing

MWMS Rule

Voice AI must have script boundaries, approved knowledge, handoff logic, and risk escalation before customer use.

3. Website Chatbot

Website chatbots are useful for:

FAQ handling
lead qualification
support triage
service recommendations
booking prompts
onboarding guidance
product/service questions

Benefits

easy client adoption
always available
can connect to RAG
can collect lead details
can reduce repetitive support

Risks

stale knowledge
unsupported claims
privacy issues
no handoff path
over-answering
wrong client knowledge
collecting sensitive data accidentally

MWMS Rule

A chatbot must know its approved knowledge source, memory boundary, tool access, and handoff triggers.

4. SMS / Short Message Follow-Up

SMS or similar short-message channels may support:

appointment reminders
follow-up prompts
lead recovery
confirmation messages
urgent updates

Risks

consent rules
opt-out requirements
spam complaints
wrong recipient
over-messaging

MWMS Rule

Short-message automation must be permissioned, minimal, and tied to a clear user relationship.

5. Email Communication

Email may support:

follow-up sequences
proposal delivery
report delivery
onboarding
lead nurture
support summaries
human handoff confirmation

Risks

spam compliance
wrong recipient
sensitive attachments
unsupported claims
unreviewed AI copy

MWMS Rule

Email automation must match consent, purpose, recipient, and review requirements.

Core Communication Workflow Pattern

The standard MWMS communication automation pattern is:

Message or call received
Source/channel verified
User/contact identified
Intent classified
Risk level assessed
Context retrieved
Route selected
Response generated or action triggered
Human handoff if required
Interaction logged
Intelligence extracted
Follow-up or improvement created

Stage 1: Message Or Call Received

The workflow begins when communication enters through:

WhatsApp
VAPI
chatbot
website form
SMS tool
email
voice call
webhook
CRM inbox
support inbox
client portal

Rule

The source channel must be known before response.

Stage 2: Source / Channel Verified

The system must verify where the message came from.

For WhatsApp, this may include:

chat ID
group ID
contact ID
sender number
approved account
approved group
approved workflow

For voice AI, this may include:

caller ID
call source
client account
assistant ID
tool call source

Rule

Do not respond unless the channel and source are inside the approved automation scope.

Stage 3: User / Contact Identified

The system should identify who is communicating.

Possible identity sources:

phone number
email
CRM record
WhatsApp sender
chatbot session
booking record
client database
previous conversation memory

Rule

If identity affects the response, identity must be verified or treated as uncertain.

Stage 4: Intent Classified

Communication must be classified before response.

Possible intents:

sales inquiry
support question
booking request
complaint
cancellation request
refund request
pricing question
urgent issue
technical issue
FAQ
spam
existing customer
new lead
human request
unknown

Rule

Do not use the same response path for every message.

Intent determines routing.

Stage 5: Risk Level Assessed

Some messages are safe to answer automatically.

Others need escalation.

High-risk categories include:

complaint
refund
cancellation
legal issue
payment issue
sensitive personal data
health/finance/legal advice
angry customer
public reputation issue
security issue
unclear account-specific request
customer asks for human

Rule

Risk determines automation authority.

Stage 6: Context Retrieved

The system may retrieve context from:

approved FAQ
client knowledge base
Supabase RAG
CRM record
product database
order database
booking system
previous conversation
support policy
workflow state
dashboard record

Rule

Communication responses must use approved context, not unsupported general AI knowledge.

Stage 7: Route Selected

Routing may send the message to:

AI response path
human support
sales team
booking workflow
complaint escalation
lead qualification workflow
FAQ response
proposal workflow
report workflow
CRM update
no-response / ignore path

Rule

Routing must be defined before automation scales.

Stage 8: Response Generated Or Action Triggered

The system may:

send a reply
ask a clarifying question
provide approved information
request missing details
create a CRM record
create a task
book a call
trigger follow-up
escalate to human
generate a report
update a dashboard

Rule

External replies and actions require tool permission governance.

Stage 9: Human Handoff If Required

Human handoff is required when:

user asks for a human
AI confidence is low
issue is sensitive
complaint or refund appears
pricing/scope is unclear
legal/financial/health issue appears
customer is frustrated
response would require account-specific action
tool lookup fails
approved knowledge is missing
conversation loops

Rule

A communication system without handoff is not client-ready.

Stage 10: Interaction Logged

The system should log:

date/time
channel
sender/contact
intent
risk level
AI response
handoff state
source used
actions taken
follow-up needed
errors

Rule

Client communication workflows need logs for trust, support, and improvement.

Stage 11: Intelligence Extracted

After conversations, the system should extract business intelligence.

Possible intelligence:

repeated questions
customer objections
product confusion
support problems
missing FAQ items
sales opportunities
complaint themes
content ideas
website improvement ideas
onboarding gaps

Rule

Communication automation should teach the business what customers are asking.

Stage 12: Follow-Up Or Improvement Created

The system may create:

sales follow-up task
support ticket
FAQ update request
website copy improvement
product knowledge update
dashboard alert
report item
client intelligence insight
nurture sequence
appointment confirmation

Rule

Good communication automation improves the business after the message ends.

WhatsApp Automation Standard

WhatsApp automation requires special care.

Approved Use Cases

approved client inquiry flow
support triage
appointment confirmation
lead follow-up
group intelligence report
sales inquiry routing
internal team digest

Avoid

responding to all messages automatically
joining or scraping groups without permission
sending bulk spam
storing unnecessary private messages
exposing group content
using personal WhatsApp accounts without boundaries
replying without intent classification

Required Fields

A WhatsApp workflow should identify:

Account:
Chat ID:
Group ID:
Sender:
Approved Chat / Group:
Message Type:
Intent:
Response Allowed: Yes / No
Handoff Required: Yes / No
Storage Rule:
Privacy Notes:

MWMS Rule

WhatsApp automation must be scoped to approved chats, contacts, or groups.

Voice AI Automation Standard

Voice AI workflows must be more controlled than text chat because voice responses happen live.

Voice AI Should Define

Assistant Role:
Business / Client:
Caller Type:
Approved Knowledge:
Script Boundaries:
Allowed Actions:
Forbidden Topics:
Tool Calls:
Handoff Path:
Call Summary:
Post-Call Report:
Consent / Disclosure Rule:
Logging:

Voice AI Should Not

answer outside approved scope
invent policies
make pricing commitments
handle sensitive complaints without escalation
continue when caller asks for human
hide that it is automated if disclosure is required
call tools without permission

MWMS Rule

Voice AI should produce post-call intelligence, not just a call response.

Chatbot Automation Standard

A chatbot should define:

Purpose:
User Type:
Scope:
Approved Knowledge:
Memory Type:
RAG Source:
Allowed Tools:
Forbidden Actions:
Handoff Trigger:
Escalation Owner:
Logging:
Fallback Response:

Chatbot Must Know

what it can answer
what it cannot answer
what source to use
when to ask a question
when to stop
when to hand off
what to log

MWMS Rule

A chatbot without memory, knowledge, and handoff rules is not a serious client system.

Communication Classification Model

Communication classification should identify:

Intent: What does the user want?
User Type: Lead, customer, client, team member, unknown.
Urgency: Low, normal, urgent.
Risk: Low, medium, high.
Required Context: FAQ, CRM, order, booking, knowledge base, human.
Response Type: AI response, clarifying question, task, handoff, no action.
Follow-Up: Required or not.

Example Classification Output

Intent: Pricing question
User Type: New lead
Urgency: Normal
Risk: Medium
Required Context: Approved pricing/service page
Response Type: AI may answer with approved pricing range or route to sales
Follow-Up: Create sales task if interest appears strong

Rule

Classification should determine the next step.

Approved Knowledge Rule

Client communication systems must respond from approved knowledge.

Approved knowledge may include:

FAQ
service pages
product information
pricing rules
support policies
client SOPs
booking policy
refund policy
onboarding guide
Supabase RAG source
CRM record
current dashboard data

Rule

Do not let AI invent business policy.

Memory Rule

Communication systems may use memory, but memory must be scoped.

Memory may include:

current conversation
session state
previous inquiry
customer preference
CRM note
support history
lead status
client-specific rule

Memory must not include:

unrelated customer data
wrong-client records
sensitive data beyond need
stale facts treated as current
casual statements saved permanently without approval

Rule

Conversation memory helps continuity.

It does not override approved knowledge or current evidence.

Tool Access Rule

Communication automation may use tools such as:

WhatsApp providers
VAPI
Unipile
GoHighLevel
Supabase
Airtable
Google Sheets
Gmail
Google Calendar
CRM systems
RAG tools
booking systems
email tools
SMS tools
PDF/report tools

Tool access must define:

allowed action
data read/write permission
external message permission
human approval need
logging requirement
error handling

Rule

Sending a message is an external action.

It requires permission.

Human Handoff Standard

A handoff should include enough context for a human to continue without asking the customer to repeat everything.

Handoff Context Pack

Customer / User:
Channel:
Conversation Summary:
Intent:
Known Facts:
Missing Facts:
Actions Already Taken:
AI Response Given:
Sources Used:
Risk Flags:
Customer Sentiment:
Recommended Human Action:
Urgency:
Owner:

Rule

Good handoff preserves context but minimizes unnecessary sensitive data.

Post-Interaction Intelligence Standard

After communication ends, the system should extract learning where useful.

Possible Learning Outputs

FAQ gap
product confusion
pricing objection
service objection
competitor mention
sales opportunity
complaint theme
support issue
content idea
onboarding issue
customer sentiment
website improvement idea

Rule

Every repeated customer question should improve the client knowledge system.

Communication Dashboard Integration

Communication systems can feed dashboards.

Dashboard items may show:

new inquiries
unresolved messages
handoffs required
lead quality
complaints
repeated questions
call summaries
support trends
sales opportunities
AI response volume
unanswered topics
high-risk conversations

Rule

Communication dashboards should show what needs action, not just message counts.

Client Intelligence Report Integration

Communication automation can feed client intelligence reports.

Examples:

monthly FAQ gap report
customer complaint themes
WhatsApp group digest
call summary report
sales objection report
lead inquiry trend report
support issue report
service improvement report

Rule

Customer conversations should become business intelligence where appropriate.

Client Package Models

This framework can support several AIBS packages.

Package 1: AI WhatsApp Customer Assistant

Handles approved WhatsApp inquiries, classifies intent, answers FAQs, routes high-risk messages, and logs interactions.

Package 2: AI Voice Receptionist

Answers inbound calls, handles basic inquiries, collects details, routes urgent issues, and produces call summaries.

Package 3: AI Sales Inquiry Assistant

Classifies sales inquiries, asks qualifying questions, retrieves service knowledge, and creates sales follow-up tasks.

Package 4: AI Support Router

Receives support messages, classifies issue type, suggests approved answers, and escalates when required.

Package 5: AI Appointment Confirmation Agent

Confirms appointments, handles simple rescheduling flows, sends reminders, and flags no-show risks.

Package 6: Communication Intelligence Digest

Summarizes calls/messages/chats into weekly or monthly business insight reports.

Minimum Viable Client Communication Product

Recommended MVP:

AI Support And Sales Inquiry Router

Inputs:

website chat or WhatsApp inquiry
approved FAQ/service knowledge
basic CRM/store/contact context

Outputs:

intent classification
approved response or clarifying question
human handoff when needed
lead/support task
interaction log
weekly insight summary

Why this is strong:

easy to understand
solves real client pain
lower risk than full autonomous agent
creates visible value
can expand into voice later

MWMS Rule

Start with routing and assisted responses before full autonomous customer communication.

Build Path

Stage 1: Define Channel

Choose:

WhatsApp
chatbot
voice
email
SMS
hybrid

Stage 2: Define Use Case

Examples:

support
sales inquiry
appointment
FAQ
lead qualification
internal digest

Stage 3: Define Approved Knowledge

Create or identify:

FAQ
service info
pricing rules
policies
support SOP
CRM data
RAG source

Stage 4: Define Classification

Set intent categories and risk levels.

Stage 5: Define Response Rules

Decide what AI can answer and what it must not answer.

Stage 6: Define Handoff

Set handoff triggers and human owner.

Stage 7: Build Workflow

Use n8n/Make/Supabase/CRM/RAG/tools.

Stage 8: Test With Realistic Messages

Test:

normal inquiry
unclear inquiry
angry customer
pricing question
complaint
human request
missing context
tool failure

Stage 9: Launch With Monitoring

Start with assisted or reviewed mode where possible.

Stage 10: Improve From Logs

Use logs to improve FAQs, routing, content, and response templates.

Launch Readiness Checklist

Before launching communication automation, confirm:

channel is defined
client use case is clear
approved knowledge exists
scope is defined
prohibited topics are defined
tool access is permissioned
message source is filtered
intent classification is tested
risk classification exists
human handoff exists
fallback response exists
logging exists
sensitive data rules exist
consent/privacy considered
client identity isolation exists
response templates tested
hallucination controls exist
dashboard/reporting path exists
error handling exists
owner assigned
monitoring process defined

Failure Modes

Failure Mode 1: Automation Responds To Everything

The system responds to every incoming message without filtering.

Correction:

Filter by approved channel, chat, contact, group, or workflow.

Failure Mode 2: No Handoff

AI continues when human support is needed.

Correction:

Add handoff triggers and escalation owner.

Failure Mode 3: AI Invents Policy

AI answers pricing, refund, or service rules from general knowledge.

Correction:

Use approved knowledge source only.

Failure Mode 4: Wrong Customer Context

AI uses the wrong CRM/contact/client data.

Correction:

Add identity verification and client/contact filters.

Failure Mode 5: Sensitive Data Stored Unnecessarily

Conversation logs store more than needed.

Correction:

Apply data minimization and retention rules.

Failure Mode 6: Voice Agent Frustrates Customer

Caller gets trapped in AI loop.

Correction:

Add quick human transfer and call failure handling.

Failure Mode 7: WhatsApp Group Privacy Breach

Private group content is processed or reported without permission.

Correction:

Require explicit group approval and minimization.

Failure Mode 8: No Learning Loop

Same customer questions repeat but FAQ never improves.

Correction:

Create post-interaction intelligence and FAQ update process.

Failure Mode 9: Tool Call Fails Silently

AI says it checked information when tool failed.

Correction:

Log tool failure and use fallback response.

Failure Mode 10: Client Thinks AI Is Fully Autonomous

Client expects system to handle all cases.

Correction:

Define scope, limits, and handoff clearly.

Application To AIBS Brain

AIBS Brain owns this framework because communication automation is a client-facing product area.

AIBS should package communication systems around outcomes:

faster response
fewer missed inquiries
better qualification
lower support load
clearer handoffs
better customer intelligence
visible reporting

AIBS Rule

Sell improved customer communication, not “chatbot automation.”

Application To Customer Brain

Customer Brain should define customer experience standards.

Customer Brain owns:

customer tone
support boundaries
escalation rules
FAQ improvements
complaint handling
customer journey alignment
post-interaction learning

Customer Rule

Automation must improve customer experience, not just reduce workload.

Application To Sales Brain

Sales Brain should define sales inquiry and lead qualification logic.

Sales Brain owns:

inquiry classification
sales questions
qualification routing
follow-up tasks
booking prompts
proposal handoff
objection capture

Sales Rule

Communication automation should identify and protect sales opportunities.

Application To Automation Brain

Automation Brain builds and maintains workflows.

Automation Brain owns:

webhooks
API integrations
channel connections
routing logic
tool calls
message delivery
error handling
logs
dashboard connections

Automation Rule

Communication workflows must be tested with real-world messy messages.

Application To Data Brain

Data Brain governs stored communication data.

Data Brain owns:

conversation logs
contact records
CRM linkage
source metadata
client isolation
retention rules
message classification data
reporting data

Data Rule

Communication data is sensitive and must be stored deliberately.

Application To Risk And Compliance Brain

Risk and Compliance Brain must review communication systems involving:

customer messages
WhatsApp
SMS
voice calls
recording/transcripts
personal data
sensitive topics
automated replies
support claims
pricing/refund information
public-facing customer communication

Risk Rule

The closer automation gets to live customers, the stronger the governance required.

Application To SIT Brain

SIT Brain should test communication systems.

SIT should test:

approved message
unapproved message
wrong group
unknown user
repeated question
angry customer
refund request
human request
tool failure
RAG failure
missing knowledge
wrong client ID
escalation
logging
response quality

SIT Rule

Communication automation must be tested for customer edge cases before launch.

Related AI Employee Capabilities

Communication Workflow Architect

Designs channel, intent categories, routing, tools, handoff, and logging.

Message Classification Agent

Classifies incoming messages by intent, user type, urgency, and risk.

Approved Response Agent

Generates responses only from approved knowledge and within scope.

Handoff Coordinator Agent

Creates human handoff context packs and routes to the correct owner.

Voice Interaction Reviewer

Reviews voice AI call logs, call quality, and escalation failures.

WhatsApp Scope Guard Agent

Checks whether WhatsApp messages come from approved chats or groups.

Customer Intelligence Extractor

Extracts repeated questions, objections, complaints, and improvement opportunities.

FAQ Improvement Agent

Turns repeated communication patterns into approved FAQ updates.

Future Expansion

This framework may later produce:

MWMS WhatsApp AI Customer Assistant Framework
MWMS Voice AI Receptionist Governance Framework
MWMS Chatbot Memory And Handoff Standard
MWMS Customer Communication Logging Standard
MWMS AI Support Router Framework
MWMS AI Appointment Confirmation Framework
MWMS Communication Intelligence Digest Framework

These should be created only when the related system moves into active build or client package design.

Strategic Summary

This block confirms that client communication automation is one of the strongest AIBS opportunities.

The key insight is:

Communication automation should not just reply.
It should classify, retrieve, respond, route, log, hand off, and learn.

The most important commercial opportunities are:

AI WhatsApp Customer Assistant
AI Voice Receptionist
AI Sales Inquiry Assistant
AI Support Router
AI Appointment Confirmation Agent
Communication Intelligence Digest

However, this area requires strong governance because it touches customers directly.

The best first version is not full autonomy.

The best first version is:

AI Support And Sales Inquiry Router with approved responses and human handoff.

That gives clients value while keeping risk controlled.

Final Standard

The MWMS standard is:

Client communication automation must be scoped, permissioned, source-aware, logged, handoff-ready, and customer-safe.
AI may assist communication, but it must not invent policy, ignore risk, bypass human escalation, or respond outside approved scope.

Communication automation is not just messaging.

It is a customer experience system.

Change Log

Version: v1.0
Date: 2026-06-01
Author: MWMS HeadOffice

Change:

Created the MWMS Client Communication Automation Framework from the AI Automations by Jack WhatsApp, VAPI, chatbot, customer support, and communication automation block.

Captured the core workflow pattern: message/call received → source verified → user/contact identified → intent classified → risk assessed → context retrieved → route selected → response/action generated → human handoff if required → interaction logged → intelligence extracted → follow-up/improvement created.

Defined client communication automation as a governed AI-assisted communication workflow that receives messages or calls, classifies intent, retrieves approved context, responds or routes safely, logs the interaction, and creates business value through faster response, better qualification, improved support, or customer intelligence.

Added channel standards for WhatsApp, Voice AI, Website Chatbots, SMS/Short Message Follow-Up, and Email Communication.

Added dedicated standards for WhatsApp automation, Voice AI automation, chatbot automation, communication classification, approved knowledge, memory, tool access, human handoff, post-interaction intelligence, dashboard integration, and client intelligence report integration.

Added future client package models including AI WhatsApp Customer Assistant, AI Voice Receptionist, AI Sales Inquiry Assistant, AI Support Router, AI Appointment Confirmation Agent, and Communication Intelligence Digest.

Added Minimum Viable Client Communication Product recommendation: AI Support And Sales Inquiry Router.

Added Build Path, Launch Readiness Checklist, and failure modes covering responding to everything, missing handoff, invented policy, wrong customer context, unnecessary sensitive data storage, voice frustration, WhatsApp group privacy breach, missing learning loop, silent tool failure, and client expectations of full autonomy.

Mapped responsibilities across AIBS Brain, Customer Brain, Sales Brain, Automation Brain, Data Brain, Risk Brain, Compliance Brain, and SIT Brain.

Added related AI Employee capabilities: Communication Workflow Architect, Message Classification Agent, Approved Response Agent, Handoff Coordinator Agent, Voice Interaction Reviewer, WhatsApp Scope Guard Agent, Customer Intelligence Extractor, and FAQ Improvement Agent.

Purpose of creation:

To establish client communication automation as a governed AIBS capability and future client-facing AIOS layer, covering WhatsApp, voice AI, chatbots, support routing, sales inquiries, approved responses, human handoff, interaction logging, and post-interaction customer intelligence.