System: MWMS
Document Type: Framework
Authority Level: MCR Source Of Truth
Status: Draft For MCR
Version: v1.0
Primary Location: MCR
Future Operational Destination: Sales Brain, Research Brain, Data Brain, AIBS Brain, HeadOffice Brain, AI Manager, AI Employee Router, Task Executor Systems, Client Acquisition Systems, Client Discovery Systems
Parent Page: Sales Brain
Owner: Martyn
Developer Boundary: Do Not Touch M’s Active Build Areas Unless Specifically Assigned
Source Of Truth: MCR
Last Reviewed: 2026-06-20
Source / Origin: AI Automations by Jack — Lesson 143 NotebookLM And AntiGravity Meeting Intelligence Workflow
MWMS Classification: Sales Intelligence Framework / Prospect Research Framework / Pre-Call Preparation System / Client Discovery Intelligence System
Primary Brain: Sales Brain
Supporting Brains: Research Brain, Data Brain, AIBS Brain, HeadOffice Brain
Related Pages: MWMS Founder Led Sales And First Client Deal Flow Framework, MWMS AI Assisted Outreach And Sales Follow Up Automation Framework, MWMS Lead Intake Qualification And Follow-Up Automation Framework, MWMS High-Ticket AIOS Client Acquisition And Trophy Client Framework, MWMS AI Audit Diagnostic And Paid Roadmap Framework, MWMS Right-Fit Client And Offer Profile Standard, MWMS Research Planning And Query Rewriting Standard, MWMS Research Synthesis Documentation And Distribution Framework, MWMS External Knowledge Engine And Reasoning Agent Separation Framework, MWMS RAG Knowledge Base And Client Memory Infrastructure Framework, MWMS Proof Library And Claims Control Standard, MWMS Proposal Structure Framework, Sales Brain Conversation Structure Framework, Sales Brain Offer Fit Interpretation Framework, Sales Brain Expectation Alignment Framework, Sales Brain Trust Reinforcement Framework, Sales Brain Follow Up Continuity Framework
Source Evidence: The source lesson presents a workflow that begins with a company or prospect name and produces a structured meeting-preparation package using company research, professional profiles, market sources, competitive analysis, executive briefing, visual summaries, presentations, dashboards and learning assets. The durable value is not the specific software combination. It is the governed conversion of dispersed prospect information into decision-ready pre-call intelligence.
MCR Duplication Check: No existing page titled MWMS AI Meeting Intelligence And Pre-Call Preparation Framework or a clearly equivalent standalone Sales Brain framework was identified in the supplied MCR page list. Existing Sales Brain pages cover conversation structure, offer fit, expectation alignment, sales progression, trust and follow-up, but do not establish the complete pre-call intelligence workflow defined here.
Purpose
The purpose of this document is to define the MWMS AI Meeting Intelligence And Pre-Call Preparation Framework.
This framework establishes how MWMS researches, verifies, organises and converts information about a prospect, company, partner, client, vendor or strategic opportunity into a decision-ready meeting intelligence package.
The framework exists because effective meetings should not begin with basic discovery that could have been completed beforehand.
Before an important meeting, MWMS should already understand:
who the organisation is
what it sells
who it serves
how it makes money
what stage it appears to be in
what problems it may face
what priorities it may currently have
who the relevant decision-makers are
what technology or systems it appears to use
what competitors and market pressures affect it
what evidence supports each conclusion
where uncertainty remains
how MWMS may create value
what questions must still be asked
what outcome the meeting should pursue
The purpose is not to create an impressive pile of research.
The purpose is to improve:
meeting relevance
questioning quality
prospect understanding
offer alignment
trust
authority
qualification
sales efficiency
proposal quality
follow-up continuity
client discovery
decision-making
This framework turns raw external information into practical meeting intelligence.
Scope
This framework applies to preparation for:
sales discovery calls
client diagnostic meetings
AIBS consultation calls
partnership discussions
vendor evaluations
strategic alliance meetings
acquisition conversations
agency prospect calls
service scoping calls
proposal meetings
account reviews
renewal discussions
internal executive reviews
high-value networking meetings
investor or adviser conversations
employment or contractor interviews where organisational research is required
This framework may be used by:
Martyn
HeadOffice
Sales Brain
Research Brain
Data Brain
AIBS Brain
AI Employees
future sales support employees
future client acquisition employees
future account management employees
This framework applies to manual and AI-assisted research.
It does not authorise uncontrolled scraping, unauthorised data access, impersonation, invasive personal profiling or automatic contact with a prospect.
Core Definition
Meeting Intelligence is the verified, organised and decision-relevant understanding of a person, company, opportunity and surrounding market that MWMS prepares before an important conversation.
Pre-Call Preparation is the process of converting that intelligence into:
meeting objectives
verified facts
working hypotheses
priority questions
opportunity themes
risk flags
offer-fit considerations
conversation guidance
recommended next steps
Meeting intelligence is not the same as a generic company summary.
A generic company summary may describe:
what the company says it does
when it was founded
who works there
what appears on its website
A proper meeting intelligence package must also determine:
why this meeting matters
what may be commercially relevant
what is known
what is inferred
what remains unknown
what should be tested during the meeting
what MWMS should avoid assuming
how the conversation should progress
Core Principle
The core principle of this framework is:
Research should reduce avoidable ignorance before the meeting without pretending to replace the meeting.
Public information can reveal:
signals
patterns
likely priorities
possible problems
strategic context
useful questions
It cannot reliably reveal every internal fact.
Therefore:
facts must remain facts
claims must remain claims
hypotheses must remain hypotheses
unknowns must remain visible
the meeting must validate what research cannot confirm
The framework prepares MWMS to ask better questions.
It does not authorise MWMS to act as though every inference is true.
Strategic Value
Strong pre-call intelligence helps MWMS:
enter meetings with context
avoid generic questioning
recognise likely business priorities
identify offer-fit faster
demonstrate preparation
build credibility
detect weak-fit prospects earlier
protect time
improve discovery
improve pricing conversations
create stronger proposals
personalise follow-up
identify cross-Brain opportunities
retain useful account knowledge
improve future client service
Poor pre-call preparation creates:
repeated basic questions
weak authority
irrelevant pitching
missed buying signals
shallow proposals
incorrect assumptions
wasted meeting time
poor follow-up
weak qualification
reduced trust
Meeting Intelligence Layers
The MWMS AI Meeting Intelligence And Pre-Call Preparation Framework uses twelve layers:
Meeting Purpose
Entity Identification
Source Planning
Company Intelligence
People And Decision-Maker Intelligence
Market And Competitive Intelligence
Operational And Technology Signals
Problem And Opportunity Hypotheses
Offer-Fit Interpretation
Meeting Strategy
Intelligence Package Production
Post-Meeting Knowledge Commitment
Meeting Purpose
Research must begin with the purpose of the meeting.
Before research starts, define:
meeting type
reason for the meeting
attendees
expected duration
current relationship stage
likely decision stage
desired meeting outcome
what MWMS needs to learn
what the prospect may need to learn
what decision may follow
Possible meeting purposes include:
initial qualification
problem discovery
AIBS diagnostic
service scoping
proposal review
partnership exploration
renewal review
strategic planning
implementation review
account expansion
vendor evaluation
Meeting Purpose Rule
Do not conduct broad research without knowing which decision or conversation it must support.
Entity Identification
MWMS must confirm the exact entity being researched.
Entity identification should include:
legal or trading name
website
location
industry
relevant business unit
relevant product or service
prospect contact
contact role
related parent company
related brands
known meeting attendees
existing relationship history
This prevents confusion between:
companies with similar names
parent and subsidiary organisations
regional divisions
old and current websites
individual and company profiles
unrelated people sharing a name
Entity Identification Rule
No major research package should proceed until the target entity is sufficiently disambiguated.
Source Planning
Research should use a deliberate source plan rather than indiscriminate browsing.
Possible source categories include:
Primary Sources
official company website
official product pages
official pricing
official documentation
official news releases
official job listings
official social accounts
official leadership profiles
published reports
public filings where relevant
Professional And Business Sources
Crunchbase
industry directories
partner directories
conference profiles
association records
marketplace listings
app directories
review platforms
Market Sources
competitor websites
industry reports
analyst commentary
trade publications
customer discussions
search demand
public reviews
job market signals
technology intelligence sources
Existing MWMS Sources
prior emails
CRM or contact notes
previous meeting records
proposal history
Research Brain records
AIBS diagnostic records
relevant MCR frameworks
client documents supplied with permission
Source Planning Rule
Use the smallest source set that provides sufficient reliable coverage.
More sources do not automatically create better intelligence.
Company Intelligence
Company intelligence should establish the organisation’s observable business context.
Research may include:
Company Identity
company description
business model
core products
core services
locations
operating markets
apparent size
ownership where relevant
Customer And Market
target customer
industries served
customer segments
geographical focus
pricing position
delivery model
acquisition channels
customer journey
Commercial Model
revenue model
recurring or transactional revenue
productised or custom service
sales-led or self-service motion
likely deal value
sales complexity
retention dependency
upsell potential
Growth And Change Signals
new offers
new hires
geographic expansion
new technology
partnerships
funding
acquisitions
leadership changes
restructuring
declining activity
new marketing campaigns
Company Intelligence Rule
Record what can be supported.
Do not invent revenue, profit, headcount, growth rate or internal capability merely because they appear likely.
People And Decision-Maker Intelligence
Meeting preparation should include relevant professional information about the attendees and likely decision group.
Useful professional information may include:
current role
responsibilities
tenure
professional background
public expertise
published priorities
recent professional activity
authority signals
likely involvement in the problem
relationship to other decision-makers
Possible decision roles include:
Economic Buyer
Operational Buyer
Technical Buyer
User
Champion
Influencer
Blocker
Procurement
Legal Or Compliance Reviewer
Final Approver
Personal Intelligence Boundary
MWMS should research professionally relevant public information.
MWMS should not build invasive dossiers using unrelated personal details.
Do not collect or use:
sensitive personal information
private family information
personal vulnerabilities
protected characteristics
irrelevant lifestyle data
information obtained through deceptive access
People Intelligence Rule
Use professional context to improve relevance and respect.
Do not use personal information to manipulate.
Market And Competitive Intelligence
Meeting intelligence should place the prospect inside its broader market.
Research may include:
direct competitors
indirect competitors
category alternatives
market positioning
pricing patterns
common customer expectations
category growth or decline
regulatory pressure
technology changes
platform dependence
common operational problems
emerging opportunities
major market risks
Competitive intelligence should identify:
what competitors promise
how they differentiate
where the prospect appears stronger
where the prospect appears weaker
where the category looks commoditised
where buyer expectations may be changing
Competitive Intelligence Rule
The purpose is not to produce a long competitor list.
The purpose is to understand the commercial environment affecting the meeting.
Operational And Technology Signals
Public evidence may reveal aspects of the prospect’s operational environment.
Possible signals include:
website platform
analytics tools
advertising platforms
CRM indicators
support systems
booking systems
ecommerce platforms
email systems
automation tools
forms
tracking gaps
broken workflows
response friction
review patterns
content cadence
job listings
integration requirements
Technology signals may help MWMS identify:
likely system fragmentation
manual work
missing integration
reporting gaps
lead leakage
customer-service friction
data silos
outdated workflows
automation opportunities
Technology Signal Rule
A detected tool does not prove how well the company uses it.
Technology presence and operational maturity must not be treated as the same thing.
Problem And Opportunity Hypotheses
Research should produce hypotheses for validation.
A hypothesis may state:
the prospect may be losing leads because follow-up appears fragmented
the company may lack a unified reporting view
repeated customer questions may be consuming staff time
the current website may not support the desired positioning
the business may have useful data that is not being converted into decisions
staff may be repeating tasks that could be systemised
the company may be ready for an AI audit before implementation
leadership may lack a reliable operational dashboard
Each hypothesis should include:
Hypothesis:
Evidence:
Confidence:
Possible Business Impact:
Meeting Question:
Disconfirming Evidence Required:
Recommended Confidence Values
Low
Medium
High
Hypothesis Rule
A hypothesis must never be presented as an established client problem until the meeting confirms it.
Offer-Fit Interpretation
Meeting intelligence should help determine whether MWMS has a relevant offer.
Possible offer-fit categories include:
AI Audit And Diagnostic
Paid Roadmap
Productized AIOS Service
Lead Capture And Follow-Up System
Review And Reputation System
Reporting And Dashboard System
Knowledge And Memory System
Content Intelligence System
Sales Support System
Workflow Automation
Research And Intelligence System
Custom AIBS Engagement
No Current Fit
Offer-fit interpretation should consider:
problem severity
urgency
economic value
authority
existing capability
implementation readiness
data availability
team willingness
budget signals
risk
MWMS delivery capability
expected return
Offer-Fit Rule
Do not force the prospect into an MWMS offer.
Use research to identify possible fit.
Use discovery to confirm actual fit.
Meeting Strategy
Research must be converted into an actionable meeting plan.
The meeting strategy should define:
Meeting Objective
What should be achieved by the end of the meeting?
Primary Learning Goals
What must MWMS understand?
Opening Context
How should MWMS demonstrate preparation without overwhelming the prospect?
Priority Questions
Which questions have the highest decision value?
Hypotheses To Test
Which researched assumptions require confirmation?
Proof To Use
Which MWMS examples, frameworks or results may be relevant?
Offer Themes
Which possible solutions may be appropriate if the evidence supports them?
Risk Areas
Which issues require caution?
Desired Next Step
What logical commitment should follow?
Meeting Strategy Rule
The goal is not to recite the research package.
The goal is to conduct a better conversation.
Intelligence Package Production
The standard MWMS Meeting Intelligence Package should contain only decision-relevant material.
Required Sections
Meeting Overview
prospect or company
meeting date
meeting type
attendees
relationship stage
desired outcome
Executive Brief
A concise explanation of:
who the organisation is
what it appears to do
why the meeting matters
what may be commercially relevant
Verified Company Facts
business model
products or services
target customers
locations
leadership
observable growth or change signals
Relevant People
attendees
roles
professional responsibilities
likely decision involvement
Market Context
category
competitors
market pressure
relevant trends
Operational And Technology Signals
systems observed
workflow signals
customer experience signals
data or integration signals
Problem And Opportunity Hypotheses
hypothesis
evidence
confidence
validation question
Offer-Fit Possibilities
potential fit
reasoning
conditions that must be confirmed
Priority Questions
qualification questions
discovery questions
impact questions
authority questions
readiness questions
next-step questions
Risks And Unknowns
missing information
conflicting evidence
weak sources
assumptions
possible deal risks
Conversation Plan
opening
priority topics
proof
transitions
desired next step
Source Record
source
source type
date accessed
authority level
relevant finding
Optional Assets
Where justified, the package may also include:
competitor comparison
market infographic
technology map
relationship map
decision-maker map
executive slide deck
opportunity dashboard
account timeline
pre-meeting audio summary
meeting question card
learning quiz or flashcards for complex accounts
Optional Asset Rule
Do not create media merely because a tool can generate it.
Create an optional asset only when it materially improves preparation, understanding or communication.
Post-Meeting Knowledge Commitment
The workflow does not end when the meeting begins.
After the meeting, MWMS should compare:
pre-call facts
pre-call hypotheses
meeting-confirmed facts
disproven assumptions
newly discovered needs
decision authority
budget context
readiness
risks
objections
agreed next steps
The post-meeting record should capture:
what was confirmed
what was corrected
what remains unknown
what action was agreed
who owns the next action
when follow-up is due
which Brain receives the information
whether a proposal or diagnostic is required
whether the prospect should continue, pause or be disqualified
Knowledge Commitment Rule
Do not allow pre-call hypotheses to become permanent account truth unless the meeting or stronger evidence confirms them.
Meeting Intelligence Workflow
The standard MWMS workflow is:
Meeting Trigger
→ Meeting Purpose Defined
→ Entity Confirmed
→ Existing Relationship Data Checked
→ Research Questions Defined
→ Sources Collected
→ Sources Assessed
→ Company Intelligence Extracted
→ People Intelligence Extracted
→ Market Intelligence Extracted
→ Operational Signals Extracted
→ Facts Separated From Claims And Hypotheses
→ Offer-Fit Possibilities Identified
→ Meeting Strategy Created
→ Intelligence Package Validated
→ Human Review
→ Meeting Conducted
→ Meeting Evidence Captured
→ Hypotheses Confirmed Or Rejected
→ Next Action Assigned
→ Durable Account Knowledge Updated
→ Workflow Closed
Meeting Trigger Types
A Meeting Intelligence Work Unit may be triggered by:
booked sales call
qualified lead
referral introduction
partnership invitation
proposal meeting
high-value account review
AIBS diagnostic request
strategic prospect identification
founder-led outbound opportunity
vendor evaluation
client renewal
stalled deal requiring re-entry
Minimum Trigger Information
organisation or person
website or identifying information
meeting date
meeting purpose
attendees if known
relationship history
expected outcome
Research Question Design
Research should answer questions connected to the meeting.
Core Questions
What does this organisation do?
Who does it serve?
How does it appear to make money?
What appears strategically important now?
What observable problems or opportunities exist?
Who is involved in the decision?
What evidence supports each conclusion?
What does MWMS still need to learn?
What possible offer fit exists?
What should the meeting accomplish?
Research should not become an open-ended attempt to learn everything about the company.
Research Depth Levels
Level 1 — Light Preparation
Use for:
low-value introductory calls
early networking
simple supplier conversations
Includes:
company overview
attendee role
basic market context
five priority questions
Level 2 — Standard Preparation
Use for:
qualified sales calls
AIBS discovery
partnership discussions
proposal preparation
Includes:
company intelligence
attendee intelligence
market context
operational signals
hypotheses
offer-fit possibilities
meeting plan
source record
Level 3 — Strategic Preparation
Use for:
high-ticket prospects
trophy clients
complex organisations
multi-stakeholder opportunities
strategic partnerships
acquisition or investment conversations
Includes:
full company analysis
decision-group analysis
market and competitor intelligence
technology and workflow analysis
risk analysis
opportunity map
executive brief
detailed meeting strategy
optional presentation or dashboard
independent validation
Research Depth Rule
Research effort should be proportionate to:
potential value
strategic importance
complexity
uncertainty
risk
likelihood of progression
Source Authority Model
Each material finding should be assigned a source authority level.
Level A — Direct Primary Evidence
Examples:
official company page
official report
direct prospect communication
public filing
contract or client-supplied record
Level B — Strong Professional Evidence
Examples:
verified professional profile
recognised industry database
reputable trade publication
established review source
Level C — Supporting Public Evidence
Examples:
directory listing
public discussion
technology detection
third-party summary
social activity
Level D — Weak Or Unverified Signal
Examples:
anonymous claim
scraped summary without provenance
outdated listing
promotional speculation
AI-generated claim without source
Source Authority Rule
Important claims should not rely solely on Level D evidence.
Fact, Claim, Hypothesis And Unknown Separation
Every important item should be classified as one of the following.
Verified Fact
Supported by reliable evidence.
Company Claim
Stated by the company but not independently verified.
External Claim
Stated by another source.
Observed Signal
Visible evidence that may suggest a condition.
Hypothesis
A reasoned possibility requiring validation.
Unknown
Material information not currently available.
Conflict
Reliable sources disagree.
Classification Rule
The intelligence package must not blur these categories.
Evidence Record
Each significant finding should record:
Finding:
Classification:
Source:
Source Authority:
Source Date:
Date Accessed:
Confidence:
Meeting Relevance:
Required Validation:
Evidence Freshness
Research should consider whether information is current enough for the meeting.
Time-sensitive information includes:
leadership
pricing
job listings
product availability
technology use
partnerships
advertising activity
funding
customer sentiment
market conditions
Freshness Rule
Old information may provide history.
It must not automatically be treated as current operating reality.
AI Employee Role Structure
A complete meeting intelligence workflow may use the following AI Employee roles.
Meeting Intelligence Coordinator
Responsible for:
creating the Work Unit
confirming purpose
assigning research
controlling scope
assembling the package
routing for review
Company Research Agent
Responsible for:
company facts
products
services
customers
business model
growth signals
People Intelligence Agent
Responsible for:
professional role research
attendee responsibilities
decision-group mapping
relevant public activity
Market Intelligence Agent
Responsible for:
competitors
category context
trends
risks
market pressure
Operational Signal Agent
Responsible for:
technology signals
workflow indicators
customer experience signals
observable automation opportunities
Evidence Validator
Responsible for:
source authority
freshness
fact classification
contradiction detection
unsupported claim removal
Sales Strategy Agent
Responsible for:
meeting objective
hypotheses
offer-fit interpretation
questions
conversation strategy
next-step recommendation
Human Approval Owner
Responsible for:
final judgement
ethical review
relevance
removal of weak or intrusive material
approval for use
Role Design Rule
A simple call does not require eight separate agents.
Roles may be combined when risk and complexity are low.
Separation should increase only when it materially improves quality or control.
Meeting Intelligence Work Unit
Each formal meeting-preparation task should define:
Work Unit ID:
Meeting Intelligence Record ID:
Prospect Or Company:
Website:
Contact:
Meeting Date:
Meeting Type:
Relationship Stage:
Meeting Purpose:
Desired Outcome:
Potential Value:
Research Depth:
Owning Brain:
Supporting Brains:
Assigned Roles:
Known Context:
Required Sources:
Priority Questions:
Research Deadline:
Risk Level:
Human Review Required:
Output Destination:
Next Owner:
Current Status:
Research Boundaries
MWMS must not:
bypass access controls
collect private information without permission
impersonate another person
use stolen credentials
scrape prohibited data sources recklessly
collect irrelevant personal information
create discriminatory profiles
make unsupported allegations
treat rumour as fact
expose confidential client information
contact the prospect automatically without approval
publish the research package
store unnecessary sensitive information
Research Boundary Rule
Professional preparation does not justify invasive surveillance.
Question Architecture
The intelligence package should generate questions across several categories.
Context Questions
What has changed recently?
What is driving the current priority?
Why is this being considered now?
Problem Questions
Where does the current process break down?
Which part creates the most friction?
How often does the issue occur?
Impact Questions
What does the problem cost?
Who is affected?
What happens if it remains unresolved?
Current-System Questions
How is the work handled now?
Which systems are involved?
Where is information lost or duplicated?
Decision Questions
Who is involved in the decision?
What must be true for the project to proceed?
What constraints affect timing?
Readiness Questions
Is the data available?
Does the team have capacity?
Is leadership prepared to change the process?
Value Questions
What would a successful outcome mean?
Which metric would improve?
How would success be recognised?
Next-Step Questions
What should happen after this meeting?
Who needs to be involved?
What evidence is needed next?
Question Rule
Do not ask questions merely to display research.
Ask questions that improve the decision.
Opening Use Of Research
MWMS may demonstrate preparation by briefly acknowledging relevant context.
Appropriate Example
“We noticed that you have expanded into a second service area and appear to be increasing your sales team. I would like to understand how that growth is affecting lead follow-up and reporting.”
Inappropriate Example
“We investigated everything about your company and have identified all your problems.”
Opening Rule
Research should create relevance without creating discomfort or false certainty.
Offer-Fit Interpretation Model
Possible fit should be assessed across eight dimensions.
Problem Fit
Does MWMS address a real problem?
Value Fit
Could the result create meaningful value?
Authority Fit
Is the right decision group involved?
Readiness Fit
Can the organisation support implementation?
Data Fit
Is the required information available?
Delivery Fit
Can MWMS deliver the solution responsibly?
Risk Fit
Are legal, operational and reputational risks acceptable?
Relationship Fit
Does the prospect appear suitable for the way MWMS works?
Offer-Fit Verdicts
Strong Possible Fit
Possible Fit Requiring Discovery
Narrow Fit
Future Fit
Referral Fit
Poor Fit
Insufficient Evidence
Offer-Fit Rule
The pre-call verdict is provisional.
The meeting produces the operational verdict.
Meeting Intelligence Scorecard
The package may be scored across:
Entity Accuracy:
Source Quality:
Source Freshness:
Company Understanding:
Attendee Understanding:
Market Understanding:
Operational Signal Quality:
Fact And Hypothesis Separation:
Question Quality:
Offer-Fit Relevance:
Risk Visibility:
Meeting Actionability:
Suggested Ratings
Not Ready
Weak
Adequate
Strong
Meeting Ready
Meeting Ready requires:
correct entity
clear purpose
sufficient reliable sources
visible unknowns
useful hypotheses
priority questions
practical meeting strategy
human approval where required
Validation Checklist
Before use, verify:
target entity is correct
contact identity is correct
meeting purpose is clear
major facts have sources
source dates are recorded
important information is current
company claims are labelled
hypotheses are labelled
unknowns remain visible
conflicting evidence is shown
personal information is professionally relevant
no prohibited data was collected
questions are useful
offer fit is provisional
meeting objective is defined
desired next step is realistic
package length is proportionate
human review is complete
Failure Modes
Common failure modes include:
researching the wrong company
confusing parent and subsidiary
using outdated leadership information
treating company marketing claims as verified facts
using low-quality data aggregators as authority
over-researching low-value calls
creating a long report with no meeting strategy
hiding uncertainty
presenting hypotheses as known problems
collecting intrusive personal data
generating generic questions
forcing offer fit
reciting research instead of listening
failing to update the record after the meeting
storing disproven assumptions
creating unnecessary slides, podcasts or dashboards
allowing AI-generated claims to circulate without sources
Any material failure should block Meeting Ready status.
Ambiguity Handling
When information is unclear:
label the ambiguity
preserve both interpretations
identify the missing evidence
lower confidence
create a meeting question
avoid firm conclusions
When sources conflict:
record both sources
compare authority
compare freshness
seek primary evidence
escalate material conflicts
preserve the conflict if unresolved
Ambiguity Rule
Unresolved ambiguity should become a discovery question, not a hidden assumption.
Meeting Intelligence Statuses
Recommended statuses:
Requested
Scoped
Researching
Evidence Review
Strategy Draft
Human Review
Meeting Ready
Meeting Completed
Follow-Up Required
Knowledge Commitment Pending
Closed
Parked
Cancelled
Failed Validation
Status must remain visible.
A package marked Researching or Failed Validation must not be treated as Meeting Ready.
Human Review
Human review is required for:
high-ticket prospects
trophy clients
client-facing meetings
strategic partnerships
sensitive industries
legal or compliance-sensitive topics
packages containing personal information
weak or conflicting evidence
high-impact recommendations
AIBS proposals
public-sector or regulated organisations
Human review should confirm:
relevance
accuracy
ethical boundaries
appropriate tone
offer fit
question quality
meeting objective
next step
Dashboard Relevance
A meeting intelligence item may later appear in a Sales Brain or HeadOffice dashboard.
Useful fields may include:
prospect
company
meeting date
meeting type
relationship stage
potential value
research depth
readiness status
offer-fit verdict
primary opportunity
primary risk
next action
owner
Dashboard Rule
The dashboard should show readiness and action.
It should not attempt to display the entire research package.
Application To Founder-Led Sales
For Martyn’s founder-led sales, this framework should help:
prepare for high-value conversations
identify likely client problems
enter calls with relevant context
reduce generic discovery
improve authority
test AIBS fit
understand implementation readiness
determine whether a paid diagnostic is appropriate
create more relevant proposals
preserve account continuity
Founder-Led Sales Rule
Preparation should support Martyn’s judgement.
It should not replace the direct human conversation.
Application To AIBS
For AIBS opportunities, meeting intelligence should examine:
current workflows
repeated manual work
information bottlenecks
lead handling
customer communication
reporting
knowledge management
staff coordination
system fragmentation
data availability
automation readiness
risk
decision authority
potential financial value
The meeting should determine whether the prospect needs:
no action
further discovery
AI audit
paid roadmap
productized AIOS service
custom system
referral
future follow-up
AIBS Rule
Do not recommend implementation merely because an automation opportunity appears technically possible.
Application To Partnerships
For partnerships, research should examine:
strategic alignment
audience overlap
capability overlap
mutual value
commercial model
reputation
delivery history
dependency risk
control
ownership
expected contribution
exit conditions
Application To Existing Clients
For existing client meetings, the framework should incorporate:
contract scope
previous goals
outstanding actions
existing systems
previous decisions
outcome history
unresolved risks
stakeholder changes
renewal or expansion opportunities
Existing Client Rule
Internal account evidence should take priority over generic external summaries.
Manual Use Rule
This framework should be proven manually before any technical automation is considered.
Manual use should establish:
which sources are genuinely useful
how much research is proportionate
which questions improve meetings
which fields support sales decisions
where AI introduces weak assumptions
what information should be retained
what information should be discarded
what level of preparation creates commercial value
No automated meeting-intelligence system should be built merely because the source lesson demonstrates that one is technically possible.
Future Plugin Or UI Relevance
This framework may later support:
Meeting Intelligence Request screen
Prospect Research Work Unit
pre-call preparation dashboard
source evidence panel
decision-maker map
hypothesis review panel
offer-fit assessment
Meeting Ready approval
meeting question card
post-meeting confirmation workflow
account knowledge update
Sales Brain dashboard
AIBS prospect diagnostic workflow
Possible Future Fields
meeting_intelligence_id
work_unit_id
prospect_name
company_name
website
contact_name
contact_role
meeting_date
meeting_type
relationship_stage
meeting_purpose
desired_outcome
potential_value
research_depth
owning_brain
supporting_brains
assigned_roles
source_count
primary_source_count
source_freshness
company_summary
business_model
target_customer
market_context
competitors
decision_group
technology_signals
operational_signals
hypotheses
offer_fit_verdict
priority_questions
primary_opportunity
primary_risk
known_unknowns
meeting_strategy
desired_next_step
validation_status
human_review_status
readiness_status
meeting_outcome
confirmed_findings
disproven_assumptions
follow_up_action
next_owner
knowledge_commitment_status
created_at
updated_at
No technical build is authorised by this framework alone.
Governance Role
Sales Brain owns the MWMS AI Meeting Intelligence And Pre-Call Preparation Framework.
Sales Brain is responsible for:
defining the meeting purpose
determining the required research depth
interpreting sales relevance
creating the meeting strategy
deciding provisional offer fit
controlling question quality
defining the desired next step
maintaining follow-up continuity
Research Brain supports:
source planning
evidence gathering
source authority
company research
market research
competitor research
contradiction detection
evidence gaps
Data Brain supports:
structured records
source metadata
account intelligence
relationship history
meeting records
confirmed facts
hypothesis state
knowledge commitment
AIBS Brain supports:
AIOS opportunity interpretation
workflow opportunity identification
diagnostic readiness
implementation-fit assessment
client system relevance
HeadOffice governs:
strategic prospects
trophy clients
major partnerships
high-risk recommendations
cross-Brain opportunities
high-value commercial decisions
Relationship To Sales Brain Conversation Structure
This framework prepares the intelligence used before the conversation.
Sales Brain Conversation Structure Framework governs how the live conversation progresses.
The relationship is:
Meeting Intelligence
→ Meeting Strategy
→ Conversation Structure
→ Discovery
→ Qualification
→ Offer Fit
→ Next Step
Relationship To Offer Fit Interpretation
This framework creates provisional offer-fit hypotheses.
Sales Brain Offer Fit Interpretation Framework should govern the final assessment after the meeting provides direct evidence.
Relationship To Follow-Up Continuity
The intelligence package and meeting outcome should flow into Sales Brain Follow Up Continuity Framework.
Follow-up should reflect:
what was discussed
what was confirmed
what remains unresolved
what value matters
who owns the next action
when the next action is due
Relationship To External Knowledge Systems
The MWMS External Knowledge Engine And Reasoning Agent Separation Framework governs how evidence is retrieved and separated from final reasoning.
Meeting intelligence should use external knowledge systems as evidence sources.
It must not allow a retrieval engine to issue final sales decisions without governed interpretation.
Relationship To RAG And Client Memory
The MWMS RAG Knowledge Base And Client Memory Infrastructure Framework may later support persistent client or prospect knowledge.
Only validated, relevant and appropriately retained information should enter client memory.
Relationship To Proof And Claims Control
Any claim MWMS intends to use in the conversation, proposal or follow-up should comply with the MWMS Proof Library And Claims Control Standard.
Unsupported claims should not be used to create urgency or authority.
Relationship To Proposal Creation
Meeting intelligence may inform a proposal.
A proposal should be based primarily on:
meeting-confirmed needs
agreed outcomes
validated scope
delivery capability
commercial fit
Pre-call research alone is not enough to justify proposal claims.
Relationship To SIT Brain
SIT Brain may later:
verify required fields
verify source presence
detect unsupported claims
detect unlabeled hypotheses
detect stale evidence
detect missing human review
block Meeting Ready status
verify knowledge commitment
check follow-up ownership
Relationship To Other MWMS Standards
This framework supports and must align with:
MWMS Founder Led Sales And First Client Deal Flow Framework
MWMS AI Assisted Outreach And Sales Follow Up Automation Framework
MWMS Lead Intake Qualification And Follow-Up Automation Framework
MWMS High-Ticket AIOS Client Acquisition And Trophy Client Framework
MWMS AI Audit Diagnostic And Paid Roadmap Framework
MWMS Right-Fit Client And Offer Profile Standard
MWMS Research Planning And Query Rewriting Standard
MWMS Research Synthesis Documentation And Distribution Framework
MWMS External Knowledge Engine And Reasoning Agent Separation Framework
MWMS RAG Knowledge Base And Client Memory Infrastructure Framework
MWMS Proof Library And Claims Control Standard
MWMS Proposal Structure Framework
Sales Brain Conversation Structure Framework
Sales Brain Offer Fit Interpretation Framework
Sales Brain Expectation Alignment Framework
Sales Brain Trust Reinforcement Framework
Sales Brain Follow Up Continuity Framework
MWMS AI Output Validation Standard
MWMS AI Agent Outcome Measurement Framework
MWMS AI Tool Permission And Access Framework
MWMS AI Observability Metadata Standard
Drift Protection
This framework protects MWMS from:
entering high-value meetings unprepared
relying on generic company summaries
confusing research with verified internal truth
treating public signals as confirmed problems
using outdated information
collecting irrelevant personal data
over-researching minor opportunities
creating impressive but unusable assets
forcing offer fit
asking generic questions
hiding uncertainty
storing disproven assumptions
losing meeting continuity
building automation before manual proof
allowing vendor-specific workflows to become permanent architecture
Meeting Intelligence Drift Signals
MWMS should watch for:
no meeting purpose
wrong company
unclear entity
no source record
stale information
weak source authority
facts and hypotheses mixed together
no unknowns
intrusive personal information
generic meeting questions
no offer-fit reasoning
no meeting objective
no desired next step
excessive package length
unnecessary media assets
no human review
no post-meeting correction
hypotheses committed as facts
Rule
Meeting intelligence drift must be corrected before the package receives Meeting Ready status.
Minimum Compliance Standard
A formal Meeting Intelligence Package is compliant only when it defines:
Meeting Intelligence Record ID
Work Unit ID
prospect or company
meeting date
meeting type
relationship stage
meeting purpose
desired outcome
research depth
Owning Brain
company overview
attendee overview
source record
source authority
source freshness
market context
operational signals
facts
claims
hypotheses
unknowns
offer-fit possibilities
priority questions
meeting strategy
risks
desired next step
validation status
human review status
current status
next owner
Architectural Intent
The architectural intent of the MWMS AI Meeting Intelligence And Pre-Call Preparation Framework is to give Sales Brain a governed intelligence layer before important conversations.
MWMS should eventually be able to move from:
Prospect Identified
→ Meeting Booked
→ Intelligence Work Unit Created
→ Sources Collected
→ Evidence Verified
→ Company And People Context Built
→ Market And Operational Signals Interpreted
→ Hypotheses Created
→ Offer Fit Considered
→ Meeting Questions Prepared
→ Human Review Completed
→ Meeting Conducted
→ Knowledge Corrected
→ Follow-Up Assigned
The long-term goal is not automated research for its own sake.
The goal is a sales system where every important meeting begins with:
relevant preparation
source-grounded understanding
visible uncertainty
strong questions
ethical boundaries
clear commercial purpose
a practical next-step strategy
Strategic Summary
The MWMS AI Meeting Intelligence And Pre-Call Preparation Framework converts scattered company, market, professional and operational information into a governed pre-meeting intelligence package.
It establishes:
meeting-purpose control
entity verification
source planning
company intelligence
professional decision-maker intelligence
market and competitor context
operational and technology signals
fact, claim, hypothesis and unknown separation
provisional offer-fit interpretation
question architecture
meeting strategy
package validation
post-meeting correction
durable knowledge commitment
The key shift is:
MWMS should not use AI research merely to know more about a prospect.
MWMS should use governed research to conduct a more relevant, trusted and commercially useful conversation.
Final Rule
Research should reduce avoidable ignorance before the meeting without pretending to replace the meeting.
No meeting purpose, no research scope.
No verified entity, no intelligence package.
No source, no trusted fact.
No clear classification, no reliable conclusion.
No labelled hypothesis, no safe assumption.
No meaningful question, no meeting value.
No human judgement, no high-value prospect strategy.
No post-meeting correction, no durable account truth.
Change Log
Version: v1.0
Date: 2026-06-20
Author: HeadOffice
Change:
Created the MWMS AI Meeting Intelligence And Pre-Call Preparation Framework using the AI Automations by Jack lesson covering AI-assisted company research, prospect intelligence, executive briefing, competitive analysis, market assets, meeting preparation and multi-format intelligence packaging.
The source’s product-specific workflow was converted into a tool-agnostic MWMS framework governing:
meeting purpose
entity identification
source planning
company intelligence
professional attendee intelligence
market and competitive intelligence
operational and technology signals
hypothesis creation
offer-fit interpretation
meeting strategy
intelligence package production
validation
human review
post-meeting knowledge correction
Purpose of creation:
To establish a repeatable Sales Brain framework for converting dispersed prospect and company information into verified, ethical and decision-ready pre-call intelligence.
Change Impact Declaration
This v1.0 creation adds a dedicated Sales Brain intelligence layer that sits before conversation structure, qualification, offer-fit interpretation, proposal creation and follow-up.
Pages Created
MWMS AI Meeting Intelligence And Pre-Call Preparation Framework
Pages Updated
None
Pages Deprecated
None
Standalone Pages Not Created
MWMS NotebookLM Meeting Preparation Framework
MWMS AntiGravity Prospect Research Framework
MWMS Automated Company Dossier Framework
MWMS Prospect Podcast Generation Framework
MWMS Meeting Quiz And Flashcard Framework
MWMS Executive Briefing Generator Framework
MWMS Prospect Intelligence Dashboard Framework
These concepts were absorbed into the unified tool-agnostic meeting intelligence framework rather than created as separate pages.
Registries Requiring Update
Sales Brain Page Registry
Canon Version Update Required
No
Change Log Entry Required
Yes
Strategic Absorption Result
MWMS gains a governed pre-call intelligence system that improves preparation, discovery, offer alignment, qualification, trust, proposal relevance and follow-up while preventing unsupported assumptions, invasive profiling, source confusion and unnecessary AI-generated research assets.
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