Direction alignment · 2 October 2026

Relevant, trustworthy reach beyond your own network.

From how dealmakers create value today to a defensible Phase 1 product direction for DealCircle.

Team Ether working hypothesisFor discussion with Sanjay & Prasad
Today's conversation

Seven chapters, one argument.

We stepped back from screens to understand how dealmakers create value, where it is lost today, and where DealCircle can create value people come back for.

01
Story
The dealmaker's journey — before any solution.
02
Value
Where DealCircle could create value.
03
Business Model
Pressure-testing the direction with the Business Model Canvas.
04
Our POV
Which value matters most — and why.
05
Service
What DealCircle actually does behind the interface.
06
Economics
How user value becomes business value.
07
Next
The remaining two weeks and the decisions we need.
Our evidence base

What our current thinking is based on.

01

Client input

What Sanjay has shared across our calls: product ambition, how the community behaves today, Phase 1 expectations and business concerns.

02

Current behaviour

How dealmakers discover, share, recall, assess and progress opportunities through networks, WhatsApp, calls and introductions.

03

Our earlier work

Prior flows, prototype exploration, trust mapping and workflow analysis — and what those exercises exposed.

04

Market patterns

How adjacent platforms in India and globally create value: discovery, matching, access, trust, controlled introductions, intelligence, services.

05

Business feasibility

Business Model Canvas, cost-to-serve, operational dependencies, channel constraints, scalability and value-capture models.

No single stream decides the recommendation. It comes from where these signals converge.
The dealmaker story · Supply side

“I have a deal.”

1
01A mandate or opportunity arrives
02Thinks through the people they know
03Posts and forwards on WhatsApp and to contacts
04Responses and introductions start to arrive
?
05Assesses fit and credibility
06The right connection happens — or the opportunity disappears into noise
The dealmaker story · Demand side

“I need a deal.”

The mirror journey. Finding something is only half of it — they also have to judge whether it's relevant and credible.

Need

A mandate, thesis or buyer brief to fill

Search network & groups

Asks around, scrolls WhatsApp

Scan opportunities

Noise, duplicates, older posts lost

Assess relevance

Is this a fit? Is the source credible?

Engage — or miss

Acts only when confidence is high enough

Across both journeys

Where value is lost today.

Reach

The right counterpart sits outside the immediate circle.

Relevance

Real signal is buried in noise and forwards.

Recall

Older posts disappear in the chat scroll.

Effort

Manual asking, forwarding and following up.

Trust

Unfamiliar people are hard to assess quickly.

Control

Sharing too much, too early, with too many.

Missed deal

The opportunity goes elsewhere — or stalls.

Discovery and recall matter a lot. They are also part of a wider set of losses — we are not ranking these yet.
Strategic tension

The network paradox.

Small networks give you trust. Large networks give you reach. DealCircle has to make a larger network usable.

Small trusted network Fast confidence · known reputation · limited reach Larger unknown network More deals and people · unclear credibility · noise · disclosure risk usable · relevant · trustworthy reach
The opportunity is not just a bigger network. It is usable, relevant, trustworthy reach.
Trust layer

Trust is not just identity verification.

01 · Direct trust

I know you.

02 · Inherited trust

Someone I trust knows you.

03 · Platform-mediated confidence

I don't know you personally, but I have enough credible context to engage.

DealCircle cannot manufacture trust. It can reduce uncertainty enough for the next action to happen.

Possible trust signals
Verified professional identityExperience & specialisationVerifiable deal activityMutual relationshipsResponsivenessContribution historyEvidence provenance

KYC confirms who someone is. It doesn't tell you whether to engage with them.

Value landscape

Five ways DealCircle could create value.

These are ways of creating value, not a feature wishlist. We use the same five groups for the rest of the deck.

F

Find

Surface what matters

  • Deal discovery
  • Recall / resurfacing
  • Relevant matching
R

Reach

Go beyond the immediate circle

  • Effective network expansion
  • Deal distribution / amplification
T

Trust

Make the unfamiliar assessable

  • Credibility context
  • Relationship context
  • Reputation / evidencewhere available
A

Act

Move from interest to connection

  • Controlled introductions
  • Collaboration / connection
R

Return

Reasons to come back

  • Remembered network / context
  • Recommendations / intelligence
  • Community & recognitionlater hypothesis
Market patterns Patterns, not features to copy

How adjacent platforms create value.

India 5 patterns

Marketplace accessListings and opportunities people can browse or post
Controlled disclosureNo-name listings, staged details, verification
Assisted matchingHuman or platform-supported introductions
Visibility productsFeatured listings, campaigns, paid reach
Advisory layerManaged services around transaction readiness

Global incl. China

Criteria-based matchingCapture investment criteria, reduce irrelevant deal flow
Relationship intelligenceWarm paths, history and context
Deal workflow layerAlerts, pipeline, documents, status, collaboration
Network intelligenceBehavioural and data signals to improve targeting
Managed distributionPlatform or analyst routes opportunities to the right audience
Market synthesis
Access RelevanceTrust & contextControlIntelligence & assistanceWorkflow & memory

Access alone is rarely the whole proposition.

The stronger models make access more useful through relevance, trust, control, intelligence, assistance or workflow.

Which combination creates repeat value for DealCircle's users — without becoming too expensive or risky to operate?

Next → testing this as a business system

Business Model Canvas

Testing the direction as a business, not only an interface.

Working hypothesis · to validate

We used the Business Model Canvas framework to pressure-test the direction across customer, value, delivery, cost and revenue — not only the product experience.

Credible network + quality deals + active demand + trusted relationships → better matching and connections → repeat deal contribution → monetisation where DealCircle creates measurable value.

Canvas · 1 of 9
Customer segments
Current working hypothesis
  • Professional M&A dealmakers and advisors — both sell-side and buy-side
  • Independent / boutique bankers and deal originators
  • Demand side: PE and investment funds, family offices, strategic buyers
Why we believe it
Client inputCurrent behaviour
Open: who pays vs who participates — and segment sizes, which we have not assumed.
Canvas · 2 of 9
Value proposition
Current working hypothesis
  • Find relevant opportunities · Place a deal with relevant demand beyond my circle
  • Connect through a trusted path · Save time · Expand reach
  • A well-connected professional assistant that understands what I need and who may be relevant
Why we believe it
Client inputValue-loss mapMarket patterns
Open: which value layer creates the strongest repeat behaviour.
Canvas · 3 of 9
Channels
Current working hypothesis
  • Acquire through professional referrals, invitations, communities and firm partnerships
  • Use a mobile-first app or responsive web — being evaluated
  • Support via WhatsApp only if cost, feasibility and behaviour justify it · Return via relevant alerts
Why we believe it
Current behaviourClient input
Open: how far to depend on WhatsApp, and when the owned experience has earned a move to mobile.
Canvas · 4 of 9
Additional hypothesis from later Sanjay / Prasad discussion

A concierge / service layer that assists high-value introductions.

Customer relationships
Current working hypothesis
  • A curated professional community — not an open social network
  • Personalised recommendations that explain why they're relevant
  • Warm introductions where a relationship path exists; members control what is shared
Why we believe it
Trust ladderControlled-disclosure patterns
Open: how much is automated vs concierge-led.
Canvas · 5 of 9
Key activities
Current working hypothesis
  • Bring in quality deals and active requirements
  • Structure deal information and match deals ↔ demand ↔ dealmakers
  • Enable trusted introductions; maintain confidentiality, quality and freshness
Why we believe it
Service blueprintEarlier workflow analysis
Open: which activities need human operations and which can be automated.
Canvas · 6 of 9
Key resources
Current working hypothesis
  • A credible professional network with quality supply and active demand
  • A relationship graph: who knows, or has worked with, whom
  • Member preferences, matching intelligence and trust evidence — the remembered network is an asset
Why we believe it
Relationship-intelligence patternsTeam synthesis
Open: what data can be collected ethically, legally and in a way members accept.
Canvas · 7 of 9
Key partners
Current working hypothesis
  • M&A advisors and firms — bring credible people, deals and requirements
  • Buyers, funds and strategic acquirers — create active demand
  • Verification, data, legal / compliance and technology providers
Why we believe it
Client inputMarket patterns
Open: which partnerships are essential for Phase 1, and which can wait.
Canvas · 8 of 9
Cost structure
Current working hypothesis
  • Product, engineering, secure infrastructure, matching and data systems
  • Verification, privacy and compliance
  • Network operations and support, communication APIs, growth and partnerships
Why we believe it
Service blueprintTeam synthesis
Open: cost-to-serve for each value mechanism — especially human-assisted introductions.
Canvas · 9 of 9
Additional hypothesis from later Sanjay / Prasad discussion

Paid amplification and paid introductions.
Illustrative test inputs from Prasad — not proposed pricing:
₹499 amplification · ₹199 introduction · ~₹15,000 annual access

Revenue streams
Current working hypothesis
  • Individual professional subscription, firm / team plans
  • Premium intelligence and services
  • Later: transaction-linked revenue and transaction infrastructure — needs commercial, legal and willingness-to-pay validation
Status
Hypotheses to validate
Open: willingness to pay, and where a paywall would discourage the behaviour that builds the network.
How we prioritise

Foundational needs vs strategic differentiation.

Directional team assessment · not user-validated
Opportunity Evidencestrength todayFrequencyof the problemImpactuser / economicRepeat valuereason to returnDifferentiationvs WhatsApp & othersCost / dependencyto deliver well
DiscoveryStrongHighMediumHighLowMedium dependency
RecallStrongHighMediumMediumMediumLow dependency
Relevant matchingMediumHighHighHighHighMedium dependency
Network expansionMediumMediumHighHighHighHigh dependency
Trust contextMediumMediumHighHighHighHigh dependency
Controlled connectionMediumMediumHighMediumMediumMedium dependency
Community / recognitionWeakLowMediumMediumMediumMedium dependency
Foundational strongest evidence, must work Differentiating highest strategic potential
Not “which feature wins”

A value stack, not a single winner.

03 · Trust / action layer

Enough context and control to engage

Becomes necessary the moment DealCircle takes users beyond familiar relationships.

TRUST · ACT
credibility · relationship context · controlled introductions
02 · Value engine

Relevant reach beyond the immediate network

Where the larger economic upside sits: the right counterpart, outside your own circle.

FIND · REACH
relevant matching · network expansion · distribution
01 · Foundation

Discover + recall

Explicit Phase 1 needs with strong client evidence. These have to work well.

FIND · RETURN
deal discovery · recall · remembered context
Team Ether working hypothesis — not a proven finding

Relevant, trustworthy reach beyond your own network.

DealCircle can help dealmakers discover and act on relevant opportunities and relationships beyond their immediate network — while keeping enough context and control to engage confidently.

We will absolutely solve discovery and recall — they are explicit Phase 1 needs. Our broader hypothesis is that DealCircle becomes more valuable when it enables relevant, trustworthy reach.
Service blueprint Team hypothesis · split to be validated

DealCircle is a service, not only screens.

01Deal / need enters
02Structure
03Match & relevance
04Trust context
05Controlled introduction
06Follow-up
07Amplify if useful
08Remember context
Product · automated
Guided posting templates
Fields, tags, anonymised teaser
Criteria match with reasons shown
Profile evidence, mutual paths
Consent from both sides
Status, nudges, reminders
Wider targeted distribution
History, outcomes, preferences
Human · concierge · exceptions
Help early members post well
Quality-check early listings
Curate matches while data is thin
Review disputed claims
Broker sensitive introductions
Chase non-response on high-value intros
Targeted outreach for priority deals
Note exceptions and learnings

Which steps are automated, which are human-assisted, and where do exceptions get handed off?

Worked introduction Illustrative example

One introduction should be traceable.

1

Meera, a sell-side advisor, posts a mandate

Specialty-chemicals business, seeking a strategic buyer. Posted as an anonymised teaser.

2

Arjun, corp-dev at a chemicals group, is surfaced

Outside Meera's direct network — two degrees away.

3

Why he fits is shown — with the evidence

Stated acquisition criteria match sector and size · verified role · a mutual contact.

4

Meera approves the introduction

She controls whether, and how much, is shared.

5

Arjun sees the teaser and Meera's context

Enough to decide — not the full deal details.

6

The outcome is remembered

It shapes future matching for both sides.

Three possible outcomes

Accepted Delivered

Proposed definition: an introduction counts as delivered when both sides opt in and contact details are exchanged.

Declined

One-tap polite decline. No reason required. Meera is told gently — nothing is shown publicly.

No response

A timed nudge, then a graceful close. It doesn't count as delivered.

Beyond the happy path

Trust has to survive the bad cases.

Principle

Many pursue one deal

The owner sees interest and decides who moves forward.

Principle

Polite declines

One tap, no reason needed, nothing visible to others.

Principle

Spam & scams

Verified entry, rate limits, report-and-review.

Principle

Disputed credibility

Show where evidence comes from; a person reviews disputes.

Principle

Withdrawn deals

Interested parties are told; the listing is archived, not erased.

Principle

Non-response

A timed nudge, then a graceful close.

Principle

Repeated introductions

Memory stops us re-introducing the same pair unprompted.

Principle

Bad prior interaction

A private signal that shapes future matching — never public shaming.

Principles today. Detailed workflows on Monday.

Channel roles

Not WhatsApp vs app. Each channel has a job.

Owns the value

DealCircle should own

  • Persistent deal memory
  • Discovery
  • Profile & context
  • Matching
  • Trust evidence
  • Controlled connection
  • Network intelligence
  • System of record
Mobile app — justified when the owned DealCircle experience creates enough repeat value to earn the migration.
Stronger network
Distribution + return

How do people come in — and why do they come back?

Each useful outcome feeds the next: more contribution, more reputation, more referrals.

Professional recognition and community are a future hypothesis to explore — not a confirmed Phase 1 feature.
Business logic

How user value becomes DealCircle value.

01 · User

How the dealmaker gains

  • Places or finds deals faster
  • Reaches counterparts beyond their circle
  • Spends less time searching and following up
02 · Repeat

Why it happens again

  • Alerts that stay relevant
  • A network that remembers
  • Credible context, every time
03 · Capture

How DealCircle may capture value

  • Subscription, firm / team plans
  • Premium intelligence and services
  • Amplification, introductions (additional hypothesis)
04 · Cost

What it costs to produce

  • Matching and data systems
  • Verification and compliance
  • Human operations for introductions
Monetisation follows repeat value. It should not break the behaviour that creates the network.
Value capture vs cost-to-serve Hypotheses

A feature can create value and still be a bad business.

MechanismUser gainValue-capture hypothesisDelivery cost / dependency
AmplificationWider, targeted reach for a dealPaid boost
₹499 · illustrative test input
Low–medium dependency · targeting quality
Trusted introductionA credible path to the right personIntroduction fee
₹199 · illustrative test input
High dependency · human follow-up, consent
Intelligence / accessBetter, faster decisionsSubscription / annual access
~₹15,000 · illustrative test input
Medium dependency · data and matching
CommunityAccess, standing, recognitionMembershipMedium dependency · curation
ServicesExecution helpService feeHigh dependency · human operations

Prices are illustrative test inputs from Prasad — not proposed pricing.

Success signals

Measure traction before forcing monetisation.

Now

Phase 1 success

  • Good deal supply
  • Meaningful use
  • Return behaviour
  • Useful connections
  • Retention
  • Network activity
Later

Commercial outcomes

  • Willingness to pay
  • Paid conversion
  • Revenue per customer
  • Contribution margin
  • Transaction outcomes, where measurable
Client target — requires validation
100k downloads
1,000 paid users
$100 per paid user

We treat these as targets to test against the Phase 1 signals, not as our plan.

Phase 1 product implication

Prove the value loop, not every feature.

Discovery and recall sit inside a broader loop. That loop is what the next two weeks should make real.

Foundation

Discover / recall

Find it, and find it again

Value engine

Understand relevance

Why this, why me

Trust / action

See trust context

Enough to engage

Trust / action

Control disclosure

Share at your pace

Trust / action

Signal interest

Low-risk first step

Return

Connect / continue

Outcome remembered

The remaining two weeks

Today is direction. Monday is detail.

Today · 2 Oct

Direction alignment

Value thesis, business logic and product principles.

Monday · 5 Oct

Product & workflow review

Detailed discovery, posting, connection and trust flows; product states and operating logic.

Following days

Prototype & refine

Build and refine the selected core loop.

Before handoff

Resolve the hard parts

Technical and operational questions, edge cases, cost logic, supporting documentation.

Final

Handoff

Clickable core experience, decision rationale, roadmap and future hypotheses.

Before we leave today

Four checks before we go deeper.

1

Does our working value thesis materially misread the DealCircle opportunity?

2

For the detailed Phase 1 workflow, should we optimise first for “I have a deal”, “I need a deal” — or must both be equally complete?

3

Is there a trust, privacy or operating constraint that makes the proposed connection model unworkable?

4

Is Monday's product and workflow focus the right next level of detail?

Relevant, trustworthy reach beyond your own network.

Thank you · Team Ether
Trust model · 1 of 3

Every signal says where it came from.

SignalWhat it tells youProvenance
Professional identityThis person is who they say they areCorroborated
Experience & specialisationSectors, deal sizes, rolesSelf-reported
Deal activityWhat they have actually closed or worked onCorroborated where verifiable
Mutual relationshipsWho you both know; who vouchesCorroborated
ResponsivenessDo they reply, and how fastObserved on platform
Contribution historyQuality deals posted, intros acceptedObserved on platform
Three kinds of provenance
Self-reported

Useful, but labelled as such. Never shown as verified.

Corroborated

Confirmed by a document, a partner or a mutual contact.

Observed

Built up from behaviour on DealCircle over time. Updates as people act.

Trust model · 2 of 3 Illustrative

The newcomer nobody knows yet.

RK
Rohan K.
Independent originator · Mid-market industrials
Verified professional identityCorroborated 12 years in industrials M&ASelf-reported 2 mutual contacts · 1 vouchCorroborated Replies within a dayObserved Deal activity on DealCircleNone yet

A newcomer has no history yet. The profile has to be honest about that — without making them invisible.

  • Show what's verified and what isn't, clearly
  • Mutual relationships give inherited trust a way in
  • Low-risk first actions (signal interest) let observed trust build
  • Trust updates over time as people respond and contribute
Missing evidence is shown as missing — it isn't hidden, and it isn't held against them.
Trust model · 3 of 3

Protecting credibility when things go wrong.

CaseWhat happensWho acts
False or inflated claimThe claim drops back to “self-reported”; repeated issues limit visibilityProduct flags · human reviews
Scam or spam behaviourRate limits, report-and-review, removal for confirmed abuseProduct + human operations
Disputed deal creditBoth versions noted; credit stays uncorroborated until resolvedHuman review
Rejected introductionPrivate; no negative signal unless there is a patternProduct
Bad prior interactionPrivate feedback that shapes future matching for that pairProduct
Vouch withdrawnInherited trust is removed and the profile updatesProduct

Detailed workflows on Monday. These are principles to agree on now.

Matching & relevance

Every match should say why it's relevant.

Inputs
  • Stated criteria: sector, size, geography, deal type
  • Role: sell-side, buy-side, advisor
  • Past activity and responses
  • Relationship graph
Match

Ranked suggestions

Fewer, better matches instead of a feed of everything.

Shown to the user
  • “Matches your sector and size range”
  • “Two mutual contacts”
  • “Active in the last 30 days”
Early on, while data is thin, a person may curate matches — that's the concierge lane.
Concierge model Additional hypothesis from later discussion

Where people help — and where the service ends.

Automated

Product does it

  • Posting, structuring
  • Matching with reasons
  • Consent requests
  • Reminders
Human-assisted

People help

  • Curating early matches
  • Sensitive or high-value introductions
  • Quality-checking early listings
Non-response

Who follows up

  • Automated nudge first
  • Human follow-up only for priority intros
  • Then a graceful close
Boundary

Where it ends

  • DealCircle connects people
  • It does not advise on or negotiate the deal
  • Any execution services are separate
Every human step has a cost. The concierge lane should shrink as data and trust signals grow.
Introductions · state model Proposed

Every introduction has a clear state.

Suggested RequestedA approves SentB sees teaser Acceptedcontacts exchanged Delivered ✓ Declinedpolite, private No responsenudge after a few days Closed
Open question: is payment (if any) triggered only once an introduction is accepted?
Repeat protection: the same pair isn't re-suggested unless something material changes.
WhatsApp · role and risk

Use WhatsApp for reach. Don't depend on it.

Where it helps
  • Existing behaviour
  • Alerts and re-engagement
  • Low-friction acquisition
What it shouldn't own
  • Deal memory
  • Profiles and trust evidence
  • Controlled connection
  • The system of record
Risks
  • Platform policy changes
  • Account blocks and spam flags
  • Messaging cost at scale
  • Data stuck in chats
Fallback
  • Every alert links back to DealCircle
  • Email / in-app as parallel channels
  • No core data lives only in WhatsApp

Cost, policy and feasibility to be confirmed before any WhatsApp integration is committed.

Amplification Additional hypothesis from later discussion

Paid reach only works if it stays relevant.

What it is

A deal owner pays to reach a wider, targeted audience beyond normal matching.

What must stay true

Amplified deals still respect relevance and disclosure controls. Recipients shouldn't feel spammed.

To test

Whether owners will pay, at what price, and whether recipients' engagement drops.

Interaction flow — to be added after Monday
Community & recognition Future hypothesis

Could professional standing bring people back?

The idea
  • Recognition for quality contributions and successful introductions
  • A known-community fast pass for trusted groups
  • Specialist circles by sector or deal type
Why it's not Phase 1
  • Weakest evidence of all the opportunities
  • Needs activity before recognition means anything
  • Risk of status games distracting from deals
Explore after the core loop shows return behaviour.
Monetisation Scenario calculation only — not a forecast

What the illustrative prices would add up to.

Annual access
₹1.5 Cr / yr

If 1,000 members paid ~₹15,000 a year

Amplification
~₹1 L / mo

If 200 deals a month were amplified at ₹499

Introductions
~₹0.6 L / mo

If 300 introductions a month were accepted at ₹199

To test: willingness to pay at each price point — all inputs are illustrative, from Prasad.
To test: does per-introduction revenue cover the human follow-up it needs?
Monday · product & workflow review

What Monday covers in detail.

Product screens

Posting, discovery and response screens; mobile / web detail

Posting & discovery

Role-specific templates

Onboarding & login

Login and known-member fast pass

Trust & verification

KYC, verification and consent

Incoming interest

Handling interest; polite rejection flows

Revenue / paywall

Amplification interaction

WhatsApp / channel

Alert and re-engagement flows; landing page

Backend / admin

Admin and operating logic

Also tracked: legal and compliance dependencies that may affect product priority.
Appendix & deep dives

Ready if you want to go deeper.

Deep dive

Trust model

Signals, provenance, newcomers, edge cases

Deep dive

Matching & relevance

Inputs, ranking, reasons shown

Deep dive

Concierge

Automated vs human, where service ends

Deep dive

Introductions

State model, delivered, decline, no response

Deep dive

WhatsApp

Role, risks, fallback

Deep dive

Amplification

Paid reach that stays relevant

Deep dive

Community

Recognition as a future hypothesis

Deep dive

Monetisation

Scenario arithmetic

Appendix

Competitors — India

Pattern × company map

Appendix

Competitors — Global

Incl. China

Appendix

Evidence register

Key claims and their sources

Appendix

Prioritisation rationale

Why each row scored as it did

Reference

Full Business Model Canvas

Baseline hypothesis

Reference

BMC block detail

Nine blocks: hypothesis, evidence, open questions

Reference

Monday backlog

Grouped scope

Appendix · Competitor map — India

India: who creates value, and how.

PatternValue mechanismHow deliveredTarget participantTrust mechanismValue captureRelevance to DealCircle
Marketplace accessFindListings to browse or postSME owners, buyersListing reviewPaid listingsSupply-side posting
Controlled disclosureTrust · ActNo-name listings, staged detailSellers, advisorsVerification, NDAsPremium tiersAnonymised teasers
Assisted matchingActHuman-supported introsBuyers, sellersAdvisor vettingSuccess / service feesConcierge lane
Visibility productsReachFeatured listings, campaignsSellers—Paid reachAmplification
Advisory layerActManaged transaction servicesOwners, buyersFirm reputationService feesService boundary
Named company examples are added once verified — only verified facts appear here
Appendix · Competitor map — Global (incl. China)

Global: layers around access.

PatternValue mechanismHow deliveredTarget participantTrust mechanismValue captureRelevance to DealCircle
Criteria-based matchingFindBuyers state criteria; deals routed to fitPE, corp-dev, advisorsMember vettingSubscriptionRelevance engine
Relationship intelligenceTrust · ReturnWarm paths and historyDeal teamsRelationship dataEnterprise licenceRemembered network
Deal workflow layerReturnPipeline, documents, statusDeal teamsAccess controlsSeat licenceLater, not Phase 1
Network intelligenceFind · ReachData signals to target outreachInvestorsData provenanceData subscriptionIntelligence later
Managed distributionReach · ActAnalyst-routed opportunitiesSell-sidePlatform curationFeesAmplification + concierge
Named company examples are added once verified — only verified facts appear here
Appendix · Evidence register

Key claims and where they come from.

ClaimEvidence streamsStatus
Discovery and recall are Phase 1 needsClient input · current behaviourClient input
Deals get lost in WhatsApp noise and scrollClient input · current behaviour · earlier workObserved
Access alone is rarely the whole propositionMarket patternsMarket pattern
Relevant reach beyond the network creates more valueTeam synthesis · market patternsTeam hypothesis
Trust needs more than KYCTrust mapping · market patternsTeam hypothesis
Concierge layer for high-value introductionsLater discussion · service blueprintAdditional hypothesis
Illustrative prices (₹499 / ₹199 / ~₹15,000)PrasadTest input
100k downloads · 1,000 paid · $100Client inputClient target
Appendix · Prioritisation rationale

Why each opportunity is assessed as it is.

OpportunityRationale
DiscoveryStrongest direct client evidence and high frequency. Groups already do a basic version, so it alone differentiates less.
RecallA clear, well-evidenced WhatsApp failure. Cheap to deliver once deals are structured.
Relevant matchingReduces noise on every visit, so it creates repeat value. Needs good criteria data.
Network expansionThe largest economic upside, but only usable together with trust and relevance.
Trust contextNecessary once users go beyond familiar people. Costly to do well — verification and review.
Controlled connectionHigh impact at the moment of action. Depends on clear consent flows.
Community / recognitionWeakest evidence. Only meaningful once there is enough activity.