Deal Collaboration
Network
Architecture — v2 Interactive
01 The deal collaboration lifecycle
02 Data sovereignty and match architecture
03 Match intelligence engine
Click any element to see the detail behind it.
Diagram 01
The deal collaboration lifecycle
For: Executives · Investors · Sales leaders
Stage 1
Brand seller
Uploads target accounts
→
Hyvara
Ingests + indexes signals
←
Partner seller
Uploads currency inventory
↓
Stage 2
Match intelligence engine
Trust scored across 7 currency dimensions
↓
Stage 3
Match signal → brand
Account name + trust score visible
both↕
Match signal → partner
Account name + AE profile visible
↓
Stage 4
Mutual opt-in
Deal intel protected until both sides consent
↓
Stage 5
Progressive intel exchange
Deal context → currency declared
↓
Breakout
Direct collaboration
Their own infrastructure — Hyvara steps back
↓
Outcome
Outcome logged → trust scores updated
Network learns. Future matches improve.
Signal to meaningful conversation: 48 hours · Without DCN: 6 months of conference stalking — or never
Brand seller — Stage 1
What the brand seller uploads
The brand AE connects their CRM directly or uploads two lists:
- Annual target account list — the accounts they're going after this year. Surfaces net new co-sell opportunities.
- Existing customer list — accounts already in their portfolio. Surfaces expansion and renewal opportunities where partner currency could accelerate growth.
Partner seller — Stage 1
What the partner seller uploads
The partner AE uploads their account relationship inventory — every enterprise account where they have an active relationship, an MSA, a delivered project, or a meaningful contact. They also declare their currency inventory across seven dimensions:
- Relationship access
- Compliance clearances (MSAs, vendor approvals)
- Vertical expertise and certifications
- Reference customers (referenceable in 72 hours)
- Available solution architects (on 48-hour notice)
- Network introductions and executive access
- Trust history from past co-sell outcomes
Hyvara — Stage 1
How Hyvara ingests and indexes the data
Hyvara runs a data anonymizer inside each org's environment before anything leaves their walls. The anonymizer:
- Hashes all account identifiers — no raw account names or IDs ever reach Hyvara
- Strips all PII from both sides
- Generates anonymized signals that represent match intent without exposing underlying data
Match intelligence engine — Stage 2
How Hyvara scores a match
The match intelligence engine computes a composite trust score across 12 weighted inputs grouped into three signal categories:
- Relationship signals — relationship depth, executive access, reference availability, network strength
- Delivery signals — certifications, vertical expertise, resource availability, industry experience
- Business signals — historical outcomes, partner engagement record, account target fit, revenue alignment
Match signal — Stage 3
What the brand seller sees
The brand AE receives a match notification showing:
- The account name — for example, "Nike"
- The trust score for this specific partner on this specific account
- The type of currency the partner holds (relationship access, compliance clearance, available SEs, etc.)
Match signal — Stage 3
What the partner seller sees
The partner AE receives a match notification showing:
This direction — partner initiating or responding to a brand AE signal — often has higher conversion than the reverse because the partner is the market maker. They found the opportunity. The brand AE responds. Lower friction, higher close rate.
- The account name — for example, "Nike"
- The trust score and Brand AE profile (their engagement track record with partners)
- The type of currency being requested
This direction — partner initiating or responding to a brand AE signal — often has higher conversion than the reverse because the partner is the market maker. They found the opportunity. The brand AE responds. Lower friction, higher close rate.
Mutual opt-in — Stage 4
The trust gate — intel is protected until both say yes
Both sides independently review the match signal and decide whether to engage. One click to accept or decline. No obligation. No explanation required for a decline.
The gate is bilateral — neither side sees the other's intelligence until both have actively consented. If one side accepts and the other declines, nothing is exposed. Either party can withdraw at any stage after opt-in without friction or explanation.
This mirrors how trust actually works between humans. You don't hand someone your most valuable relationship on day one. You give them a signal, evaluate their response, and open the next door only when the previous one demonstrated good judgment.
The gate is bilateral — neither side sees the other's intelligence until both have actively consented. If one side accepts and the other declines, nothing is exposed. Either party can withdraw at any stage after opt-in without friction or explanation.
This mirrors how trust actually works between humans. You don't hand someone your most valuable relationship on day one. You give them a signal, evaluate their response, and open the next door only when the previous one demonstrated good judgment.
Progressive intel exchange — Stage 5
How deal context and currency are shared
Once both sides opt in, Hyvara structures a controlled intel exchange in stages. Each stage requires explicit consent:
- Deal context shared — brand AE shares stage, strategic need, and timing. Partner sees what's actually needed and can assess fit.
- Currency declared — partner declares specific currency relevant to this account: which relationships, which MSAs are active, which SEs are available on what timeline.
Breakout — Stage 5 completion
They take it live in their own infrastructure
Once the intel exchange is complete, both parties move the conversation into their own infrastructure — Zoom, Slack, email, phone. Hyvara has done its job.
The relationship belongs to the humans who built it. Hyvara is the exchange mechanism, not the relationship itself. This is a deliberate design choice: no CIO will allow deal intelligence to sit in a third-party system. The architecture ensures they never have to.
The outcome is logged back to Hyvara when both parties report results — but the raw conversation, deal terms, and relationship context stay entirely in their hands.
The relationship belongs to the humans who built it. Hyvara is the exchange mechanism, not the relationship itself. This is a deliberate design choice: no CIO will allow deal intelligence to sit in a third-party system. The architecture ensures they never have to.
The outcome is logged back to Hyvara when both parties report results — but the raw conversation, deal terms, and relationship context stay entirely in their hands.
Outcome — Feedback loop
How the network gets smarter with every connection
When both parties report back, Hyvara logs the outcome and updates trust scores on both sides:
- Partners who deliver get higher trust scores and more high-quality matches. The score rewards quality over time.
- Brand AEs who close with partners and honor relationship protection terms get access to higher-currency partner matches.
- Currency types that produced the most quota movement per dollar invested become the strategic priority for the next cycle.
Diagram 02
Data sovereignty and match architecture
For: Enterprise architects · Security teams · CTOs
Adobe (Brand org)
Salesforce CRM
Raw deal data — stays here
Target account list
Company internal — never exported
Opportunity intelligence
Stage, timing, contacts — stays here
Data anonymizer
Hashes IDs · strips all PII · generates signals only
Ensemble (Partner org)
Partner CRM / ERP
Raw relationship data — stays here
Currency inventory
MSAs, references, SEs — stays here
Delivery history
Projects, outcomes — stays here
Data anonymizer
Hashes IDs · strips all PII · generates signals only
anonymized signals only ↓
anonymized signals only ↓
Snowflake Data Marketplace
Shared anonymized signal layer · cloud-hosted · no raw CRM · no PII · hashed account IDs only
↓
Hyvara matching engine
Reads signals · runs trust score · surfaces match recommendations
Hyvara never stores
- Raw CRM data
- PII of any kind
- Deal intelligence
- Account names or contacts
Hyvara only processes
- Hashed account IDs
- Anonymized signals
- Match metadata
- Trust score composites
Principle 1
Trust is built progressively — not granted upfront
Principle 2
Your data never leaves your infrastructure
Principle 3
Both quotas move — or the mechanism does not work
Adobe brand org
Salesforce CRM
The brand AE's Salesforce instance is the source of truth for their deal data. This is where open opportunities, account contacts, deal stage, and competitive intelligence live.
None of this data ever leaves the Adobe environment. The data anonymizer sits inside the Adobe org boundary and processes the CRM data locally — hashing account identifiers and stripping PII before generating the anonymized signals that travel to the Snowflake layer.
From a security standpoint: Hyvara never has credentials to Adobe's Salesforce. Hyvara never sees raw opportunity data. The integration is a one-way signal emission, not a data sync.
None of this data ever leaves the Adobe environment. The data anonymizer sits inside the Adobe org boundary and processes the CRM data locally — hashing account identifiers and stripping PII before generating the anonymized signals that travel to the Snowflake layer.
From a security standpoint: Hyvara never has credentials to Adobe's Salesforce. Hyvara never sees raw opportunity data. The integration is a one-way signal emission, not a data sync.
Adobe brand org
Target account list
The annual target account list — the accounts the brand AE is going after this year — is uploaded once and refreshed periodically. It feeds the matching engine's net new co-sell opportunity discovery.
This list is company-internal and never exported in raw form. The anonymizer hashes each account identifier before any signal leaves the Adobe environment. Hyvara sees hashed IDs, not account names.
The existing customer list (accounts already in portfolio) can also be uploaded to surface expansion and renewal opportunities where partner currency could accelerate growth. Same anonymization process applies.
This list is company-internal and never exported in raw form. The anonymizer hashes each account identifier before any signal leaves the Adobe environment. Hyvara sees hashed IDs, not account names.
The existing customer list (accounts already in portfolio) can also be uploaded to surface expansion and renewal opportunities where partner currency could accelerate growth. Same anonymization process applies.
Adobe brand org
Opportunity intelligence
Deal stage, timing, internal contacts, competitive context, and strategic priorities are all considered highly sensitive and stay entirely within the Adobe environment.
This information is only shared after mutual opt-in during Stage 5 of the connection flow — and even then, it is shared directly with the matched partner, not stored by or routed through Hyvara.
The progressive intel exchange is a controlled peer-to-peer handoff. Hyvara orchestrates the structure of that handoff — both sides consenting at each step — but never accumulates the raw intelligence itself.
This information is only shared after mutual opt-in during Stage 5 of the connection flow — and even then, it is shared directly with the matched partner, not stored by or routed through Hyvara.
The progressive intel exchange is a controlled peer-to-peer handoff. Hyvara orchestrates the structure of that handoff — both sides consenting at each step — but never accumulates the raw intelligence itself.
Data anonymizer
The privacy boundary — runs inside your org
The data anonymizer is the critical architectural component that makes enterprise adoption possible. It runs inside the customer's own environment — inside Adobe's network, inside Ensemble's network — before anything is emitted outward.
What it does:
What it does:
- Hashes account identifiers — account names and CRM IDs are replaced with deterministic hashes. Two orgs can discover a shared account via matching hashes without either side knowing the other's raw data.
- Strips all PII — contact names, email addresses, phone numbers, and any personally identifiable information are removed before signals are generated.
- Generates match signals — the output is a structured signal representing match intent: "this org has currency of type X for account hash Y." No raw data included.
Ensemble partner org
Partner CRM / ERP
The partner org's CRM and ERP systems hold their relationship history, account contacts, project delivery records, and business development pipeline.
Like the brand side, none of this raw data ever leaves the Ensemble environment. The data anonymizer processes it locally, hashing account identifiers and generating signals that represent the partner's currency without exposing the underlying relationships.
Partners retain full control over which accounts they surface and which currency they declare. The declaration is explicit and opt-in — not scraped from their systems without consent.
Like the brand side, none of this raw data ever leaves the Ensemble environment. The data anonymizer processes it locally, hashing account identifiers and generating signals that represent the partner's currency without exposing the underlying relationships.
Partners retain full control over which accounts they surface and which currency they declare. The declaration is explicit and opt-in — not scraped from their systems without consent.
Ensemble partner org
Currency inventory
The currency inventory is the structured declaration of what the partner can actually bring to a deal. This data has never existed in any structured form before in the partner ecosystem.
It covers seven dimensions:
It covers seven dimensions:
- Active MSAs and vendor approvals at specific accounts
- Referenceable customers available within 72 hours
- Solution architects and SEs available on 48-hour notice
- Vertical certifications and implementation depth
- Executive relationships and peer network access
- Peer introductions and community influence
- Past co-sell outcomes and trust history
Ensemble partner org
Delivery history
Past project outcomes, customer satisfaction data, and co-sell attribution records feed the trust score's "trust history" dimension.
Partners who have delivered results in prior co-sell engagements — and whose outcomes were logged and attributed through Hyvara — get higher trust scores and more high-quality match opportunities over time. The score rewards consistent delivery.
This creates a marketplace incentive structure: partners who show up, deliver, and let outcomes be attributed build compounding platform advantage. Partners who don't follow through see their match quality decline. Quality is self-reinforcing.
Partners who have delivered results in prior co-sell engagements — and whose outcomes were logged and attributed through Hyvara — get higher trust scores and more high-quality match opportunities over time. The score rewards consistent delivery.
This creates a marketplace incentive structure: partners who show up, deliver, and let outcomes be attributed build compounding platform advantage. Partners who don't follow through see their match quality decline. Quality is self-reinforcing.
Shared signal layer
Snowflake Data Marketplace
The Snowflake Data Marketplace serves as the shared anonymized signal exchange layer. It is cloud-hosted and purpose-built for this kind of privacy-preserving data collaboration.
What lives here:
What lives here:
- Hashed account IDs from both sides
- Anonymized currency signals from partner orgs
- Match metadata — signal type, strength indicators, timing
- Raw CRM data
- PII of any kind
- Deal intelligence or opportunity details
- Account names in any readable form
Hyvara layer
The Hyvara matching engine
The Hyvara matching engine reads the anonymized signals from the Snowflake layer, runs the trust score computation, and surfaces match recommendations to both parties.
Three components:
Three components:
- Match engine — identifies which hashed account IDs appear on both the brand side's target list and the partner side's relationship inventory. This is the account overlap detection — but it's just the starting point, not the output.
- Trust engine — for each overlap, computes the composite trust score across 12 weighted inputs from both sides. The score determines which overlaps are worth surfacing and in what priority order.
- Recommendation engine — surfaces the match to both parties with the account name (now safe to reveal since both own the relationship to that account) and the trust score. Both parties see the signal simultaneously.
Diagram 03
Match intelligence engine
For: Product leaders · Architects · Investors
Relationship signals
Relationship depth
Executive access
Reference availability
Network strength
Delivery signals
Certifications
Vertical expertise
Resource availability
Industry experience
Business signals
Historical outcomes
Partner engagement record
Account target fit
Revenue alignment
→
Match
Intelligence
Engine
Intelligence
Engine
12 weighted inputs
composite scoring
composite scoring
→
Outcomes continuously improve future recommendations
Match recommendation
Which partner, which account, why now
Confidence score
Probability of successful co-sell outcome
Collaboration readiness
Currency present · trust history supports it
Different from Crossbeam: Crossbeam shows overlap — a list of shared accounts. The match intelligence engine scores trust and surfaces intent. Overlap is not coordination.
Relationship signal
Relationship depth
Measures the quality and recency of the partner's relationship with named decision-makers at the target account. This goes beyond "we know someone there" — it scores whether the partner has earned access through delivered work, not just LinkedIn proximity.
Why it matters: Opening doors through a trusted relationship that was earned through delivered work compresses the first meeting from weeks to days. The AE doesn't need to cold outreach. The partner makes the intro with credibility already attached.
Why it matters: Opening doors through a trusted relationship that was earned through delivered work compresses the first meeting from weeks to days. The AE doesn't need to cold outreach. The partner makes the intro with credibility already attached.
Relationship signal
Executive access
Measures whether the partner has established relationships at the VP, SVP, or C-suite level at the target account — not just practitioner-level contacts.
In enterprise deals, executive sponsorship on the buyer side is often the difference between a deal that stalls in procurement and one that gets accelerated. A partner with genuine executive access at Nike is worth more than one with ten mid-level contacts — and the score reflects that asymmetry.
Network currency (peer introductions and executive relationships) is one of the seven currency dimensions and scores separately from relationship depth to capture this distinction.
In enterprise deals, executive sponsorship on the buyer side is often the difference between a deal that stalls in procurement and one that gets accelerated. A partner with genuine executive access at Nike is worth more than one with ten mid-level contacts — and the score reflects that asymmetry.
Network currency (peer introductions and executive relationships) is one of the seven currency dimensions and scores separately from relationship depth to capture this distinction.
Relationship signal
Reference availability
Measures whether the partner can produce referenceable customers in the same vertical or use case — and critically, how quickly. The DCN scores references available within 72 hours separately from references that require weeks of coordination.
Why it matters: References move final evaluations across the line. A buyer who is 90% committed but nervous about risk needs one peer conversation with a similar company who has already implemented. The partner who can produce that reference in 72 hours saves an entire quarter. That's the quarter saved — it goes into the trust score directly.
Why it matters: References move final evaluations across the line. A buyer who is 90% committed but nervous about risk needs one peer conversation with a similar company who has already implemented. The partner who can produce that reference in 72 hours saves an entire quarter. That's the quarter saved — it goes into the trust score directly.
Relationship signal
Network strength
Measures the partner's ability to generate net new pipeline for the brand AE through their own network — accounts the AE was not working, contacts the AE couldn't reach, industry communities the AE wasn't part of.
This is the partner AE to brand AE direction of the DCN — lower friction, higher conversion rate. The partner acts as the market maker. They see an account in their relationship inventory that matches the brand AE's target list. They surface the connection proactively. The brand AE responds to a warm introduction rather than making a cold call.
Network currency is particularly powerful for accounts in verticals where the partner has deep community presence — healthcare, financial services, public sector.
This is the partner AE to brand AE direction of the DCN — lower friction, higher conversion rate. The partner acts as the market maker. They see an account in their relationship inventory that matches the brand AE's target list. They surface the connection proactively. The brand AE responds to a warm introduction rather than making a cold call.
Network currency is particularly powerful for accounts in verticals where the partner has deep community presence — healthcare, financial services, public sector.
Delivery signal
Certifications
Compliance currency — active MSAs, vendor approvals, and regulatory clearances already in place at the target account.
Why it matters: In enterprise sales, procurement cycles alone can kill deal momentum. A deal that would otherwise close in Q3 slips to Q2 of the following year because the partner needs to go through a 90-day vendor approval process. A partner who already has an active MSA with Nike eliminates that entirely.
Compliance currency is one of the highest-value dimensions in regulated industries — healthcare, financial services, federal government — where the approval process is both slow and mandatory.
Why it matters: In enterprise sales, procurement cycles alone can kill deal momentum. A deal that would otherwise close in Q3 slips to Q2 of the following year because the partner needs to go through a 90-day vendor approval process. A partner who already has an active MSA with Nike eliminates that entirely.
Compliance currency is one of the highest-value dimensions in regulated industries — healthcare, financial services, federal government — where the approval process is both slow and mandatory.
Delivery signal
Vertical expertise
Expertise currency — measures the partner's depth in the specific vertical relevant to this deal. Vertical certifications, implementation depth, and regulatory knowledge scored against the specific account and deal context.
Why it matters: A partner with genuine vertical depth closes technical objections in one meeting instead of three. They speak the buyer's language, understand the regulatory constraints, and don't need the brand AE to translate. Scope stays intact. ACV holds or expands.
Vertical expertise is particularly valuable when the buyer's security or compliance team is involved — a partner who has already navigated that vertical's specific requirements is worth months of deal acceleration.
Why it matters: A partner with genuine vertical depth closes technical objections in one meeting instead of three. They speak the buyer's language, understand the regulatory constraints, and don't need the brand AE to translate. Scope stays intact. ACV holds or expands.
Vertical expertise is particularly valuable when the buyer's security or compliance team is involved — a partner who has already navigated that vertical's specific requirements is worth months of deal acceleration.
Delivery signal
Resource availability
Resource currency — available solution architects, technical specialists, and SEs who can be in the room on 48-hour notice.
Why it matters: The right expertise in the room when it matters — not three weeks from now. In a competitive deal, the vendor whose technical team shows up at the right moment with the right depth wins the technical evaluation. A partner who can deploy an SE on 48-hour notice is a deal accelerant the brand AE simply cannot replicate through internal headcount alone.
The 48-hour availability threshold is specific and intentional — it separates partners who can actually respond to deal urgency from those who have the resources in theory but can't mobilize them in practice.
Why it matters: The right expertise in the room when it matters — not three weeks from now. In a competitive deal, the vendor whose technical team shows up at the right moment with the right depth wins the technical evaluation. A partner who can deploy an SE on 48-hour notice is a deal accelerant the brand AE simply cannot replicate through internal headcount alone.
The 48-hour availability threshold is specific and intentional — it separates partners who can actually respond to deal urgency from those who have the resources in theory but can't mobilize them in practice.
Delivery signal
Industry experience
Measures the partner's track record of successful implementation at accounts in the same industry, use case, and deal complexity.
This goes beyond certifications — it's about demonstrated outcomes. A partner who has implemented Adobe Experience Cloud at five retail enterprise accounts in the past 18 months brings pattern recognition that no training course provides. They've seen the failure modes, they know the integration challenges, and they can give the buyer confidence that comes only from having done it before.
Industry experience scores separately from vertical expertise because expertise can be theoretical — experience is always empirical.
This goes beyond certifications — it's about demonstrated outcomes. A partner who has implemented Adobe Experience Cloud at five retail enterprise accounts in the past 18 months brings pattern recognition that no training course provides. They've seen the failure modes, they know the integration challenges, and they can give the buyer confidence that comes only from having done it before.
Industry experience scores separately from vertical expertise because expertise can be theoretical — experience is always empirical.
Business signal
Historical outcomes
Trust history — past co-sell outcomes logged through Hyvara, attributed and scored. This is the dimension that compounds over time.
Partners who deliver get more matches. Specifically: partners whose prior connections resulted in closed deals, on-time delivery, and positive outcome attribution accumulate trust score points that give them preferential access to high-quality match opportunities.
This is the flywheel: good partners get better matches, better matches produce better outcomes, better outcomes increase trust score, higher trust score attracts better brand AE partners. The network rewards quality and makes quality increasingly visible.
Partners who deliver get more matches. Specifically: partners whose prior connections resulted in closed deals, on-time delivery, and positive outcome attribution accumulate trust score points that give them preferential access to high-quality match opportunities.
This is the flywheel: good partners get better matches, better matches produce better outcomes, better outcomes increase trust score, higher trust score attracts better brand AE partners. The network rewards quality and makes quality increasingly visible.
Business signal
Partner engagement record
This dimension scores the brand AE side — not the partner. Specifically: how have they treated partners in prior co-sell engagements?
This creates a marketplace incentive for both sides to behave well. Trust is bilateral.
- Did they close deals with partners?
- Did they honor the partner's relationship protection terms?
- Did they attribute outcomes correctly?
- Did they follow through after the intro was made?
This creates a marketplace incentive for both sides to behave well. Trust is bilateral.
Business signal
Account target fit
Measures whether the brand AE's interest in the target account is strategic or opportunistic — and whether the partner's relationship to that account fits the AE's actual intent.
Strategic intent: the AE has this account on their named target list, has researched it, and is building a multi-quarter plan to land it. This is a high-value match opportunity.
Opportunistic intent: the AE saw the match signal and is exploring whether the account is worth pursuing. This is still a valid match but scores lower because commitment is uncertain.
From the partner's perspective: a partner who has a deep relationship at an account the AE is only casually interested in may decline — their relationship is too valuable to spend on a low-commitment AE. The score helps both sides identify genuine strategic alignment.
Strategic intent: the AE has this account on their named target list, has researched it, and is building a multi-quarter plan to land it. This is a high-value match opportunity.
Opportunistic intent: the AE saw the match signal and is exploring whether the account is worth pursuing. This is still a valid match but scores lower because commitment is uncertain.
From the partner's perspective: a partner who has a deep relationship at an account the AE is only casually interested in may decline — their relationship is too valuable to spend on a low-commitment AE. The score helps both sides identify genuine strategic alignment.
Business signal
Revenue alignment
Every DCN connection is designed to produce a quota outcome on both sides simultaneously. Revenue alignment scores whether the specific match has the deal size and structure to actually move both quotas.
Brand AE quota impact:
Brand AE quota impact:
- Faster deals — same pipeline closes in less time. AE recovers capacity for additional deals in the same year.
- Bigger deals — partner currency reduces buyer risk. ACV holds or expands on the same deal.
- More deals — net new pipeline from accounts the AE couldn't penetrate through direct outreach.
- Faster software close means faster services engagement — implementation revenue accelerates in the same quarter.
- Larger software deal means larger services scope — partner quota grows proportionally.
- Net new services opportunities at accounts partner currency opened.
Match intelligence engine
How the composite score is computed
The match intelligence engine weighs all 12 inputs against the specific account and deal context. Each dimension is scored independently and combined into a composite that reflects the total available capital for this specific connection.
The weighting is dynamic — not fixed. A deal in healthcare heavily weights compliance currency (active MSAs, regulatory clearances). A deal in financial services weights expertise currency and executive access. The engine adapts the weight distribution to the vertical, deal stage, and declared need.
The score also accounts for recency. Relationship currency earned 18 months ago at an account with significant executive turnover is weighted lower than currency earned in the past 6 months. The engine knows that enterprise relationships are perishable.
Outcomes continuously feed back into future scoring — the engine learns which currency types produced quota movement in which contexts and adjusts weights accordingly over time.
The weighting is dynamic — not fixed. A deal in healthcare heavily weights compliance currency (active MSAs, regulatory clearances). A deal in financial services weights expertise currency and executive access. The engine adapts the weight distribution to the vertical, deal stage, and declared need.
The score also accounts for recency. Relationship currency earned 18 months ago at an account with significant executive turnover is weighted lower than currency earned in the past 6 months. The engine knows that enterprise relationships are perishable.
Outcomes continuously feed back into future scoring — the engine learns which currency types produced quota movement in which contexts and adjusts weights accordingly over time.
Engine output
Match recommendation
The match recommendation surfaces to both parties simultaneously. It shows:
- The account name — now safe to reveal since both the brand AE and the partner AE have a legitimate relationship to that account
- Which specific partner is recommended and why — the primary currency type driving the match
- The timing signal — why this match is relevant now, not in three months
Engine output
Confidence score
The confidence score is the engine's probability estimate for a successful co-sell outcome — not just an account overlap. It answers: given everything we know about this partner's currency, this AE's track record, and this account's context, what is the probability that this connection produces a quota outcome on both sides?
This is the distinction that separates the DCN from every account overlap tool. Crossbeam can tell you that two companies share Nike as an account. The confidence score tells you which partner has the right currency for Nike right now, whether their trust profile matches the AE they'd need to work with, and what the probability of a successful co-sell connection actually is.
Overlap is not coordination. Overlap is a list. The confidence score is what makes a connection worth making.
This is the distinction that separates the DCN from every account overlap tool. Crossbeam can tell you that two companies share Nike as an account. The confidence score tells you which partner has the right currency for Nike right now, whether their trust profile matches the AE they'd need to work with, and what the probability of a successful co-sell connection actually is.
Overlap is not coordination. Overlap is a list. The confidence score is what makes a connection worth making.
Engine output
Collaboration readiness
Collaboration readiness answers a different question than the confidence score: not just "is this a good match?" but "are both parties actually ready to act on it right now?"
It factors in:
It factors in:
- Currency availability — are the SEs actually available? Is the reference customer reachable this quarter?
- Trust history alignment — does this AE have a track record of following through on partner relationships?
- Deal timing — is the account in a stage where partner engagement would accelerate or disrupt?
- Mutual commitment signals — have both parties demonstrated active deal-building intent through their upload behavior?
· Deal Collaboration Network · Confidential
Architecture v2 Interactive