← StackSwap OS

The intelligence layer

The missing layer between
your leads and your CRM.

Stack intel, ICP scoring, and buyer-model training — added to every lead before the record ever lands. Apollo, Clay, HubSpot, Salesforce: your stack stays the same; your intelligence layer changes.

Every tool your team already uses becomes a training surface for your buyer model.

The architecture

One layer, dropped between what you have.

Leads come from wherever you source them. They land wherever you already work. SS OS is the step in between that adds the intelligence — and keeps the patterns to train your model.

Sources

ApolloClayZoomInfoSales Nav

SS OS

Stack detectionICP fit scoreBuyer modelOpener draft

Destinations

HubSpotSalesforceOutreachInstantly

Every integration

What each tool gains when leads route through SS OS.

Same tools. Same workflow. Each card leads with what SS OS adds to the record before it lands.

All integrationsLead sourcesCRMsSequencersEnrichmentProspecting

Lead source

Apollo.io

  • Stack detection on every lead
  • ICP fit score, not a generic benchmark
  • Buyer model training on every pull
  • Opener drafted, not just a contact returned

How SS OS works with Apollo.io →

Enrichment & automation

Clay

  • Stack detection as a Clay enrichment column
  • Fit score that improves over time
  • Buyer model training happens in parallel
  • No redundant enrichment spend

How SS OS works with Clay →

CRM

HubSpot

  • Auto-sync to HubSpot custom properties
  • Analyze CRM → seed the buyer model instantly
  • CRM enrichment without leaving HubSpot's workflow
  • Intelligence sourcing routes directly to HubSpot

How SS OS works with HubSpot →

Email sequencer

Instantly

  • Opener drafted at enrichment time
  • Verified email before it enters the campaign
  • Fit score as a send-priority signal
  • No personalization research lag

How SS OS works with Instantly →

CRM

Salesforce

  • Custom fields written back to Salesforce
  • Historical closed/won data seeds the buyer model
  • Fit scoring in Salesforce reports

How SS OS works with Salesforce →

Lead source & intent

ZoomInfo

  • Your model, not ZoomInfo's intent score
  • Tech stack detection ZoomInfo doesn't provide
  • Full-record buyer model training

How SS OS works with ZoomInfo →

Sales engagement

Outreach

  • Personalization drafted at enrichment time
  • Verified contacts before they enter the sequence
  • Fit score for sequence routing

How SS OS works with Outreach →

CRM

Pipedrive

  • Stack intel on every Pipedrive organization
  • Buyer model seeded from Pipedrive deal history
  • Fit score as a Pipedrive filter

How SS OS works with Pipedrive →

Prospecting

LinkedIn Sales Navigator

  • Tech stack that LinkedIn's profile doesn't show
  • Buyer model score for every LinkedIn prospect
  • Verified work email to go with the LinkedIn profile

How SS OS works with LinkedIn Sales Navigator →

CRM

Attio

  • Stack intel as Attio record attributes
  • Buyer model seeded from Attio deal history
  • Attio lists filter by fit score

How SS OS works with Attio →

Popular workflows

Wire it into the motion you already run.

The most common ways operators drop SS OS between their source and their destination.

ApolloSS OSHubSpot

Find better accounts before sales touches them

Pull a list from Apollo, score every account against your buyer model, and write the stack intel back to HubSpot — reps only ever see prioritized records.

See the workflow →

ClaySS OSInstantly

Enrich, score, and personalize every outbound lead

Add SS OS as a Clay enrichment step, gate on fit score, then push the highest-fit rows to Instantly with the opener already drafted to the stack they run.

See the workflow →

SalesforceSS OS

Train the buyer model on historical wins

Connect Salesforce and run Analyze CRM — SS OS reads your Closed Won / Closed Lost opportunities and seeds the buyer model from your real conversion history.

See the workflow →

What happens to a lead?

A bare record goes in. An intelligence record comes out.

The same lead, before and after it routes through SS OS — the difference is everything your buyer model needs to score it and everything your rep needs to open the conversation.

Before SS OS

  • Name
  • Domain
  • Email

After SS OS

  • Detected tech stack
  • Estimated monthly spend
  • Replacement opportunity
  • ICP fit score
  • Buyer-model score
  • Recommended opener

Illustrative — fields SS OS adds to a record, not a real account.

Don’t see your tool?

Any tool that exports a company name works — CSV, webhook, or REST API. If it can send a company name, SS OS can score it.

Request an integration →

Or email nick@stackswap.ai — we read everything.