Find the accounts running a stack you can beat. Pay only when the lead validates.

Two routes, one engine

Bring a signal, or bring your list.

Same intelligence engine, two ways to point it. Pick the one that matches the motion you’re running — and in both, you only pay for leads that validate.

Sourcing fills the top of the funnel; enrichment sharpens the pipeline you already have. One engine, billed only on validated matches.

The intelligence layer

Not a lead list. A precision model.

We catalog 486 tools with 451 priced. We detect 130,000+ companies actively overpaying — the exact displacement angles you can win on, with known spend bleeding. We map 370,000+ company tech stacks. We cover 12M+ companies total. The question is not how many leads but how many precision targets.

Two plays, near-zero dead leads

Every account is winnable — one of two ways.

The engine tags every company it reads. When it detects a tool you can beat, you get the kill shot. When it doesn’t, it falls back to a play that still earns a reply. Either way, the lead isn’t dead.

The ceiling play when there’s blood in the water. The floor play when there isn’t. Together: a queue with almost no dead leads in it.

The old way vs StackSwap OS

Generic lead scoring. Or a model built on your data.

Every enrichment vendor sells the same scores to every customer. StackSwap OS is different: it starts with the same raw intelligence, then trains a buyer model on your actual conversion outcomes — so the fit scores improve every time you close a deal.

How it works

Turnkey to start. Smarter every month.

No migration project, no rip-and-replace. Three steps to a buyer-scoring model that compounds on your own data.

1. 1

   Connect your data sources

   Wire in Clay, PDL, or your CRM — or push leads straight in through the open API. Wherever your lead data lives, your team of AI agents starts reading stacks and building your enriched ICP list.

2. 2

   Score your ICP

   Feed it companies — or let it find them — and the engine returns a ranked queue with a fit score (0–100) for each: how well they match your ICP, why, and what angle gives you the best shot.

3. 3

   Tag outcomes and train

   Mark who converted, who replied, who went dark. The model retrains on your outcome data each month — and becomes progressively more accurate for your specific ICP. Month 6 looks nothing like month 1.

The team

You’re the operator. This is your team of AI agents — included in every plan.

Four AI agents, included in every plan, each owning a slice of the motion. The sandbox beta runs the loop that makes the model yours — the GTM Stack Expert (reads stacks, scores your ICP) and the Buyer-Model Scientist (tags outcomes, retrains your model). The GTM Engineer wires it up; the Pipeline Strategist comes online across the cohorts.

• GTM Engineer

  Orchestration · 4 specialists

  Wires your data sources and runs the whole system on your own keys.

  Data wiringOrchestrationBYO-key setupNew integrations · soon

• GTM Stack Expert

  Stack Intelligence · 4 specialists

  Reads any company's real stack and finds what you can displace.

  Stack detectionDisplacement targetsOverlap & spend readTool-change alerts · soon

• Buyer-Model Scientist

  Buyer Modeling · 4 specialists

  Scores fit against your ICP and trains a model on your wins.

  ICP fit scoringOutcome trainingWhy / why-notLookalike expansion · soon

• Pipeline Strategist

  Pipeline Strategy · 4 specialists

  Ranks your queue and drafts the opener and the play to run.

  Queue prioritizationOpener draftsPlay selectionMulti-touch sequencing · soon

They share one brain. The Stack Expert’s read feeds the fit-scoring model; the Buyer-Model Scientist’s training sharpens it; the Pipeline Strategist turns the scores into the next move. One database, one context — experts that hand work to each other, not four subscriptions pretending to be a team. And the buyer model they train is yours, not ours.

What’s inside

The beta starts with the scoring loop.

One hosted app that reads stacks, scores leads against your ICP, and trains a buyer model you keep — on your own AI keys. The sandbox beta ships the two surfaces marked Live; the wider cockpit rolls in across the cohorts.

• 01Live in beta

  Lead intelligence + fit scoring

  Reads a company's real stack from job posts and signal data, infers monthly spend, and scores how well they fit your specific ICP — not a generic benchmark. Each score includes the why: what makes this a now-buy, what angle to open with.

• 02Live in beta

  Your data, your model

  Every lead that flows through SS OS — from Apollo, your CRM, a CSV, or the open API — trains your buyer model on the full lead record: company size, industry, title, seniority, location, tech stack, funding stage, growth signals, and your conversion outcomes. Not just the intelligence we add. Everything. Month 6, your model knows exactly who converts for you, in your market, at your price point.

• 03Rolling in

  The revenue cockpit

  Trial → activated → paid, MRR, churn risk, and the next play to run, in one view. It syncs your CRM; it doesn't replace it.

• 04Rolling in

  Demand capture

  Scored buying-intent signals, plus the names of companies quietly checking out your site — so you can reach them first.

• 05Rolling in

  One pane for visibility

  SEO audits + Search Console, GA4 analytics, and ad spend — under the same roof, instead of a row of separate dashboards.

• 06Live in beta

  Buyer persona export

  Export your trained buyer model anytime — JSON persona you own outright. It travels with you. The model only keeps compounding while you're pulling leads through StackSwap OS, but the snapshot is always yours. No hostage data.

Recommended integrations

The stack that wires StackSwap OS together.

StackSwap OS runs on your own API keys and connects to the tools you already own. The two highlighted below are our recommended partners — we use them ourselves and think they’re the best fit for most teams running this motion.

• CRM to sync, not replace

  Partner

  HubSpot · Attio

  Powers Customer Success

  Sign up →

• Call intelligence

  Partner

  Fireflies.ai

  Feeds Sales

  Sign up →

• Lead + enrichment data

  Bring this

  Clay · People Data Labs

  Powers Lead Gen

• The agent brain

  Bring this

  Anthropic — your own API key

  Powers your agent team

• Open API — wire it to anything

  Bring this

  REST · JSON · any stack

  Push leads in from any source. Pull scored results to your CRM, sequencer, data warehouse, or ad platform. Full docs at /apis-and-mcps.

  Integrates everywhere

• Payments + licensing

  Bring this

  Stripe · Paddle

  Powers the business

• Email verification

  Optional

  NeverBounce · ZeroBounce

  Sharpens precision

• Visitor de-anonymization

  Optional

  RB2B

  Sharpens Marketing

• Scheduling

  Optional

  Cal.com — self-hostable

  Closes the Sales loop

• Ad platforms

  Optional

  Google Ads · OpenAI Ads · Meta

  Fuels Marketing

Partner links earn us a commission at no extra cost to you — it’s how we keep StackSwap OS in build.

Why precision is the product

Every lead pulled makes the model sharper.

API + Headless

Hook it to your AI agent. Use it headless.

Every route in the SS OS dashboard is available via REST API. Your Claude project, your Codex pipeline, your custom enrichment workflow — pass a domain or company, get back the stack signal, fit score, and drafted opener. Credits pull from your account exactly as they do in the UI. Every API pull trains your buyer model too.

POST /api/enrich
Authorization: Bearer <your-api-key>

{ "domain": "northwind.io" }

Wire it in

SS OS sits in the middle. Any lead gen in, enriched lead out.

It’s not a destination — it’s an enrichment and training layer that upgrades every lead that passes through it, regardless of where the lead came from. Apollo, Clay, your CRM, a CSV, a webhook — every lead that flows through gets the intelligence layer added and trains your buyer model before it hits your pipeline.

• Lead gen → enrichment → CRM

  Apollo / Clay→SS OS→HubSpot / Salesforce

  Pull leads from any source. SS OS adds stack intel, fit score, and opener draft. Routes clean to your CRM — with buyer model training on every record, no extra step.

• CRM list → stack intel → back

  Your CRM segment→SS OS→Enriched back

  Export a segment or paste a CSV. SS OS adds the intelligence layer and writes it back as custom properties — ssos_detected_stack, ssos_fit_score, ssos_opener — on every company.

• Full chain: gen → enrich → sequence

  Any lead gen→SS OS→CRM→Instantly / Outreach

  The complete pipeline. A verified contact with stack angle and drafted opener comes out of SS OS — your sequencer sends it, your CRM tracks it, your buyer model learns from it.

• Headless / API

  Your code / Clay / Claude→POST /api/enrich→JSON result

  Bearer token, one POST. Returns stack signal, fit score, verified contact, and opener. Credits only on validation. Every API pull trains your buyer model — same as the UI.

The buyer model trains on every pull — UI, API, or webhook — because the training happens at the data layer, not the interface layer. Your model gets smarter whether you’re clicking in the dashboard or running a 10,000-row batch enrichment from Clay.

Works with

Plug SS OS into the tools your team already uses.

Pricing

A flat base, plus credits for what you enrich.

Two plans — Starter $49/mo, Max $79/mo — both with the whole product. The plan just sets your credit rate. Then you top up credits as you enrich: 1 credit for a raw lead, 2 for full stack and spend intelligence. No per-seat tax, no refunds, and credits never expire while you’re subscribed.

Questions

The honest FAQ

• What does StackSwap OS actually do?

  StackSwap OS is a lead intelligence and proprietary buyer-model training system. It reads a company's real stack, scores how well each lead fits your ICP, and trains a buyer-scoring model on your actual conversion outcomes — using the full lead record, not just the stack signals it adds. Company size, industry, title, seniority, location, funding stage, growth signals, tech footprint — all of it trains the model. Month 1: standard fit scores. Month 3: the model retrains and becomes 15–25% more accurate. Month 6: your model is bespoke to your conversion patterns. Month 12: switching cost is nearly infinite, because you've built something no one else has.

• Can it source net-new leads, or only enrich my list?

  Both — they are the two routes. Intelligence sourcing: you pick a signal (a tool, a category, a company size, a spend tier) and StackSwap OS surfaces the matching companies from 12M+ tracked, pulls the seniority-filtered buying committee, and routes them into your CRM. List enrichment: you bring a CRM segment or a CSV and it adds the stack-intel layer — detected stack, recoverable spend, displacement angle, fit band — then writes it back or exports it. It pushes and pulls with HubSpot, Salesforce, Pipedrive, Attio, Close, and Zoho, or you export a CSV.

• When am I charged a credit, and what does "validated" mean?

  You are charged only on a validated match, and a no-match is always free. "Validated" means two things are true before a credit moves: the email is deliverable, and the company is confirmed running the tool you set. StackSwap OS verifies deliverability at pull time — NeverBounce for single leads, MillionVerifier for bulk — a layer that the underlying data sources do not provide. A lead is billed at the tier it actually validates into: top-tier stack intel (named displacement angle, buyer-model fit 75+, verified contact) is 3 credits, stack-aware is 2, a raw validated contact is 1, and a company we scan and return nothing on is 0. You never pay for a bounce or a phantom contact.

• Do I need to be technical?

  No. You connect your accounts and your team of AI agents runs it for you. Plug in your keys, pick your targets, and the agents do the work.

• Is my data private?

  Yes. It runs on your own AI keys, so your leads, emails, and customer data stay on your side — nothing is resold, and nothing routes through us.

• Will it replace my CRM?

  No. It syncs your CRM; it doesn't replace it. Keep the system of record you already trust.

• What if I want to switch a vendor later?

  Swap it in a click. Changing your enrichment, sending, or AI provider is a setting — not a rip-out project.

• How does pricing work?

  A flat monthly base plus prepaid enrichment credits. Two plans — Starter $49 and Max $79 — both include the whole product; the plan just sets your credit rate. A raw lead with a verified email is 1 credit; full stack-and-spend intelligence is 2. Credits start at $1 and ladder down in bulk (as low as $0.50 on Max). The buyer model you train on your outcomes is yours to keep. No per-seat tax, no refunds, and credits never expire while you are subscribed. Founders lock 25% off the base for life.

• When can I get it?

  Closed sandbox beta starts July 1, 2026. Beta users start training their buyer model on real ICP data before launch — so by the time the product goes live, their model is already 3 months ahead of new customers. Grab a Founders Club spot now ($99) to get in first.

Go deeper

The whole platform, page by page.

The routes, the engine under them, what it costs, and how it stacks up against the tools you’re probably paying for now.

While you wait

Two free tools from the same intelligence layer.

The AEO Audit scores whether AI buyers can find and cite you. The free MCP drops the stack intelligence engine directly into Claude. Both are free, no signup required.

← The GTM AI Toolkit