Your stack, your channels, a more persuadable audience.

atlas is the audience intelligence system behind every enterprise engagement. It works with the data you already hold, resolves it to people and households, scores whose behavior will change and why, and returns the answer to the channels you already buy. Nothing to replatform.

Your CRM record

No reason. No timing. No message.

Leaves your environment as

  • Email········
  • Phone········
  • Name and ZIP········

SHA-256, hashed on your side. Raw records stay put.

Back in your CRM

Behavioral layer

Lead with

Delivered to

  • CRM and email
  • DSP and social
  • Warehouse and BI

Architecture

Hashed keys cross. Your raw records stay put.

atlas sits between your systems and your channels. Only hashed keys cross the match boundary. Scores come back to where your teams already work, and the outcomes you agree to share return every day to check and retrain the models.

Your environment

CRM or CDP

Customer file: email, phone

Data warehouse

Share or export, hashed keys

Site and app

Pixel, first-party events

Media stack

Seed audiences, DSP and social

Outcome systems

Conversions, funded accounts, enrollments

ConnectSFTP · warehouse share · API · pixel · clean room

atlas · audience intelligence system

Resolve

270M+ U.S. adults resolved · one key per person and household

  • Hashed email and phone
  • UID 2.0
  • Household key

Gravity · model engine

Calibrated 0 to 1 · versioned · digital activity refreshed daily, graph rebuilt monthly

  • Propensity
  • Motivation
  • Decision style
  • Receptivity
  • Persuadability
  • Publish gate

Organize and evaluate

Audience builder, holdout split, baseline checks

  • Thresholds
  • Neighbor separation
  • Holdout split
  • Cohort cards
DeliverAudiences and scores · API · warehouse share · clean room

Your channels

CRM and email

Scored records and a next-best message

DSP and social

Hashed audiences, seeds and suppressions

Warehouse and BI

Scores joined to your own models

Clean room

Match, score and evaluate in place

Outcome labels return

Conversions feed the daily retrain

GovernanceEthnicity and ideology never selectable · permitted uses documented · scores versioned and labeled · kill decisions logged · SOC 2 Type I report under NDA
Architecture of an atlas engagement. Your systems connect to atlas across a match boundary that only hashed keys cross; raw records stay in your environment. atlas resolves identities, scores them with Gravity and organizes audiences, then delivers audiences and scores back to your CRM, media, warehouse or clean room. Outcome labels return and retrain the models daily.

Runs where your data already lives.

Runs on

  • Databricks

Delivers to

  • Meta
  • Google Ads
  • TikTok
  • LinkedIn
  • Snowflake
  • LiveRamp
  • Pinterest
  • Snapchat
  • Reddit
  • X
  • Microsoft Advertising
  • Amazon Ads
  • Yahoo DSP

Connects with

  • Salesforce
  • HubSpot
  • Marketo
  • Braze
  • Mailchimp
  • Twilio
  • Segment
  • mParticle
  • Google BigQuery
  • Amazon S3
  • Shopify
  • Google Analytics

And any DSP, clean room or platform that takes hashed files or UID 2.0.

What it does

Six ways we move a number you already report.

Each is scoped to one decision, measured on a holdout you control and read out on day 60.

  1. 01

    Find who isn’t in your file

    Score 270M+ U.S. adults for readiness on your decision and deliver the people most likely to act whom you aren’t already reaching.

    MeasureCost per acquired customer against your current audiences

  2. 02

    Say the thing that moves them

    Group the audience by motivation and attach a message hypothesis to each group. Your creative team tests the variants.

    MeasureConversion-rate lift by motivation group, in a controlled test

  3. 03

    Reach them when they’re ready

    Readiness concentrates in windows of the day and week. Media and outreach run in those windows instead of the category default.

    MeasureCost per outcome against your current flighting

  4. 04

    See the change inside your base

    Recognize changing needs within existing customers: a consumer becoming a business, a patient whose regimen is shifting.

    MeasureAdditional product relationships and cross-sell rate

  5. 05

    Catch switching before it happens

    Comparison behavior that comes before a switch triggers outreach while there is still a decision to influence.

    MeasureRetained relationships or balances against a control

  6. 06

    Prove it against your own model

    Held-out evaluation of your current model with and without Moonbrush signals, then controlled activation on the agreed outcome.

    MeasureAUC and top-decile lift, then incremental outcomes on your holdout

The engagement

Sixty days to an answer you can audit.

Every engagement starts as a proof of concept on your own data. If it doesn’t beat the baselines on your holdout, you’ll know on day 60.

  1. Week 0

    Agree the decision, the data and the success criteria. Paperwork includes the data use agreement and the acceptance criteria.

  2. Weeks 1–2

    Match keys and attach scores in the clean room or your warehouse. Your match rate is reported before anything is built.

  3. Weeks 3–8

    Activate in your channels against a holdout you control. Outcomes return as they happen.

  4. Day 60

    Read-out on lift and impact, with the validation report. Then an annual program, if the numbers earn it.

  • Integration

    We connect to your warehouse, CRM, clean room or media stack, matching your DSP’s spec when it has one.

  • Data onboarding

    Your file is matched under one identity key, and you see the match rate before any model is built.

  • Applied intelligence

    A Moonbrush team builds and validates the models with you, and writes the cohort cards and message hypotheses.

  • Enablement

    Your analysts get the scores, the validation report and view-only dashboards or API access to keep using them.

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