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Intempt
A clam holding a glowing pearl as streams of bubbles flow into it.

A customer data platform your team can actually run.

Collect events once, resolve them to a person, and use them straight away with no modeling project first.

Start for free
Intempt customer data platform
G2
0.0on G2
10B+events
500M+users
7+years profitable
50+enterprises

Segment moves your data. It cannot build the audience.

What's in the CDP

Data Hub

Every event, profile and object on one schema. Identity resolution built in, no taxonomy to define upfront.

Events

Track it and watch it land. A live feed confirms every call while you are still in the code, then streams it out.

Integrations

Sources in, destinations out. Unlimited on every tier, including free.

AI Attributes

Predictive traits the platform computes for you. Churn risk, lifetime value, propensity, updated live.

AI Segmentation

Describe the audience in plain language. The segment resolves itself, no query to write.

Consent

Consent recorded per person and per channel, enforced in real time across every journey and every rule.

Workflows

Deliver events to your own Kafka, to webhooks, and to every destination you already use - each one a step in the same recipe.

Capture every customer signal once.

One snippet on your site or in your app, and every action starts arriving in the same shape.

  • Send the same event shape from web, app and server
  • Watch events land live as you click through your own product
  • Drop the mapping layer between tools
Capture every customer signal once

Turn signals into a customer story.

Anonymous sessions join the known profile the moment someone signs in.

  • Merge on identify rather than on a nightly batch
  • Stitch device IDs, emails and custom IDs together
  • Keep the visit from before the signup attached to them
Turn signals into a customer story

Build audiences without waiting on data teams.

Pick conditions and the group resolves itself, so marketing stops filing tickets.

  • Filter on any event, attribute or existing segment
  • Use computed scores like ordinary conditions
  • Let the segment keep updating as people change
Build audiences without waiting on data teams

Give every profile more useful context.

Scores and attributes that are calculated, predicted or researched, all usable as normal fields.

  • Score recency, frequency and spend with RFM
  • Predict any event you choose with likelihood
  • Research a fact that was never in your data at all
Give every profile more useful context

Put customer data where teams need it.

Publish to a Kafka cluster you own, land Parquet in your own bucket, or push to the tools your team uses.

  • Stream to topics you declared, in JSON or Avro
  • Write Parquet for your warehouse to read
  • Replay anything that failed once you have fixed it
Put customer data where teams need it

Keep your data costs simple.

Add as many sources and destinations as you want on any plan, free included.

  • Connect as many as you need, with no cap on any tier
  • Meter on volume rather than monthly tracked users
  • Stop at the cap instead of getting an overage bill
Keep your data costs simple

Collect from everywhere

Client, server and cross-platform

Seven SDKs feeding one schema. Instrument the browser, the app and the backend, and every event lands in the same taxonomy with the same identity resolution behind it.

Client-side

Auto-capture from the surfaces your customers actually touch.

Server-side

Send events your client never sees. Payments, jobs, webhooks.

Cross-platform

One integration for both app stores.

No cap on sources at any tier, including free. Instrument everything.

Intempt vs the customer data platforms

Segment has the larger destination catalogue. The rows below are about whether the data does anything once it arrives.

CapabilityIntemptSegmentcompareTwilio Engagecompare

Event collection

SDKs and sources feeding the profile

Included

450+ sources and destinations

Via Segment

Identity resolution

Anonymous to known to account

Included

Business tier

Via Segment Unify

Audience building

Segments from traits and behaviour

Included

Business tier

Included

Sends a message

The CDP itself reaching the customer

Included

Not offered

SendGrid plus Twilio

Channel coverage

Email, SMS, push, in-app, web personalization

All five native

None

Across three vendors

Product analytics

Funnels and retention on the same events

Included

Not offered

Delivery metrics only

Experiments

Testing on the audience you just built

Included

Not offered

Not offered

Revenue attribution

Tying the routed event to closed revenue

Included

Routes the data only

Out of scope

Who operates it

Who has to be on staff to change a destination

A marketer

Engineering

Engineering

Data portability

Warehouse sync, raw export, API

Included

Best in class

Segment grade

Pricing model

How the bill moves as you grow

On demand, no overage

Per tracked user, with a floor

Three meters

Every claim above is argued in full, with what they do better, on the linked pages.

Wired into the toolsyour team already opens.

Slack, Stripe, Twilio, SendGrid, Gmail, Google Calendar, Firebase, Apache Kafka, AWS. Blu Agent operates them for you without a browser tab.

See every integration
JavaScript
Node JS
Apple
Stripe
Gmail
Google Calendar
Google Meet
Twilio
SendGrid
Slack
Amazon SES
Webhook
Apache Kafka
Amazon S3
Firebase Cloud Messaging

Teams love it

They stopped stitching tools andhired one system.

StockInvest

Acquisition and retention are one connected motion. Personalizing the path before signup only pays off when the same system carries the user through onboarding afterward.

Anonymous traffic was not turning into registered users, and acquisition and retention were run as two separate problems. We ran Experiences on the anonymous visitor flow to put the right content and CTAs in front of each visitor, then handed new signups to automated Journeys for onboarding and deeper engagement.

455,396

users instrumented

Read the full research
FieldsUSA

Judge experiments on revenue per visitor instead of conversion rate. A variant can win on conversions and still lose on revenue, and repeat buying only shows up when the whole journey is in one view.

High-intent shoppers browsed a large, specialized outdoor catalog, and browsing, product interest and purchase history sat in different places. We unified them into one customer view, then ran real-time personalization, intent-based segmentation and timely follow-ups on top of it, judging experiments on revenue per visitor.

Read the full research
Hoperfy

Build the pipeline on observed signals. When follow-ups trigger on intent, the team spends its time on the users who are genuinely engaging.

Static lead lists and timeline-based follow-ups were hiding who was actually engaging. We ran a signal-led outbound pipeline where follow-ups fire on real behavior: outbound replies, onboarding progress and product usage.

Read the full research

Frequently askedquestions.

Collect the data, resolve the customer, build the audience, then use it wherever the team needs it.

No. Events arrive and resolve onto profiles here. If you also want the raw data in your own storage, we write Parquet into a bucket you own, but nothing is waiting on a modeling project first.

Intempt Data

Your pipeline. Your cloud. Your data.

Collect events from every source, resolve one profile per person, and let anyone describe an audience without writing SQL or waiting on an analyst. Free to start, with no cap on sources or destinations.

Start for free