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Hightouch AI Decisioning

by HightouchYC S19No ratings yet

Reinforcement-learning decisioning for 1:1 message, channel, and timing across email, SMS, and push

Visit hightouch.com
Tool type
AI agents for 1:1 lifecycle decisions
Made for
Lifecycle and retention marketing teams
Runs on
Hightouch web platform on your data warehouse
Runs in the Hightouch web app and reads from the customer's data warehouse; it does not store that data.
Last checked
29 Oct 2026
6 product sources

What it does

AI Decisioning is a Hightouch product that uses reinforcement learning to decide, for each customer, which message, offer, channel, creative, timing, and frequency to use, including whether to send at all. It covers email, SMS, and push, and replaces manually built journeys and A/B tests with agents that continuously experiment and learn from every interaction.

Marketers set goals and target audiences, supply approved content, and define guardrails such as allowed actions and send-volume thresholds. The product reads customer data directly from the data warehouse without storing it. Teams can then review performance lift against a holdout group, set the attribution window and metrics, and see which content performs for each segment.

It suits lifecycle and retention marketing teams that already keep customer data in a warehouse and want 1:1 personalization while retaining approval control. It is listed on the pricing page as part of the Agentic Marketing Platform, with a pre-set monthly allowance of personalized actions, and the page directs buyers to request a demo.

What it can do

  • Decides the message, offer, channel, creative, timing, and frequency for each customer on a 1:1 basis, including whether to send at all
  • Uses reinforcement learning to continuously experiment and optimize paths to conversion
  • Lets marketers define goals, target audiences, allowed actions, content, and send-volume thresholds as guardrails
  • Reads customer data directly from the data warehouse without copying or storing it in Hightouch
  • Reports performance lift against a holdout group with marketer-defined attribution windows and metrics
  • Surfaces top-performing segments and content with AI-sorted charts and recommendations on adding, refreshing, or retiring content

Works with

  • Data warehouse (read directly, per the AI Decisioning page)
  • Email, SMS, and push channels (per the AI Decisioning page)

Before you choose

  • The product reads from your data warehouse and does not store data; you need a warehouse-based data setup.
  • Marketers review and approve AI outputs; guardrails and approvals control what is sent.
  • Pricing is usage-based within the Agentic Marketing Platform; confirm the monthly personalized actions allowance and overage terms with sales.

Listed under

Get started

The page's primary call to action is a demo request; pricing details are on the pricing page.

  1. Define goals for your decisioning agents by setting target audience and business outcomes.
  2. Provide content and set guardrails by authorizing allowed actions, content to use, and send-volume thresholds.
  3. Review performance and lift against the holdout group, and confirm the attribution window and metrics you want to track.
Request a demo or contact sales

Plans and prices

Pricing is usage-based within the Agentic Marketing Platform, which lists a pre-set amount of monthly personalized actions. Request a demo or contact sales to confirm the rate, allowance, and overage terms.

Agentic Marketing PlatformUsage-basedUsage meter named on the pricing page; confirm the rate with sales.
  • Pre-set amount of monthly personalized actions
  • Includes AI Decisioning, Ad Studio, and Lifecycle Studio

Source: hightouch.com/pricing, checked 29 Oct 2026. Prices can change; check before you buy.

Sources for this overview

Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.

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What’s changed

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Where this comes from

How we research
Company website
hightouch.com: product, pricing and policy pages
Hacker News
Launch posts and discussion
YC directory mirror
Batch and company name
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knowledge_base
manual_review

Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.