Aampe
Agentic engagement infrastructure giving every user a dedicated agent for continuous messaging personalization and experimentation
Pricing
Paid
Platforms
Web, API
Developer
Aampe Inc.
Rating
4.5 / 5.0
Last Updated
September 3, 2026
Overview
Aampe is agentic infrastructure for customer engagement.
Instead of static segments and fixed journeys, it assigns a dedicated agent to every individual user, and that agent learns user behavior and preferences in real time to decide the next best message.
The company has raised $18M to pioneer what it calls Continuous Intelligence and says it is trusted by some of the most forward-thinking consumer companies.
Setup is deliberately thin — add your CDP and CPaaS API keys, set your goals, and the system starts learning.
Use Cases
Upgrading lifecycle messaging (activation, retention, re-engagement) from manual segments and fixed journeys to real-time per-user decisions
Running thousands of parallel variants of push, email, and in-app messages to replace one-A/B-test-at-a-time optimization
Building and refreshing audiences automatically from live behavioral signals to cut manual segmentation workload
Delivering causal insights on which behaviors drive conversion and retention for product and growth teams
Adding an intelligent decisioning layer on top of an existing CDP and messaging stack without migrating platforms
Who Is This For
Lifecycle marketing teams at consumer brands, DTC companies, and apps with large user bases
Growth teams that already run a CDP and messaging providers and want a smarter decisioning layer
Operations leaders weighed down by manual segments and fixed journeys who want continuous experimentation
Product and data science teams needing explainable attribution and causal behavior insights
Mid-size to enterprise companies willing to go through a sales-led pilot (no self-serve subscription)
Key Features
A Dedicated Agent per User
Every individual user gets an agent that learns behavior and preferences in real time, compounding knowledge across campaigns, launches, and lifecycle stages.
Parallelized Continuous Experiments
Tests thousands of content, timing, and channel variants in parallel instead of one A/B test at a time, constantly learning and optimizing for impact.
Self-Evolving Audiences
Audiences update automatically from live behavioral signals, engagement patterns, and lifecycle context, reducing manual segmentation work for marketing teams.
Causal Insights and Explainability
Produces causal distributions for every action with counterfactual policy simulation, so optimization is explainable instead of a black box.
Fast Stack-Agnostic Setup
Add CDP and CPaaS API keys, set your goals, and agents begin learning — no user journeys, static segments, or manual models need to be built first.
Pros & Cons
Pros
- Individual-level personalization rather than segment-level: a continuously learning agent per user is the core differentiator versus static-segment tools
- Experimentation at scale: thousands of variants tested in parallel, replacing the one-A/B-test-at-a-time rhythm
- Light integration: connects to your existing CDP and CPaaS; the company says customers do not set up user journeys at all
- Causal distributions and counterfactual simulation make optimization explainable and feed product and data teams with actionable insights
- Backed by $18M in funding as a category pioneer in Continuous Intelligence, with outcome metrics such as incremental purchases and GMV uplift highlighted on the site
Cons
- No public price list — engagement is sales-led with custom pilots, which is opaque for smaller teams
- A decisioning layer, not a sending channel: you must already run a CDP and a messaging/CPaaS provider
- Built for consumer-scale audiences; small B2B lists get limited value from per-user agents
- Stated outcome figures (incremental purchase and GMV uplift) need a sales demo or case study to verify
Pricing Plans
Pilot
Sales-led pilot: connect your CDP and CPaaS keys, set goals, and validate results on a limited audience before contracting.
- Connects to your existing CDP and messaging providers
- Controlled experiments aligned to business goals
- Outcome reporting and insight delivery
Enterprise
Full subscription with per-user agents across your entire audience, continuous experiments, and causal analytics.
- Dedicated agents for every user at scale
- Thousands of parallel experiment variants
- Causal distributions and counterfactual simulation
- Customer success and integration support
Frequently Asked Questions
Editorial Review
Editorial Team
August 29, 2026
Editorial verdict: in a year where agentic marketing is an overused label, Aampe is one of the few products that genuinely pushes agents down to the individual user level and replaces one-off A/B tests with continuous parallel experimentation. Unlike Humanic or Questera, which generate and send their own lifecycle campaigns, Aampe sits on top of your existing CDP and messaging stack and focuses purely on the decision layer — a clean architectural choice for teams that do not want to rip out their current ESP.
Editorial Team
September 2, 2026
The deductions are about transparency: there is no public pricing, and the incremental purchase and GMV claims on the site need a demo to verify. This is enterprise software sold through pilots, so teams without a CDP and CPaaS foundation should not expect plug-and-play value; B2B teams with small lists should run a pilot before committing.
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