Aampe for Data Science
Agentically generate clean, labeled data from daily engagement
With Aampe, non-technical teams deploy communications that build structured datasets as they work, converting everyday messaging into a continuous source of reliable training data for data science. It's a human-in-the-loop engine for data generation.
Overview
Adaptive feature flagging that learns user preferences across models
Aampe replaces binary feature flags with agents that experiment continuously across tagged variants—even competing models—discovering which data-generating process best matches each user's preferences and evolving as those preferences change.
Benefits
Agentically manage user-level experimentation and treatment optimization
Clear causal signals for deeper explainability and smarter exploration
With Aampe, non-technical teams deploy communications that build structured datasets as they work, converting everyday messaging into a continuous source of reliable training data for data science. It's a human-in-the-loop engine for data generation.
Continuous feature engineering through semantic abstraction
Teams define abstract concepts, and Aampe agents automatically populate those dimensions with user-specific data. The result is a living, high-resolution feature space that updates in real time for downstream models.
Causal distributions for every action, enabling counterfactual policy simulation
Every user interaction feeds into a Beta distribution representing the causal strength of that action. These distributions allow teams to simulate new policies, compare hypothetical interventions, and quantify uncertainty — turning experimentation data into a flexible substrate for policy design and evaluation.
Product
Collaboration without coordination overhead
Aampe's agentic infrastructure orchestrates experiments intelligently, so marketing and product teams can launch new ideas without disrupting active tests.
Data scientists can deploy updated models directly into the same interface, where agents route predictions into clean, abstracted features that other teams can use immediately.
Integrations
Integrate seamlessly
and deploy in days
Al-driven optimization works with your existing tech stack—no SDKs, custom development, or complex setup needed. Sitting on top of current communication platforms, it enables rapid deployment without heavy engineering work, so teams can focus on performance, not implementation.
Do I need "the basics" set up before I use Aampe?
No. Aampe *is* the basics (plus a whole lot more)! For example, you don't need to have user journeys set up before we can optimize. In fact, our customers don't set up user journeys at all! We achieve individualized personalization through the actual messages you send, so you don't need any formal messaging structure to get started. You only need a CPaaS connection so we can send message and a CDP connection so we can track impact.
How hard is it to get started?
Set up is a snap: Add your CDP and CPaaS API keys, set your goals, and you're ready to start writing!
Does Aampe replace my current CRM platform or CPaaS provider?
It doesn't have to! Aampe can work right alongside your current CRM platform or CPaaS provider, making them function better by producing much better results more efficiently. With a simple API connection, you can enable new levels of messaging personalization without having to spend time and effort building rigid segments and static, over-generalized user journeys.
How many users do I need for Aampe to work?
Aampe doesn't need a large number of users to operate. We have apps with fewer than 10,000 users already seeing impressive results. If you write quality messages, we can use them to engage an audience of any size.
Our app is already instrumented and an external provider captures our events, do we need to integrate Aampe within our app?
Not at all. Aampe will pull the relevant event data from the service you've instrumented your app with so the effort on your engineering team is kept to minimum.
How can we share data with Aampe?
You can share data with Aampe using a dump into a storage bucket (AWS, GCP, Azure, etc.), via SFTP. For more details refer to our Integration Guide. Cannot find your preferred method for data sharing? Let us know and we'll be happy to figure it out with your team.
How do we test that push notifications are received as expected?
There are a couple of options here. The preferred option is that an Aampe engineer installs the app on their test device (either from the store or using an APK). In that case, Aampe does all testing needed. In the cases where this is not possible, the alternative option is that you provide Aampe with a few user IDs either from your team or your test devices, and testing will be done in collaboration with your team.
Does Aampe require static segmentation?
No. Aampe uses semantic content labels and per-user learning rather than relying on broad predefined buckets.
Does Aampe just optimize for clicks?
No. The internal materials position Aampe as learning across multiple horizons and using reward functions to connect short-term signals with longer-term outcomes such as retention, revenue timing, and sustained engagement.
How does Aampe learn?
Aampe learns from real user behavior using tagged content, reward signals, abstraction layers, social calibration, and next-best-action policy selection to update what each agent believes from real user behavior.
Is Aampe just machine learning?
No. Aampe relies primarily on real-world experiments, then uses machine learning to collect, generalize, and apply findings faster. We also use AI to support or perform tasks like writing copy, organize, and draw insights from user behavior, and identify messaging impact. Our hybrid approach of using both experimentation and machine learning avoid many of the common pitfalls of a naive ML approach.
I already have an amazing Data Science team, why do I need Aampe?
Aampe frees your data science team to work on more productive things. Instead of bogging them down with requests for reports or messaging A/B tests, they can spend their time running more valuable analyses, doing the kinds of work that only they can do.
I don't have a Data Science team, can I get any benefit from Aampe?
Absolutely! Aampe runs many of the tests and reports that a typical data science team normally would. Now apps of any size can have the same capabilities as the big guys.
If Aampe fully automates my CRM, do I lose control?
Absolutely not! Even with Aampe running, you're still able to add or remove messages, constrain messages to certain time windows, send ad hoc messages, or even stop sending messages entirely.
Can I still send ad-hoc messages to my customers if I need to?
Of course! (Although most of our customers report needing to send fewer ad hoc messages after starting with Aampe.) While Aampe is running, you can still send individual messages from your current customer communications platform.
Can Aampe help generate content or does it just select and schedule it?
We sure can! Aampe is designed to help you build a messaging library of thousands of unique and instrumented messages in minutes in a Bring Your Own Model approach. Check out how it works.
Does Aampe just help with sends and clicks, or can it help with mid and bottom of the funnel actions too?
Aampe helps with much more than clicks! One of the first steps of using Aampe is setting your goals. These may be any user action that you're able to track — anything from clicks to sessions to conversions — and, once they're set, Aampe optimizes for these goals.
Why should I trust Aampe's product and technology?
At Aampe, our answer will never be "Just trust us." In fact, we hate the "black box" mentality so much, we've gone to great lengths to explain how our system works for non-technical users, and we've even written a detailed whitepaper to explain our system to technical users! If you have any questions, please reach out! We love talking about how we make personalization better.
Continuous intelligence for customer engagement
Move beyond campaigns.
Let agents optimize every
interaction.
