Treat your Customers as Individuals

Personalize your offering to each visitor one-on-one, in real time, with a scalable AI delivery infrastructure tailored to your business goals

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AI Personalization, personalized to you​

Go beyond demographics, segments and focus groups. Learn the behaviors, preferences and desires of every user human to deliver a custom experience – every time, at every point of interaction.

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Industry-Leading AI Infrastructure​​

Deploy advanced AI features to your services and delight your users, just like Netflix, Google or Amazon are doing.​

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No Vendor Lock-in​

Fly high and free! Unlike ‘black box’ personalization services, we don’t trap your data, IP and predictive methods inside our platform.

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Integrated with Your Workflow

PrimedIO works seamlessly with your customer infrastructure, data feeds, interaction points and prediction models (yes, blended models too).​​​

Reliable AI product features for all

100ms Guaranteed Latency
99.5% SLA uptime
>1,000 Requests/s Horizontally Scalable
Step up your AI pace and race closer to the tech leaders, without spending years and millions on development. PrimedIO gives your data scientists and domain experts the infrastructure they need to rock your customers' world.
Diagram of PrimedIO offerings and data flowsFlowchart demonstrating how PrimedIO server architecture, combined with PrimedIO Features, APIs, and Admin GUI, combine with your predictions and models, as well as PrimedIO data partners, to result in a personalized experience. This personalized experience increases satisfaction for your customers.

Out-of-the-box cloud integration Technology Partners

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Go to Kubernetes
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Listen

Track user interaction across your ecosystem

Easily integrate PrimedIO into every consumer-facing aspect of your service to discover behavior and usage patterns. Track and manage every channel and device from a single platform.

Behavioral Tracking

Learn

Meet the humans behind the data

Turn those clicks, views, hovers and conversions into desires, aspirations and preferences. Use any predictive models, business assumptions and architecture you deem fit: PrimedIO shapes around your imagination.

AI Blending

Delight

Provide recommendations and unique experiences

Blend your newfound interaction insights with business expertise and predict what each customer wants to see, when. Push predictions to PrimedIO via Python SDKs, or using REST, and never worry about performance, security or scalability.

Prediction Delivery

Improve

Fine-tune as you go

Define KPIs, campaigns and A/B testing* right inside the platform. Use built-in analytics tools to keep a tight eye on individual model performance and improve your users' experience in real time.

Analytics and A/B Testing

We value your time

PrimedIO is built around fellow developers and data scientists.

Work better and faster with front-end client libraries and data science pipeline integrations.

And bring your tools of choice: the platform is framework- and platform-agnostic.

Push Your Predictions

            
  model.signals.create(key=‘iPhone‘)
  universe.targets.create(key=‘itemX‘, value={‘msg‘ : ‘hello‘})
  predictions = [{‘signal_key‘: ‘iPhone‘, ‘target_key‘: ‘itemX‘, ‘score‘: 0.9}]
  pio.predictions.upsert(predictions)
  universe.campaigns.create(key=‘my.recommendations‘)
            
          

Build Personalized UX

          
  const result = pio.personalise({
    campaign:  ‘my.recommendations‘,
    signals: { device: ‘iPhone‘},
    limit: 5,
    }). then ( data => {
      data.results[0].target.key == ‘itemX’
      data.results[0].target.value == ‘hello’
    });
          
        
              
  pio.personalise({
    campaign:  ‘my.recommendations‘,
    signals: { device: ‘iPhone‘},
    limit: 5,
    }). then ( data => {
      data.results[0].target.key == ‘itemX’
      data.results[0].target.value == ‘hello’
    });
              
            
              
  NSDictionary *dictSignals = @{@”device“: @”iPhone“};
  [primed personalize:@”my.recommendations” signals:
  dictSignals limit:3 success:^(NSDictionary *response) {
  //Handle response
  } failed : ^(NSString *message) {
  //Handle response
  }];