Sold by: ecosystem.Ai
Deployed on AWS
The first low-code environment to combine behavioral social science with real-time machine learning. Create prediction projects (recommenders, experiments, interventions, generative, etc), manage data, models and experiments and productionize deployments.
Overview
ecosystem.Ai is a low code environment which uses a combination of AI and behavioral science to select the best campaigns, products, messages, and offers for your customers - in real time. Set up effective recommendations in minutes using our default Dynamic Recommenders and use Generative AI to enhance your interactions. Or configure your own AI algorithms, with control over all of the settings that impact how the recommendations are made.
The complexity and variability of humans means that change is inevitable; the ecosystem.Ai model serving platform assists you in delivering on those tight AI project deadlines with a robust platform that can be used to integrate your models into websites, apps, inbound call centers, outbound dialers, etc and access to a full set of API's.
The ecosystem.Ai platform: Creates revolutionary engagements by understanding the human in your system, using social science and behavioral algorithms. Seizes opportunities as they happen using truly real-time capabilities; model serving, features, dynamic experimentation and business integrators. Radically reduces the cost and time to market, for every deployment, by providing an effortless no-code/low-code deployment environment. What you get with this install: Prediction Server - allows you to manage many data engineering, data science, machine learning and other functions available through Python, the Workbench, or API's. Workbench - is a no-code front-end to perform end-to-end prediction project life cycle activities including the deployment of real-time behavioral predictions into production. Notebooks - comes with a number of default Python libraries and Jupyter Notebooks to guide you through any customizations you might need for predictions, experiments, simulations, etc. Client Pulse Responder - provides full runtime inference and scoring capabilities for dynamic or static real-time activities including logging, and is permanently in production. Grafana - make your real-time data come to life. It's a dashboard to track the performance of the use-cases implemented in the Client Pulse Responder Runtime.
Highlights
- Creates revolutionary engagements by understanding the human in your system, using social science and behavioral algorithms.
- Seizes opportunities as they happen using truly real-time capabilities; model serving, features, dynamic experimentation and business integrators.
- Radically reduces the cost and time to market, for every deployment, by providing an effortless no-code/low-code deployment environment.
Details
Sold by
Delivery method
Delivery option
64-bit (Arm) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 22.04
Deployed on AWS
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Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
c6g.xlarge Recommended | $15.00 |
c6g.2xlarge | $15.00 |
m6g.16xlarge | $30.00 |
c6g.12xlarge | $20.00 |
c6g.4xlarge | $20.00 |
m6g.xlarge | $15.00 |
m6g.12xlarge | $30.00 |
m6g.8xlarge | $30.00 |
m6g.large | $15.00 |
c6g.metal | $30.00 |
Dimensions summary
You pay by the hour for the AWS instance size you run the ecosystem.Ai Platform on. All 15 options deliver the same platform through a pre-configured Amazon Machine Image; they differ only in compute capacity. The c6g family targets compute-heavy workloads, while the m6g family balances compute and memory. Within each family, sizes scale from large up through metal, so the hourly rate rises as you add virtual CPUs and memory. You choose the instance that matches your workload, and billing tracks your actual running hours with no fixed commitment.
Top-of-mind questions for buyers
Both families run the same platform. The c6g family gives more compute power per unit of memory, which suits processing-heavy prediction workloads. The m6g family balances compute and memory more evenly, which suits workloads that hold more data in memory. Your hourly rate reflects the family and size you pick.
The hourly software rate meters running time only. When you stop an instance, software charges stop accruing. Underlying AWS resources such as storage attached to a stopped instance may still incur separate AWS fees, but those are billed by AWS, not by the platform's hourly software charge.
Every instance runs a pre-configured Amazon Machine Image with the same platform. This includes the Prediction Server, the no-code Workbench interface, integrated Jupyter Notebooks, the always-on inference runtime, and monitoring dashboards. Instance size only changes compute capacity, not which components you receive.
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Vendor refund policy
Our AWS Marketplace application doesn't offer refunds or credits for any used or unused service periods, as costs are incurred based on resource consumption.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (Arm) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Review product features on https://ecosystem.ai and connect with us on Slack. Full life-cycle support for static, dynamic and generative models for model training and inference and real-time continuous AI models for nudging, offers, etc.
Additional details
Usage instructions
Please assign your own security groups and related load balancing requirements.
Instructions: Launch the product via 1-Click Use a web browser to access the application at http://<EC2_Instance_Public_DNS>
Sign in using the following credentials: Username: admin@ecosystem.ai Password: the instance_id of the instance
Additional users and profiles can be maintained in the Workbench.
All data is stored in the instance and accessible via Python APIs, the Workbench, or via the instance directly. None of the data created or stored will be shared in any way whatsoever outside of your installation. The AMIs does not request or use access or secret keys from users to access any AWS resources.
Resources
Vendor resources
Support
Vendor support
Register on our Slack channel (https://ecosystemai.slack.com/archives/C018V6W2UFL ) for support. We provide algorithm support and assist with various types of use-cases. Free training and ongoing AI support options available. There is also a custom GPT for additional support use the ecosystem.Ai Use Case Designer V2:
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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