Listing Thumbnail

    AI Spark: Governed Entry Point for AI in Regulated Environments

     Info
    Sold by: TomorrowX 
    Deployed on AWS
    AI Spark is a governed entry point for AI: a bounded operational use case connected through TomorrowX Data Mediation™, deployed into your AWS account, without replacing existing systems. Many AI ideas stall between demonstration and production because live workflows introduce real data, identity, approvals and risk. AI Spark connects the model to a meaningful but contained workflow through a governed mediation boundary, so data access, output handling and action are controlled and evidenced from the start. Organisations retain full control of infrastructure, security and network boundaries, including in regulated, secure and air gapped environments. Designed for partner-led delivery, AI Spark produces an operational proof with visible controls and evidence for business, risk and technical stakeholders, and a reusable capability for scaling AI adoption.

    Overview

    AI Spark is a governed entry point for AI in complex and regulated environments, built on TomorrowX Data Mediation™. It moves an AI idea from a conversation to a controlled, demonstrable interaction with the systems and workflows that matter, deployed into the customer AWS account and without replacing existing systems.

    Public sector and regulated organisations are already experimenting with AI, but progress often stalls before production. Many AI ideas can be demonstrated with documents and conversation; operational value begins when AI participates in a real workflow, which introduces live data, identity, approvals, exceptions and downstream consequences. Governance, compliance and risk concerns make it difficult to deploy AI safely in live environments, especially where legacy systems and constrained architectures limit deployment options. Programmes therefore remain demonstrations or jump too quickly into integration.

    AI Spark creates a contained path to operational relevance. A meaningful but bounded workflow is selected, data access, controls, evidence and acceptance criteria are defined, and the model is connected through a governed mediation boundary, so data access, output handling and action are governed from the start. The outcome is demonstrated with visible controls at the point of system interaction and evidence for business, risk and technical stakeholders, and the organisation decides whether to scale, revise or stop.

    Customers retain full control of infrastructure, security and network boundaries, including in regulated, secure and air gapped environments. AI Spark is designed for partner-led delivery, and the mediation capability established is reusable for further AI deployment, giving organisations a controlled and repeatable path to AI adoption.

    Highlights

    • Governed entry point for AI: a bounded operational use case proven with visible controls and evidence, not a standalone chatbot demonstration.
    • AI connected through a TomorrowX Data Mediation™ boundary governing data access, output handling and action, without replacing or re-platforming existing systems.
    • Deploys into the customer AWS account for full infrastructure, security and network control, including regulated, security-sensitive and air-gapped environments.

    Details

    Delivery method

    Supported services

    Delivery option
    CAP Agent - ECS Fargate

    Latest version

    Operating system
    Linux

    Deployed on AWS
    New

    Introducing multi-product solutions

    You can now purchase comprehensive solutions tailored to use cases and industries.

    Multi-product solutions

    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.
    Financing for AWS Marketplace purchases

    Pricing

    AI Spark: Governed Entry Point for AI in Regulated Environments

     Info
    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.

    Usage costs (1)

     Info
    Dimension
    Description
    Cost/unit/hour
    Hours
    Container Hours
    $82.19178082

    AI Insights

     Info

    Dimensions summary

    You pay for this product by the container hour. Billing is usage-based, so your cost tracks how long the container runs. There are no tiers or fixed quantities to select. The single dimension scales directly with your runtime hours. You add up the hours the container is active, and charges follow that total. This model connects an AI use case to a bounded workflow through Data Mediation, running inside your controlled environment. Because pricing is metered by the hour, you can start with a contained proof and let usage grow or stop as needed.

    Top-of-mind questions for buyers

    One container hour is one hour of runtime for the deployed container running the Data Mediation solution. The clock accrues while the container is active in your controlled environment. Partial hours and total active time roll up into your metered charge. Counting follows how long the container runs, not the number of users or workflows.
    Charges follow active runtime. When the container is not running, software hours do not accrue. This lets you start with a contained proof, then pause when the workflow is not in use. Note that underlying AWS resources, such as storage, may still incur separate AWS fees while stopped.
    You connect a model to a bounded workflow and pay only for the hours the container runs. There is no upfront quantity to commit. This fits a contained proof where you demonstrate an outcome, then decide to scale, revise, or stop. Cost tracks runtime, so it grows or shrinks with your activity.
    tomorrowx.com
    Helpful?

    Vendor refund policy

    Please contact TomorrowX for refund & policy https://tomorrowx.dev/get-help/ 

    Refer to the AWS Marketplace Buyer Guide for further details regarding:

    How can we make this page better?

    Tell us how we can improve this page, or report an issue with this product.
    Tell us how we can improve this page, or report an issue with this product.

    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.

    Usage information

     Info

    Delivery details

    CAP Agent - ECS Fargate

    Supported services: Learn more 
    • Amazon ECS
    Container image

    Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.

    Version release notes

    Maintenance release for the AI Spark full stack deployment. The CAP Agent engine moves to build 30180 and now reports 12.1.14 B30180: an agent that cannot load a deployed configuration now reports the cause to the CAP Console and is left without a running configuration, instead of restarting its previous configuration against files the deploy had already replaced. The deployment's initial configuration snapshot is re-cut against this release and carries Base Rules build 30180. The embedded Jetty runtime stays at 12.1.14 and Java moves to 21.0.13. This is a drop-in replacement for cap-agent:48a29b4: the CloudFormation template URL, launch steps, template parameters, task definition shape, environment variables, EFS mount path, port mappings (8080 web, 20001 management), ALB health check path, and CAP Console connection workflow are all unchanged.

    Upgrading to this release: Existing stacks pick up the new image on their next service update (force a new deployment of the agent service); no template change or stack update is needed. Install Base Rules 30180 through the CAP Console update workflow and redeploy to bring existing agents current - the configuration snapshot only seeds new deployments. Apply CAP Console 12.1.14:30180 as well to see the cause of a failed configuration load on the agent status panel; an earlier CAP Console still does not start an agent whose load failed, but the cause is then only in the agent log. If you are upgrading from an image older than cap-agent:48a29b4, the first configuration deploy to each agent sends the full set of extensions once. Step-by-step upgrade instructions: https://tomorrowx.com/go/cap-distribution-refresh 

    Documentation: https://docs.tomorrowx.com/cap/vZHo2144m1e79o3WX0RU  Support: help@tomorrowx.dev 

    Engine fix: When a deployed configuration could not be loaded, for example because an extension it needs was missing, the agent logged the error but told the CAP Console the reload had succeeded. The CAP Console then started the agent, which revived its previous configuration against files the deploy had already replaced, and the error that surfaced pointed at the wrong thing. In build 30180 the agent reports the failure and its cause to the CAP Console and is left without a running configuration, the same state as an agent that has not yet been deployed to; the CAP Console shows the cause on the agent status panel and does not start the agent. Correct the cause and deploy again. After a failed load, loads triggered by incoming web requests are retried at most every 30 seconds. Agents whose configuration loads normally are not affected.

    Base Rules 30180: Agents using scoped deploys no longer fail to load for want of the Apache Commons IO library, which now ships with Base Rules. File and batch input keep to the Concurrent thread limit, so an agent with a low value may process files more slowly; raise the setting where needed. Socket listeners can limit how many connections they serve at once and close connections that have gone idle. UDP messages and replies now arrive complete and at their real length rather than cut at 512 bytes. The file output log adaptor writes each line without holding up other agent work. Rule execution semantics are otherwise unchanged.

    Snapshot refresh: The initial configuration snapshot the stack restores on first launch is re-cut against this release. It carries the 12 extensions used by the AI Spark deployment, including Base Rules build 30180 and the November 2026 release of the data set rules, from which the unused Sync Data Sets rule has been removed; the other extensions are the same releases as in the previous snapshot. The snapshot includes the agent's record of its active extensions, so the first deploy to a new stack sends only extensions that differ from it. Deployments created from this image start current; existing deployments update their extensions through the CAP Console update workflow as before.

    Dependency review: Java moves to 21.0.13 (Temurin 21.0.13+9), the October 2026 Java update. No other library changes in the image: Jetty 12.1.14 with virtual threads on HTTP ingress, pgjdbc 42.7.13, and all prior CVE remediations are retained. Ubuntu 24.04 LTS base OS packages are refreshed to current at image build time. A healthy CAP Agent launch continues to log zero WARN, zero ERROR.

    Compatibility: No breaking changes for existing customers. No CloudFormation template changes in this release - stacks launched with the same inputs behave identically. No session cookie changes, so no sign-out on update. CAP rulesets and extensions run unchanged on this image, except that a rule set still using the removed Sync Data Sets rule fails to load and now reports that on the agent status panel. The protocol between the CAP Console and the agent gains a failure reply to a reload; CAP Console and agent builds from before and after this release work together.

    Additional details

    Usage instructions

    Quick Launch

    Deploy a CAP Agent using CloudFormation (change the region in your AWS Console to your preferred region first): https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://public-tomorrowx-s3.s3.eu-central-1.amazonaws.com/cap-agent-marketplace.yaml&stackName=cap-agent 

    1. Select your VPC and 2+ subnets in different availability zones
    2. Optionally restrict web and management access CIDRs
    3. Click "Create stack" - deploys in ~3 minutes
    4. Go to CloudFormation > Stacks > cap-agent > Outputs for your Agent URL

    Connecting Your CAP Console

    1. Open CAP Console > Administration > Agent Definitions > Create New PDA
    2. Set Host to the task public IP (from Outputs tab)
    3. Set Port to 20001
    4. Set Task ARN, Amazon ALB Target Group ARN, Amazon Access Key, and Amazon Secret Key from the Outputs tab
    5. Deploy extensions and rulesets via Console

    To Remove

    Delete the CloudFormation stack - all resources are cleaned up automatically.

    Documentation: https://docs.tomorrowx.com  Support: help@tomorrowx.dev 

    Resources

    Support

    Vendor support

    Support is delivered through partners, with TomorrowX providing platform support and specialist advisory capability where applicable. Support levels scale by license tier and are confirmed during onboarding. The customer retains control of infrastructure and networking within their AWS environment. For platform support requests, please visit

    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.

    Similar products

    Customer reviews

    Ratings and reviews

     Info
    0 ratings
    5 star
    4 star
    3 star
    2 star
    1 star
    0%
    0%
    0%
    0%
    0%
    0 reviews
    No customer reviews yet
    Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.