Cortex is the AI-powered Internal Developer Portal that helps engineering leaders at companies like Canva, Skyscanner, and Grammarly build organizations that ship reliable, secure, and efficient software, faster. By connecting data across your engineering ecosystem, Cortex uses AI to make sense of complex systems, identify what's holding your teams back, and drive action automatically. From understanding ownership and production readiness to enforcing best practices and measuring AI maturity, Cortex transforms engineering data into meaningful insights and automated workflows. The result: teams that move faster with confidence, stronger reliability at scale, and an organization fully ready for the AI-powered future of software development.
Cortex provides custom packages for every phase towards engineering excellence. Please contact AWS-Marketplace@cortex.io for a demo of Cortex, Private Offer, or additional pricing options.
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Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
This contract prices access to the Cortex Internal Developer Portal by user count. The Cortex IDP Users dimension covers 50 users on a SaaS-hosted basis, forming the core subscription you commit to for the term. The Overage Fees dimension applies when usage exceeds your committed amount, billed by user-hours. The Depreciated SKU dimension is a legacy user-based option retained for existing arrangements and is not the standard purchase path. Together, the base user allotment sets your committed capacity, while overage fees handle any usage beyond it.
Top-of-mind questions for buyers
What counts as one user for the 50 Users SaaS Hosted subscription?
A user is an individual person with access to the Cortex portal. The subscription covers 50 such users on Cortex's hosted, cloud-delivered environment. You do not manage the underlying infrastructure. Engineering leaders, platform teams, SREs, and developers each count as one user toward your allotment.
How are overage fees calculated when usage exceeds my 50-user allotment?
Overage Fees are billed by user-hours beyond your committed 50-user capacity. This meters extra usage rather than requiring you to buy a new block upfront. The base subscription sets your committed capacity, and overage charges apply on top only when actual usage crosses that amount.
What is the Depreciated SKU and should I select it?
The Depreciated SKU is a legacy user-based option retained for existing arrangements. It is not the standard purchase path for new buyers. If you are buying for the first time, the Cortex IDP Users subscription is the current user-based option. Contact the vendor if unsure which applies to you.
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Please refer to Cortex Documentation, your company Slack channel with our team, or your Sales & Customer Success points of contacts for additional support. For any additional troubleshooting please contact help@cortex.io.
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Connects data across engineering ecosystem and uses AI to analyze complex systems and identify bottlenecks
Production Readiness Assessment
Evaluates and tracks production readiness status of services and systems
Automated Workflow Execution
Drives automated actions and workflows based on insights derived from engineering data
Best Practices Enforcement
Enforces engineering best practices and standards across teams and services
AI Maturity Measurement
Measures and tracks AI maturity levels within the organization
AI Impact Measurement
Tracks adoption and utilization of AI coding assistants, measures AI-assisted pull requests, and connects productivity changes to engineering outcomes including cycle time, deployment frequency, defect rates, and delivery predictability.
Multi-Source Data Integration
Passively ingests signals from source control, issue trackers, CI/CD pipelines, cloud infrastructure, and AI coding assistants to create a unified intelligence layer for engineering leadership.
Engineering Metrics Framework
Implements DORA and SPACE metrics to establish consistent measurement strategy for benchmarking trends, tracking delivery health, and reporting engineering performance outcomes.
Intelligent Work Classification
Leverages Amazon SageMaker for automated classification of engineering work to provide visibility into work allocation, flow patterns, and effort distribution across teams.
Multi-Tenant SaaS Architecture
Delivered as a multi-tenant SaaS platform built on AWS infrastructure with integration to Amazon Bedrock for chat and agentic experiences, providing secure and scalable analytics for engineering organizations.
Software Quality Assurance
Codified checks and guidance to ensure quality, reliability, and alignment of software development practices
Access Control Management
Role-based access control mechanism to manage and control access to actions and data within the portal
Usage Analytics and Monitoring
Identification, benchmarking, and analysis of usage trends to understand adoption patterns and developer behavior
Ownership and Permission Mapping
Clear association of owners to permissions and roles to establish accountability and access governance
User-friendly data visualization has supported non-technical teams and improved customer insights
Reviewed on Jul 29, 2026
Review provided by PeerSpot
What is our primary use case?
We are partners, and I stand more like an end user. We usually give Cortex.io's data visualization tool to customers, and that's how we use it.
What is most valuable?
Cortex.io is user-friendly, and its intuitive user interface is beneficial for non-technical team members. Our customers benefit from using Cortex.io and find this product beneficial for them.
What needs improvement?
Deployment for Cortex.io is not a simple process and is somewhat complex.
For how long have I used the solution?
I have been working with Cortex.io for three years now.
How are customer service and support?
Cortex.io's technical support is helpful and responsive. I would rate this aspect a nine out of ten.
What about the implementation team?
Depending on the kind of project, two or three people usually take part in implementation.
What other advice do I have?
I am familiar with Cortex.io. From my point, we are the support team, and we do not do the deployment. The engineers do the deployment, so I cannot give you the timeframe they use in doing those deployments. I have not used it myself, so I cannot tell you what I appreciate in this solution. My team is using it, and they usually give it to customers. In case they have any issue, they call us. From my department, I cannot give answers about why customers want this because I am more on the support side. I have no idea whether customers utilize Cortex.io's custom algorithms development feature because I am not aware of that. I am not sure how Cortex.io's automated data clearing impacts data accuracy, so I cannot give you that information either. My overall review rating for this product is ten out of ten.
reviewer2807607
Centralized service catalog has improved visibility and now drives faster incident resolution
Reviewed on Mar 06, 2026
Review from a verified AWS customer
What is our primary use case?
My main use case for Cortex.io is that it provides the centralization of data from all the tools like CI/CD, monitoring, or incident management, making it a single source of truth and giving us a centralized command center for managing the health and reliability of the software services and the teams.
I use Cortex.io as a centralized command center to manage many microservices and engineering squads in a centralized way, which provides a centralized service catalog that centralizes data from all the microservices, allowing us to know who owns each service, its current health, and any documentation gaps.
What is most valuable?
The best feature Cortex.io offers is visibility, which is most relevant to the teams or services struggling with consistency and operational toil. This visibility gives us complete insight across our entire services and organization, which stands out the most for me.
The visibility feature has helped our teams by resulting in a 75% reduction in mean time to restore, allowing us to get alerts and incident history instead of relying on scattered spreadsheets and unreliable tools, thus saving around 15 to 20 hours per newly created service.
Cortex.io positively impacts our organization not only with visibility but also through its scorecards that grade each service against engineering standards, helping us check for on-call owners, passing tests, and production readiness.
The scorecards feature has changed how our teams work by providing me, as a manager, with a bird's eye view of operational maturity across teams and insight into pending incidents and responsible personnel.
What needs improvement?
I wish Cortex.io could cater to smaller teams struggling with visibility and operational toil, as a lighter version would be really great.
I believe AI adoption tracking can be enhanced and made more useful, as it currently lags behind market trends, especially in the area of security tracking for AI adoption. I think the interface and support could improve in that field.
For how long have I used the solution?
I have been using Cortex.io for the last six months.
What do I think about the stability of the solution?
Cortex.io is very stable.
What do I think about the scalability of the solution?
The scalability of Cortex.io is high.
How are customer service and support?
Customer support is very professional, and I receive complete answers within a fraction of time.
Which solution did I use previously and why did I switch?
I haven't used any other solution previously.
How was the initial setup?
I deploy Cortex.io using both public cloud and on-premise solutions.
For my public cloud deployment, I use AWS, and for my self-hosted deployment, I utilize Kubernetes plus Helm.
What about the implementation team?
I don't have complete visibility on how Cortex.io was purchased, but I believe it is through AWS Marketplace.
What was our ROI?
I have been seeing a 70 to 75% reduction in MTTR after using Cortex.io, which is the only metric I can share.
What's my experience with pricing, setup cost, and licensing?
Regarding pricing, it is fair, and the setup cost for the self-hosted version is really simple. I am on a starter deal with five product tiers that include engineering intelligence and DORA matrices. Although I have faced budget restrictions regarding engineering intelligence for renewal, initial setup costs are justified and licensing fees are broadly acceptable in the industry.
Which other solutions did I evaluate?
Before choosing Cortex.io, I evaluated Spotify Backstage, which I believe is open source, and also looked at Port.io, as these are the two options I discussed or analyzed.
What other advice do I have?
My advice to others looking into using Cortex.io is to start with a service catalog first, as scorecards are the real power feature, and it is beneficial to invest in Cortex Academy early for teams to learn how to use it effectively.
If Cortex.io gets better AI adoption tracking improvements and they provide solutions for smaller setups, that would also enhance its value.
I would rate this product an 8 out of 10 overall. I feel completely satisfied, as I do not have any other improvements needed, and have no additional thoughts about Cortex.io.
Armani Bond
Centralized metrics have improved risk visibility and now guide daily security decisions
Reviewed on Feb 24, 2026
Review from a verified AWS customer
What is our primary use case?
I have experiences in Cortex.io to centralize overall security and engineering insights and to track the overall health and risk metrics. I use it for monitoring scoreboards, metrics to measure systems' reliability, and the security posture overall. I also track the vulnerabilities and do remediation progress, provide visibility into the team performances and compliance data, and use dashboards to prioritize security and improve overall operations with my team. I drive data-based decisions to reduce risk and improve engineering efficiency.
I use Cortex.io daily to track my security and the operational health metrics for services. For example, I use it to monitor service scoreboards that measure things such as vulnerability backlogs, deployment risk, incident trends, and compliance metrics. When I saw a service with a growing vulnerability backlog, I worked with the engineering team to prioritize remediation tasks and track the progress in Cortex.io. I updated dashboards and metrics so that leadership could see improvements over time, which helped teams make data-driven decisions. It helped them reduce risk by ensuring vulnerabilities were addressed in a timely manner, and everything was fixed promptly.
Another example of how I used Cortex.io is that I used it to monitor security and compliance health across our services. I review service scoreboards and metrics that track open security findings, configuration compliance, incident response performance, and deployment risk indicators. When a service showed non-compliant configurations or any open findings, I notified the engineering teams, helped prioritize remediation, and tracked progress in Cortex.io dashboards. I provided updates so leadership could measure improvements. Overall, this ensured security issues were addressed proactively and in a timely manner, giving teams clear visibility into the risk. I check dashboards and metrics regularly as part of my daily workflow and use the data to guide security and operational improvements.
What is most valuable?
In my opinion, one of the best features of Cortex.io is the unified service catalog because Cortex.io automatically builds a centralized catalog for all your services and teams, detailing the ownerships, so you always know what exists and who owns that feature. I also love the scorecards and readiness checks; Cortex.io provides custom scoreboards that measure things such as security controls and best compliance practices, allowing teams to track health and improvements over time. I also love the progress tracking and how you can initiate and tie the scorecard goals so that work isn't just visible but actionable, allowing you to complete owners, deadlines, and also track progress that way. I appreciate the visibility and overall better reliability, as Cortex.io helps speed up onboarding, improves reliability, and frees engineers to focus on high-impact work throughout the team.
The scorecards control the readiness, security controls, and best practices, and they have helped my team make better tracking of health improvements and save a lot of time.
Cortex.io has positively impacted team collaboration because it provides clear visibility into service health, security posture, and operational metrics. Before Cortex.io, insights were scattered across tools and spreadsheets, making it harder to prioritize work and measure progress. With Cortex.io, my teams could see scoreboards and metrics all in one place, which allowed us to identify vulnerabilities and risks faster. We track remediation progress over time, make data-driven decisions more quickly, and improve collaboration through shared visibility. This enhances my team's efficiency, accountability, and helps reduce risk by addressing issues proactively and in a timely manner.
I experienced timely remediation because Cortex.io improved my team's efficiency and security visibility by centralizing service measures and risk data. Before using it, we tracked vulnerabilities and operational metrics in separate tools and spreadsheets, which made prioritization difficult. We reduced time spent searching for risk data because everything was on one dashboard, and my teams could quickly see scoreboards. We did remediation efforts to track it better and prioritize high-risk issues faster, and overall, it improved collaboration and decision-making within my security team. The operational health measures also made it more transparent.
What needs improvement?
One feature I would love to see in Cortex.io is more advanced real-time threat detection and automated alerting. I feel that this is very important, especially tailored for vulnerability severity and risk prioritization. Currently, Cortex.io provides excellent scoreboards and insights, but having real-time security alerts tied directly to risk levels, with automatic escalation and suggested remediation actions, will make the platform even more powerful in my opinion. This matters because it bridges the gap between observability and active security response, helping prioritize high-severity risks automatically, which can cut down the time spent manually correlating metrics and alerts.
One area for Cortex.io's improvement could be deeper automation and actionable recommendations. For example, the automation prioritization for vulnerabilities by risk could have more remediation actions based on historical issues, and also more security tools for real-time alerts.
For how long have I used the solution?
I have been using Cortex.io for about five years.
What other advice do I have?
Something I wish I knew before starting that could serve as good advice for others looking into using Cortex.io is to integrate it into your daily workflow. If possible, use it more than just part of your daily routine. I feel that it should be used actively as a decision-making tool and not just for visibility. The scorecards and metrics are powerful, and they are most valuable when teams actively use the insights to prioritize security and operational improvements. I advise others to regularly review scorecards and health metrics and to treat the dashboards as decision-making tools. Collaborate on remediation based on insights, track progress over time, focus on metric improvements, and maintain clear ownership and accountability, as Cortex.io works best when integrated into team processes, leading to better overall improvement. I would rate my overall experience with Cortex.io as an 8 out of 10.
Which deployment model are you using for this solution?
Hybrid Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
reviewer2801571
Cloud security has improved as detailed dashboards prioritize vulnerabilities and risks
Reviewed on Feb 07, 2026
Review from a verified AWS customer
What is our primary use case?
I use Cortex.io for cloud security to check vulnerabilities and for application security to check misalignments, misconfigurations, and open scanning of vulnerabilities in the environment, in the cloud environment. My main use case for Cortex.io is cloud security.
What is most valuable?
The best features Cortex.io offers are the dashboard, which is very detailed, and the fact that you can run different kinds of testing such as application security testing, vulnerability management testing, and cloud security testing, allowing you to see the levels and rankings of how vulnerable those situations are, including the risk factors.
Out of those features, the dashboard stands out as the most valuable to me because it contains all of the information and analytics that is required.
Cortex.io has positively impacted my organization by helping as an accelerator in fixing a bunch of different code reviews and cloud-based systems, and we also use it for client work just to ensure that everything is properly shipped.
The specific outcomes from using Cortex.io include quicker insights represented by numbers and graphs, allowing us to see the severity level, the number of open vulnerabilities, and the number of open tickets, which helps us check which one to resolve first.
What needs improvement?
For now, I cannot think of how Cortex.io can be improved. I do not have more about the needed improvements, even small things that could make my experience better.
For how long have I used the solution?
I have been using Cortex.io for about a year.
What do I think about the stability of the solution?
I would assume Cortex.io is stable.
What do I think about the scalability of the solution?
I think Cortex.io is quite scalable for multiple users depending on the task and demand.
How are customer service and support?
I haven't had to reach out to customer support, so I wouldn't know how it is.
How would you rate customer service and support?
Negative
Which solution did I use previously and why did I switch?
I did not previously use a different solution.
How was the initial setup?
I am not sure if we purchased Cortex.io through the AWS Marketplace, but it is provided by Palo Alto.
What about the implementation team?
I cannot really tell if we purchased Cortex.io through the AWS Marketplace, but it is provided by Palo Alto.
What was our ROI?
I have not seen a return on investment, so I cannot share relevant metrics.
What's my experience with pricing, setup cost, and licensing?
I am not sure about my experience with pricing, setup cost, and licensing.
Which other solutions did I evaluate?
Before choosing Cortex.io, I did not evaluate other options because I did not make the decisions; it was a business decision.
What other advice do I have?
I think Cortex.io is a good space to start.
Which deployment model are you using for this solution?
Private Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?