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    Tray AI orchestration platform for the enterprise

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    Sold by: Tray.ai 
    Deployed on AWS
    Connect AI to your enterprise systems, data, and processes. And run it in production.
    4.5

    Overview

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    Tray.ai is an AI orchestration platform that connects AI to the enterprise systems, data, and workflows that run your business.

    Most organizations can build an AI proof of concept. The harder problem is running AI reliably across real business processes, where AI needs to reach the right data, trigger actions across systems, and operate within clear governance boundaries. Tray sits between your AI models and your enterprise operations to solve that problem.

    Companies like Zuora, Apollo.io, HackerOne, NetApp, and Cisco run Tray to build AI-powered workflows, deploy agents across their operations, and connect hundreds of enterprise systems, all on a single platform with the observability and controls that production AI requires. Access Amazon Bedrock foundation models inside Tray, with the integration infrastructure and data connectivity to make those models useful in real business environments.

    For Private Offers/Custom Scoping: Please contact aws_sales@tray.ai 

    Highlights

    • Build and deploy AI agents and AI-powered workflows connected to 700+ enterprise systems, with full control over data access and actions
    • Deploy and govern MCP servers centrally through Agent Gateway. Extend any AI model or agent with workflow-backed tools that connect to any app or data source
    • Run agents, integrations, and AI-infused automations on a single platform with unified observability, audit trails, PII tokenization, and access controls

    Details

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    Pricing

    Tray AI orchestration platform for the enterprise

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    Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    12-month contract (1)

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    Dimension
    Description
    Cost/12 months
    Tray Enterprise Edition
    Enterprise License with task consumption (includes Enterprise Support)
    $150,000.00

    Vendor refund policy

    Tray.io sells an annual subscription service that is payable in advance. Unfortunately, refunds are not available during the term. Customers can elect not to renew at the end of their subscription.

    Custom pricing options

    Request a private offer to receive a custom quote.

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    Vendor terms and conditions

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    Usage information

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    Delivery details

    Software as a Service (SaaS)

    SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.

    Support

    Vendor support

    Get help with Frequently Asked Questions and common troubleshooting topics at our support center: https://tray.ai/documentation/help/frequently-asked-questions/account-management-faqs  or contact support@tray.ai  for assistance.

    Learn to automate your apps with online learning at Tray Academy:

    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.

    Product comparison

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    Accolades

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    Top
    25
    In Data Integration
    Top
    10
    In Intelligent Automation, ML Solutions, Collaboration & Productivity

    Customer reviews

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    Sentiment is AI generated from actual customer reviews on AWS and G2
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    Overview

     Info
    AI generated from product descriptions
    AI Agent Deployment and Management
    Build and deploy AI agents and AI-powered workflows with connections to 700+ enterprise systems, including control over data access and actions.
    MCP Server Governance
    Deploy and govern Model Context Protocol servers centrally through Agent Gateway with ability to extend AI models and agents using workflow-backed tools connected to applications and data sources.
    Unified Observability and Audit
    Run agents, integrations, and AI-infused automations on a single platform with unified observability, audit trails, and access controls.
    PII Data Protection
    Implement PII tokenization capabilities for protecting sensitive personal information across orchestrated workflows and integrations.
    Foundation Model Integration
    Access and integrate Amazon Bedrock foundation models within the platform with infrastructure and data connectivity for enterprise business environments.
    AI-Enabled Digital Worker Orchestration
    Intelligent digital workers with machine-learning based orchestration to maximize efficiency and flexibility of process automations, with write-once reusable process steps and connectors.
    No-Code and Low-Code Integration
    No code or low code integration capabilities to AWS services and third-party software through Digital Exchange and AWS Marketplace for end-to-end automation lifecycle management.
    Process Emulation and Decision Automation
    Digital workers emulate human actions, decisions, and business process workflows to automate repetitive and time-intensive tasks across business operations.
    Managed Platform with High Availability
    Fully managed intelligent automation platform as a service with guaranteed 99.9% uptime SLA, including support, maintenance, platform upgrades, and site-to-site VPN connectivity.
    Pre-Configured Digital Workers with OCR and ICR
    Pre-configured digital workers leveraging optical character recognition (OCR), intelligent character recognition (ICR), and human-machine forms for automated document processing.
    Autonomous AI Agents
    Intelligent, no-code agents that connect to toolchains, understand real-time context, and take action autonomously by reasoning over alerts, tickets, logs, and configs to remediate incidents and enforce security policies.
    Native API Integration
    4,000+ native APIs including all major AWS services with full integration coverage, eliminating need for middleware or partial coverage solutions.
    Natural Language Workflow Generation
    AI-powered workflow builder that converts natural language prompts into fully configured, ready-to-run workflow blocks using semantic search and contextual suggestions without requiring API knowledge.
    Role-Based Access Control and Audit Governance
    Built-in RBAC, audit logs, approval workflows, and full execution traceability with SOC 2 Type II compliance and Bedrock-powered isolation for secure operations.
    Real-Time Collaborative Interface
    AI Rooms providing shared workspaces where teams interact with agents, review context, approve actions, and trigger flows directly from chat with human-in-the-loop governance in a single auditable interface.

    Contract

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    Standard contract
    No
    No

    Customer reviews

    Ratings and reviews

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    4.5
    162 ratings
    5 star
    4 star
    3 star
    2 star
    1 star
    73%
    23%
    3%
    0%
    1%
    3 AWS reviews
    |
    159 external reviews
    External reviews are from G2  and PeerSpot .
    reviewer2865237

    Automation has reduced manual data updates but still requires frequent troubleshooting efforts

    Reviewed on Jun 25, 2026
    Review provided by PeerSpot

    What is our primary use case?

    My main use case for Tray.io  is creating workflows to work with our Zendesk  and our other application services.

    A specific example of a workflow I have set up with Tray.io  is that we use our employee tracking system to bring that information over to Zendesk  every time an employee is hired or updated. One in particular would be signature change updates for their emails; when they make a change with HR, Tray.io provides the information over to Zendesk for our Zendesk ops team to make those changes.

    Setting up that workflow presented some challenges; Tray.io is not necessarily the easiest platform to work with. We have been using it for a while, and some were set up before I started with the company, so tweaking them can take a little bit of work. It is quite a learning curve even with their academy, but once we get it up and going, it functions fine. The biggest issue we have with Tray.io is that it runs out of memory space and does not process all of our workflows.

    If it is not just those basic things, it is primarily the system we use to communicate between all of our other systems.

    What is most valuable?

    The best features Tray.io offers include the drag-and-drop workflow builder that makes it a lot easier, and I think the automation capabilities are good. However, I feel that we would like it to be a little bit better, but we are making it work.

    Tray.io has positively impacted my organization by eliminating a lot of the manual work that we were having to do daily. It has given our team opportunities to work on different projects, and the automation that Tray.io provides saves us a lot of time and solves some of the issues that we were having prior to using it.

    I use the drag-and-drop builder across the board; we do the same process for all of our workflows that we have, so it is not one in particular that stands out. All of our workflows are pretty much the same: look at this, bring back this, bring back that, send it to here so that we can send it over to this system. We try to keep it as simple as possible.

    What needs improvement?

    To improve Tray.io, I wish that there was an easier way to download the information of our workflows to have it in some form of an Excel file that explains our workflows that we built, because we have been trying to find a way to document them to evaluate them, and we are basically having to use Miro to recreate the workflows there. It would be helpful to have a way for those who do not have access to Tray.io to look and see what it was doing and review whether or not we need to make some tweaks. Additionally, errors occur regularly when we have too large a number of employees that come over; for example, at the end of the year when our school staff is off for the summer, they technically go as inactive employees, and processing a large number of them bogs up the Tray.io system and leads to errors. We then have to go into all the Tray.io workflows to find out which piece broke and how to minimize it, so those limitations on how much data we can push overnight are frustrating.

    I would appreciate better documentation; I feel that the academy or training I took when I started with the company through Tray.io was adequate and gave us the basics, but I have not really had much experience finding support documents to help when we have problems. Although digging through the logs that Tray.io provides does help, I wish there were more in-depth help to get our systems to work easier. We kind of just bandage it together to keep it working, but it is not something that makes me say I am so glad we have Tray.io.

    I landed on that rating because we feel that it is mediocre; it does what we need it to do more often than not, but it does not impress us as it is not always reliable and hands-off. We do have to touch it quite often to make sure it keeps working, and I would love for it to be more powerful, particularly as we grow as a company, which is frustrating. Therefore, it is not something I would recommend to others as a great tool unless you are only moving small pieces of data.

    Before we wrap up, I think my additional thoughts about Tray.io mostly repeat the same points I have made previously: it is a strong workflow automation tool that works well with some of our APIs, but I just have not seen it grow and change. This could be due to the fact that we are just not using it to its greatest ability. I think that pricing-wise it is fair; I would love to see a software system be beneficial and worth the money. Right now its flexibility is beneficial since it replaced one of our other systems, so it is better than what it used to be. The complex setup of its conditions can be difficult, but the drag-and-drop feature helps. However, I think it is hard for non-technical people to learn the software, and that is the biggest challenge; you really need to know what you are doing. If you are not using it regularly, it can be difficult to come back because there is not a lot of documentation. Additionally, there is not a clear way to provide individualized documentation. The limitations on data transfer volumes at particular times are also frustrating, and without an easy debugging process, it is hard to address issues. Finding the balance between the needs of a small company and supporting larger data transfers is crucial for setting appropriate expectations regarding what the software system can do.

    For how long have I used the solution?

    I have been using Tray.io for three years.

    What do I think about the stability of the solution?

    Setting up that workflow presented some challenges; Tray.io is not necessarily the easiest platform to work with. We have been using it for a while, and some were set up before I started with the company, so tweaking them can take a little bit of work. It is quite a learning curve even with their academy, but once we get it up and going, it functions fine. The biggest issue we have with Tray.io is that it runs out of memory space and does not process all of our workflows.

    What do I think about the scalability of the solution?

    We then have to go into all the Tray.io workflows to find out which piece broke and how to minimize it, so those limitations on how much data we can push overnight are frustrating.

    What was our ROI?

    I estimate that we save over 40 hours a week thanks to Tray.io's automation, as it has even eliminated a position on our team because that person was no longer needed once we started the automations.

    What other advice do I have?

    Honestly, I am not sure that we have used anything that really shows how AI helps us with Tray.io at this point. We are still at the basic level of just doing the very basics and have not used any AI features on it to really improve it.

    My advice to others looking into using Tray.io is that when you are getting ready to start using it, make sure that you are aware of the technical capabilities of the person that will be administrating it to ensure it matches the work that needs to be done. I would also say that if there are any automated workflows that AI can provide with Tray.io, that would be great to know because we are not necessarily using that; we do it all manually.

    I provided a review rating of five for Tray.io.

    Amrit Dash

    Automated student enrollments have reduced manual work and now free our team for higher-value support

    Reviewed on Jun 04, 2026
    Review from a verified AWS customer

    What is our primary use case?

    We used and evaluated Tray.io  for approximately three to six months during a proof of concept evaluation phase. During this period, our engineering and operation teams utilized the platform to build high-volume data integration pipelines, specifically syncing student enrollment data between our student information system and the LMS  system that we have. While we ultimately decided to consolidate our day-to-day automation needs on Make  due to its lower barrier to entry and visual ease for non-developers, our time with Tray.io  gave us a solid understanding of its enterprise-grade capabilities and structure.

    Our primary use case during our evaluation of Tray.io was automated student roster management and enrollment synchronization. Specifically, we needed to ensure that when a student registers for a course on our platform, their profile gets updated, and course access to the particular subject is also done across our internal database as well as our LMS  systems. A specific example would be that we set up a workflow which would handle batch updates between our core student database that was running on Supabase in Postgres and our LMS system, which was using a version of Canvas during that time. The workflow operated as follows: when a dual trigger is queried, our database is queried at a specific time at night, maybe around 12:00 a.m. or 1:00 a.m., to fetch all the new student registrations and course changes that were done in the last 24 hours. Then, Tray.io received the data as a nested JSON payload. Using the Tray loop helper, the workflow iterated through each student record to map a field in each specific column for student ID, email, course name, and role based on the format required in the LMS API. The logic that was built handled different user roles; if a record indicated a teaching assistant, the workflow sent them specific permission in the LMS, and if it was a standard student, they would be assigned the standard access.

    The workflow sent formatted data to the LMS API so that we could create or update enrollments. If an API call failed due to any issues such as invalid email format, Tray.io's error handling branch caught the failure, isolated this specific record, and sent us a notification in our Slack channels with the error details, allowing us to manually fix it while the rest of the batch could sync without any interruption.

    What is most valuable?

    In our specific use case, several features stood out particularly strong from Tray.io. There is a robust loop and data helpers when dealing with large datasets of student data. The payload structures are rarely flat; we would have nested objects throughout. Tray.io offers highly capable helpers that allow for detailed data manipulation, making the passing of nested JSON data much simpler and easier. There is comprehensive error handling and branching for business-critical workflows such as student enrollments; an important feature is that Tray.io allows us to configure advanced error handling paths for individual steps within a workflow. We can easily set up a try-catch block to define exactly what should happen when API calls fail, and based on that, we can set up the route to alert the team via Slack, which is what we are currently doing. The connector SDK is also very nice; it has a large library of pre-built connectors that can connect a lot of proprietary internal tools directly into Tray.io, allowing the developer to build, test, and deploy custom connectors using Node.js and integrate the data directly into Tray.io.

    During our three to six-month evaluation pilot, automating our student enrollment sync with Tray.io delivered proper operational improvements. We reduced our manual data entry and verification work for the operations team by approximately 10 to 15 hours per week during peak registration periods. There were fewer system errors because the system-to-system data mismatch errors were reduced to near zero during our test runs. There were still issues where the student entered the wrong input; these cases were being tracked using error handlers. The pilot proved that automated near-real-time sync was feasible for our infrastructure, helping shape our long-term automation and data integration strategy.

    What needs improvement?

    Tray.io is definitely a highly powerful tool, but there are three main areas that I feel could be improved. There is a steep learning curve in user accessibility; the builder is highly developer-centric, making it difficult for a non-technical team member to modify or troubleshoot workflows. Introducing a more intuitive visual interface similar to what we have in make.com right now would make the platform much more collaborative and easier to work with for any non-technical folks or newly onboarded engineers, allowing them to be briefed faster.

    Visual debugging is another area where troubleshooting complex nested loops can feel very abstract. Having clearer, more visual step-by-step data tracking during test runs would speed up the development and testing process. The pricing model is geared heavily towards enterprise budgets; offering more flexible mid-market pricing tiers would make it more accessible for a growing organization that wants a small start and scale up gradually.

    The core platform security is highly robust and easily meets our requirements for SOC 2 and GDPR compliance. However, when utilizing their AI features such as Merlin AI with sensitive student data, we maintain a very cautious approach. While Tray.io provides enterprise-grade governance guardrails and data masking capabilities, our internal compliance policies prevent us from passing any personally identifiable student information directly through AI-driven processors. We trust Tray.io's underlying infrastructure security, but we believe organizations must still enforce strict data filtering protocols on their end to ensure student privacy is maintained.

    During our evaluation, we tested the AI capabilities in a sandbox environment, primarily using it to generate workflow drafts and natural language prompts from web data schemas. Strength-wise, it is highly capable when it comes to translating simple text descriptions into functional workflow templates. It serves as a great accelerator, helping to map standard files quickly and reducing the initial setup time for basic integrations. For issues, in the case of highly custom APIs or deeply nested data structures, accuracy declines. We noticed occasional misinterpretation of complex schemas, meaning our developers still had to manually review and correct the outputs. It is a highly helpful productivity booster but still requires human oversight for enterprise-grade reliability.

    For how long have I used the solution?

    I have been working in my current field for almost four and a half to five years.

    What do I think about the stability of the solution?

    Tray.io is pretty stable.

    What do I think about the scalability of the solution?

    It is quite easy to scale.

    How are customer service and support?

    We never had a chance to interact with customer support directly.

    Which solution did I use previously and why did I switch?

    We did not use a solution previously; we started using a different solution after using Tray.io.

    Which other solutions did I evaluate?

    We evaluated Integromat  and other apps as well, but Tray.io did stand out.

    What other advice do I have?

    I give Tray.io an eight out of ten rating mostly because of how it is developer-centric and lacks a low-code platform and the pricing. The reduction in manual data tasks had a direct positive impact on our team's daily focus. Instead of spending hours manually cross-referencing registration spreadsheets and troubleshooting discrepancies between our student databases and the LMS, our operation team directed their time towards high-priority student support. Specifically, during busy intake periods, they were able to focus on resolving complex student billing inquiries, improving onboarding material, and handling edge cases for registration requests much faster. The platform is definitely a value and worth considering for implementation.

    reviewer2806989

    Webhook workflows have streamlined data routing and improve daily debugging and logic building

    Reviewed on May 31, 2026
    Review from a verified AWS customer

    What is our primary use case?

    My main use case for Tray.io  is webhook functionality. We send webhooks from our application to Tray.io  and then run workflows from Tray.io to our different use cases to send data to multiple other applications.

    What is most valuable?

    The best features Tray.io offers are debugging, detailed instruction, multiple webhook configuration, workflow items, and flexibility to add logics.

    Out of those features, I find myself using logic and debug the most, and they have been the most valuable in my day-to-day work.

    Tray.io has positively impacted my organization by helping to manage webhooks easily and workflows easily, and it has improved collaboration so that other clients can use webhooks.

    What needs improvement?

    There is not much that can be improved in Tray.io. It is a good tool, but debug can be improved further and the solutions can be improved further.

    For how long have I used the solution?

    I have been using Tray.io for two years.

    What do I think about the stability of the solution?

    Tray.io is stable in my experience.

    What do I think about the scalability of the solution?

    Tray.io's scalability is very good. It can be scaled very fast.

    How are customer service and support?

    I have never had the opportunity to interact with customer support, but it should be good.

    Which solution did I use previously and why did I switch?

    I have not used a different solution before Tray.io.

    How was the initial setup?

    Tray.io is deployed in my organization on a public cloud. We use Tray.io itself, so there is no specific deployment. I did not purchase it myself. I think it was purchased directly from Tray.io.

    Which other solutions did I evaluate?

    I have not evaluated other options before choosing Tray.io.

    What other advice do I have?

    I rate Tray.io an eight out of ten overall.

    I gave Tray.io an eight out of ten because of minor improvements needed, some feasibility to manage and configure solutions, and a need for more flexibility to make it a ten.

    Regarding Tray.io's AI capabilities, I have not used them.

    I have not used Tray.io's AI capabilities regarding accuracy and reliability of output, but when I did use it, it gave me the results.

    My advice to others looking into using Tray.io is to consider it, as it is a good tool that people can use. I gave this review a rating of eight out of ten.

    Information Technology and Services

    Easy-to-Identify Logs and Audit Trails

    Reviewed on Apr 17, 2026
    Review provided by G2
    What do you like best about the product?
    To check for the logs and audits of any events that are easy to identify
    What do you dislike about the product?
    That the UI seems cluttered at times for a new user
    What problems is the product solving and how is that benefiting you?
    By being transparent about the logs and activities which in turn is very useful for debugging and fixing
    Samuele Sois

    Marketing A/B tests have gained deeper insights from user behavior and unified global reporting

    Reviewed on Mar 18, 2026
    Review provided by PeerSpot

    What is our primary use case?

    My main use case for Tray.io  is to conduct A/B testing for marketing initiatives that the company has undertaken. We test the deployment of different campaigns across similar cohorts and evaluate which one performs better.

    Tray.io  fits into my A/B testing process by analyzing the number of words used by consumers in comments and the number of times they stopped campaign videos at specific points. Through this analysis, we can investigate the attention levels of users and determine what thoughts are elicited by the campaign.

    I have found that the error management in my main use case with Tray.io is not as effective as we would prefer. We would appreciate having a way to recycle cases that do not carry much value. Every user is precious in their own way, and even if a user does not provide much information, we would still value the ability to extract some information from those boundary cases.

    What is most valuable?

    The best features Tray.io offers include excellent visualization capabilities and a dashboard, which stand out to me the most.

    I appreciate that it is very easy to convert the data we receive from Tray.io into dashboards from Power BI, which is extremely useful. I would also appreciate if in the future Tray.io provides a way to natively convert the data to Tableau.

    Tray.io has positively impacted my organization as it provides a trusted way to organize data results and share them throughout the company at once. As a multinational and very large company, it is definitely beneficial that those of us in the UK can use the same format that colleagues use in India, and the entire data architecture is framed within a trusted system from an established organization. As far as I know, Tray.io has been operating for the last 12 years, making it a very reliable system.

    What needs improvement?

    I believe Tray.io can be improved by offering integration with Tableau, which is still not available.

    I rated it an eight because there are still some things that can be improved, as I mentioned before.

    For how long have I used the solution?

    I started using Tray.io approximately one year ago.

    What do I think about the stability of the solution?

    In my experience, Tray.io is stable, as we have never experienced issues with it failing or being unavailable. We did not experience any downtime, compatibility issues, or system issues at all.

    What do I think about the scalability of the solution?

    The scalability of Tray.io is quite good. We were able to deploy it from a small company within Tata with 200 people to what is now a multinational company with 92,000 people globally, and the people involved in using Tray.io number in the hundreds. I believe the scalability is quite good.

    How are customer service and support?

    I have never used the customer support for Tray.io because the software is very easy to use and we never needed to contact support. However, I can tell you that the support provided through newsletters and update bulletins is quite good.

    Which solution did I use previously and why did I switch?

    Previously, we attempted to develop an in-house solution as a company proprietary system, but we failed to achieve a good standard and quality level with that approach. We therefore looked for an established solution.

    What was our ROI?

    I have seen a return on investment as the company has been renewing the product for the entire 19 months we have been using it, which indicates that trust is high and they likely see value and advantage in using the system. There are no complaints in this regard.

    What's my experience with pricing, setup cost, and licensing?

    My experience with pricing, setup cost, and licensing for Tray.io is that I did not personally follow the pricing negotiation, but I understand that the company pays a monthly fee which is very competitive. No one has complained in the finance department, and it is very rare for Tata Motors to refrain from complaining about pricing.

    Which other solutions did I evaluate?

    A few options were evaluated before choosing Tray.io, but I cannot recall which ones were proposed to me because Tray.io was identified as the most valid option since the very beginning.

    What other advice do I have?

    My advice to others considering Tray.io is to trust the process because once the installation is complete, it is extremely easy to deploy and set up.

    I have rated this product an eight out of ten.

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