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    Edge Delta AI Teammates

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    Sold by: Edge Delta 
    Deployed on AWS
    Edge Delta AI Teammates are your agentic observability team that never sleeps. They continuously analyze your production data in real time, automate root cause analysis, and cut through the noise to surface the issues that matter.
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    Overview

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    Edge Delta's AI Teammates are the only agentic observability team built on top of an enterprise-grade observability stack, enabling continuous analysis of real-time production data from all your tools, environments, and data sources. These out-of-the-box AI agents automate root cause analysis, surface actionable signals from noise, and help teams significantly reduce MTTR while focusing on the creative work that fuels innovation.

    To facilitate Private Offers, contact sales@edgedelta.com .

    Highlights

    • AI Teammates learn what "normal" looks like across your services, automatically filtering out transient issues and low-value alerts so your team spends less time on manual triage and more time on work that actually matters.
    • AI Teammates automatically correlate incidents with code merges, config changes, and related telemetry data to pinpoint the most likely cause, so your team gets straight to answers with full context already in hand.
    • Intelligent Telemetry Pipelines and fine-grained RBAC controls keep your data secure and compliant, while seamless integrations with your existing tools mean your team can get value from AI Teammates in minutes, without introducing risk or starting from scratch.

    Details

    Delivery method

    Deployed on AWS
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    Pricing

    Edge Delta AI Teammates

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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 (7)

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    Dimension
    Description
    Cost/12 months
    Ent - ED - Telemetry Pipelines (Edge) 5TB - 12 Months - $146,000
    Edge Delta Telemetry Pipelines (Edge). Process/forward observability and security data to any downstream destination using Edge Fleets. 5000 GB of raw data ingest daily. 12 month term. Annual discounted cost of $146,000
    $10,950.00
    250 GB/day
    Ingest up to 250 GB of raw data per day
    $27,375.00
    500 GB/day
    Ingest up to 500 GB of raw data per day
    $54,750.00
    1 TB/day
    Ingest up to 1 TB of raw data per day
    $109,500.00
    1GB/Day
    For organizations that need control and flexibility over growing volumes of telemetry data.
    $36.50
    100 GB/day
    Up to 100 GB per day raw data ingest
    $3,650.00
    36.5 TB for 12 Months
    Customer has 12 months to send 36.5 TB of raw data ingest into Edge Delta Pipelines
    $3,650.00

    Vendor refund policy

    Refunds are not available

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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

    Contact for further information info@edgedelta.com 

    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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    Updated weekly

    Accolades

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    Top
    50
    In Security Observability, Monitoring and Observability
    Top
    10
    In Generative AI, Log Analysis
    Top
    10
    In Migration, Monitoring, Continuous Integration and Continuous Delivery

    Customer reviews

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    Sentiment is AI generated from actual customer reviews on AWS and G2
    Reviews
    Functionality
    Ease of use
    Customer service
    Cost effectiveness
    7 reviews
    Insufficient data
    Insufficient data
    Positive reviews
    Mixed reviews
    Negative reviews

    Overview

     Info
    AI generated from product descriptions
    Real-time Production Data Analysis
    Continuous analysis of real-time production data from all tools, environments, and data sources using agentic observability capabilities
    Automated Root Cause Analysis
    Automatic correlation of incidents with code merges, config changes, and related telemetry data to identify the most likely cause with full context
    Anomaly Detection and Alert Filtering
    Learning of normal behavior patterns across services with automatic filtering of transient issues and low-value alerts to reduce manual triage
    Intelligent Telemetry Pipelines
    Enterprise-grade observability stack with intelligent telemetry pipeline architecture for secure data processing and compliance
    Fine-grained Access Control
    Role-based access control (RBAC) mechanisms for granular data security and compliance management
    AI-Powered Root Cause Analysis
    Automatically investigates alerts and pinpoints root causes with 5x faster analysis capabilities.
    Natural Language Query Interface
    Enables querying of observability data using conversational natural language to identify issues and receive actionable insights.
    Real-Time Anomaly Detection
    Detects system anomalies in real-time to prevent incidents before they impact users.
    OpenTelemetry Integration
    Supports standardized OpenTelemetry integration for unified data collection across logs, metrics, and traces in cloud-native environments including Kubernetes, serverless, and microservices.
    Multi-Tiered Storage Architecture
    Implements multi-tiered storage and data management capabilities to optimize telemetry costs and achieve 30% to 50% cost savings.
    Telemetry Data Platform
    Ingests, analyzes, and alerts on metrics, events, logs, and traces in a unified platform
    Full-Stack Observability
    Visualizes and troubleshoots entire software stack in one connected experience with integrated AWS service monitoring
    Anomaly Detection and Issue Correlation
    Automatically detects anomalies, correlates issues, and reduces alert noise through applied intelligence
    Agentless SAP Monitoring
    Provides agentless monitoring for ABAP systems with support for SAP RISE, ECC, S/4HANA, BTP, CALM, Fiori, Ariba, PI/PO, BW and 175+ monitoring points
    AWS Service Integration
    Deep integration with AWS technology stack including Amazon EKS, AWS Lambda, AWS Kinesis, Amazon CloudWatch, and AWS Distro for OpenTelemetry

    Security credentials

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    Validated by AWS Marketplace
    FedRAMP
    GDPR
    HIPAA
    ISO/IEC 27001
    PCI DSS
    SOC 2 Type 2
    No security profile
    -
    -
    No security profile

    Contract

     Info
    Standard contract
    No
    No
    No

    Customer reviews

    Ratings and reviews

     Info
    4.4
    8 ratings
    5 star
    4 star
    3 star
    2 star
    1 star
    38%
    62%
    0%
    0%
    0%
    0 AWS reviews
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    8 external reviews
    External reviews are from G2  and PeerSpot .
    KajalSharma

    Centralized observability has accelerated incident resolution and currently improves release monitoring

    Reviewed on Jun 05, 2026
    Review provided by PeerSpot

    What is our primary use case?

    My primary use case for Edge Delta  has been observability, log monitoring, and troubleshooting application issues. I rely on it to analyze bugs, investigate incidents, monitor system behavior after releases, and help ensure overall platform reliability. Edge Delta  serves as my main tool for log monitoring, analyzing logs, investigating issues, and gaining better visibility into application and system performance.

    One specific example of how I used Edge Delta for log monitoring was during a production release where we needed to verify that a new back-end feature was behaving as expected after deployment. We used Edge Delta to monitor application logs in real-time and track error patterns, API failures, and unusual spikes in warnings. Shortly after deployment, we noticed an increase in validation errors coming from a particular service. By filtering and analyzing the logs, we quickly identified the root cause and worked with the development team to resolve it before it affected a large number of users. The biggest benefit was reducing the time spent manually searching through logs and helping the team identify issues much faster during critical release windows.

    I used Edge Delta not only during incidents but also for routine monitoring, release validation, and investigating performance trends. Having centralized visibility into logs and telemetry data helped us be more proactive in identifying potential issues before they became larger problems.

    What is most valuable?

    In my experience, the best features of Edge Delta are real-time processing, powerful filtering and search capabilities, observability across multiple data sources, and efficient telemetry data management. The feature I found most valuable was real-time log analysis, which allowed me to identify issues quickly without waiting for long logs to be processed through multiple systems. I also appreciated the filtering and querying capabilities because they made it easier to isolate specific errors, services, or time periods during troubleshooting. That significantly reduced the time needed to investigate incidents. Overall, these capabilities helped improve operational awareness and accelerated issue resolution across teams.

    Edge Delta has positively impacted my organization by improving operational visibility and reducing the time required to investigate issues. Before adopting a centralized observability solution, troubleshooting often involved gathering logs from multiple sources and manually correlating information. With Edge Delta, teams have a more unified view of system activity, which makes it easier to identify and diagnose problems. We also noticed faster incident responses and smoother post-release monitoring. Engineers could detect unusual patterns, errors, or performance issues earlier, which helped reduce the time between identifying a problem and resolving it. The biggest improvements were faster troubleshooting, better operational awareness, and more proactive monitoring of application health.

    What needs improvement?

    Overall, Edge Delta is a strong observability platform, but there are a few areas where it could be improved. One area is dashboard and reporting customization. The platform provides useful operational insights, but having more flexibility to create highly tailored views for different teams would be beneficial. Another area is onboarding and usability. Observability  platforms can be complex, especially for new users, so additional guided workflows, recommendations, and learning resources could help teams become productive more quickly.

    Deeper integration visibility would be useful as well. Many organizations use multiple monitoring, logging, and incident management tools, so having even better cross-platform correlation and troubleshooting workflows would add value. On the pricing side, observability platforms can become expensive as data volume grows. More granular cost optimization insights and usage visibility would help organizations better understand how data consumption impacts cost and where optimizations can be made. The platform is strong in its core capabilities. The improvements I would prioritize would be deeper ecosystem integrations, enhanced cost visibility, and more intelligent automation to help teams act on observability data more efficiently.

    For how long have I used the solution?

    I have been using Edge Delta for one year.

    What do I think about the stability of the solution?

    Overall, I find Edge Delta to be a stable platform. In day-to-day usage, we have not experienced significant reliability issues, so the stability is one of the strengths of the platform, and I feel comfortable relying on it for production monitoring and troubleshooting activities.

    What do I think about the scalability of the solution?

    Scalability is one of the areas where Edge Delta performed well. I find the platform capable of supporting growth in both data volume and system complexity, which is important for organizations with expanding applications and infrastructure.

    How are customer service and support?

    I have not personally interacted with the customer support team, but from what I have heard from my team and other teams, they have a significantly nice customer support system. The people answering the queries are really intelligent, and they have provided responses in a very reasonable time. Overall, I would rate the customer support around eight out of ten because the team is helpful, technically competent, and responsive.

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

    Before Edge Delta, we primarily relied on a combination of traditional log management and monitoring tools along with some in-house dashboards. While those tools provided visibility, it often required jumping between multiple systems to gather logs, correlate events, and investigate incidents. That made troubleshooting time-consuming, especially during production issues or release validation. We evaluated Edge Delta because we sought more efficient log processing. The main reason for adopting Edge Delta was to improve visibility, reduce investigation time, and simplify how teams worked with large volumes of telemetry and log data.

    How was the initial setup?

    My experience with pricing and licensing has been generally positive, although I am more involved in the implementation and day-to-day usage than in procurement decisions. From an implementation perspective, the setup effort is fairly reasonable. Most of the work involves configuring data sources, integrations, log collection pipelines, and dashboards rather than deploying infrastructure. Because Edge Delta is a managed SaaS platform, there are minimal infrastructure-related setup costs on our side, which help speed up adoption. In terms of licensing, my understanding is that costs are influenced by factors such as data volume and usage. Overall, I find the setup process straightforward, and the licensing model feels aligned with the capabilities and operational benefits the platform delivers.

    What was our ROI?

    The biggest benefit has been the reduction in troubleshooting and incident investigation time. Based on our experience, root-cause analysis has become roughly thirty to forty percent faster, allowing engineers to spend less time searching through logs and more time resolving issues. From a quality and reliability perspective, earlier detection of issues has helped reduce the risk of prolonged production incidents, which provides value even if it is not always measured in direct financial terms. While I do not have exact dollar figures, the ROI is evident through time savings, improved operational efficiency, and better visibility into system health.

    Which other solutions did I evaluate?

    We looked at a few other observability and log management tools such as Datadog , Splunk, and Elastic Observability . Each of those products has its own strengths, but what stood out about Edge Delta was its approach to processing and analyzing telemetry data efficiently and helping reduce operational overhead.

    What other advice do I have?

    My advice would be to start by clearly defining your observability goals before implementation. Understanding what you want to monitor, whether it is application performance, log analytics, incident response, or operational visibility, will help you get the most value from the platform. I suggest starting with a focused use case and expanding gradually. Once teams become comfortable with the workflows and dashboards, it is much easier to scale observability practices across additional services and environments. I would rate this review an eight overall.

    Computer Software

    Good Experience

    Reviewed on Apr 17, 2024
    Review provided by G2
    What do you like best about the product?
    It is a complete to for data analysis and log reviewing. It's possible to create triggers and a dashboard that can ease the daily tasks.
    As on investigating with customer support tickets, it helps on properly see the information on a good speed.
    What do you dislike about the product?
    It is impossible to format the rendering of data in a more clustered manner to help a quick overview of data.
    What problems is the product solving and how is that benefiting you?
    Quickly looking into data and logs
    Mateus S.

    Good experience

    Reviewed on Apr 06, 2024
    Review provided by G2
    What do you like best about the product?
    Ease of Use when searching for logs. Also the support by the edge team looking into the requests from my team.
    What do you dislike about the product?
    The fact that the logs weren't almost real time
    What problems is the product solving and how is that benefiting you?
    Looking into logs at day by day. It was a complete tool at all
    Luana A.

    It was a good experience

    Reviewed on Mar 05, 2024
    Review provided by G2
    What do you like best about the product?
    We can retrieve data from a long date range, and it is great for maintenance and incident tracks.
    What do you dislike about the product?
    The interface of the product is not very user friendly.
    What problems is the product solving and how is that benefiting you?
    It helps us to be more aware and better keep track of our application performance.
    Amit M.

    Early adopter, not achieving the full benefits from the solution

    Reviewed on Jan 28, 2024
    Review provided by G2
    What do you like best about the product?
    Cost savings is the main benefit that I see
    What do you dislike about the product?
    The team does not grok it and they do not systematically integrate it into their workflows
    What problems is the product solving and how is that benefiting you?
    Log analysis in an efficient way
    View all reviews