Code-Cube.io
Code-Cube.io is a comprehensive marketing observability solution that ensures the accuracy and reliability of tracking data across digital platforms. It continuously monitors tags, dataLayers, and conversion events to detect issues the moment they occur. By providing real-time alerts, the platform allows teams to quickly respond to tracking failures before they affect campaign performance or reporting accuracy. Its automated auditing capabilities remove the need for time-consuming manual QA processes, saving valuable resources. With features like Tag Monitor, users can oversee tag behavior across both client-side and server-side environments with full transparency. DataLayer Guard further strengthens data integrity by validating events, parameters, and values in real time. The platform helps businesses avoid wasted ad spend caused by incorrect or incomplete data signals. It also supports multi-domain tracking, ensuring consistency across complex digital ecosystems. Code-Cube.io is trusted by global brands to maintain high-quality marketing data at scale. Ultimately, it enables organizations to optimize performance and make confident, data-driven decisions.
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NeuBird
NeuBird AI is an agentic AI platform built for IT and SRE teams who are done fighting fires manually. It watches your entire stack around the clock and when something goes wrong, it does more than surface an alert. It investigates by pulling from your logs, metrics, traces, and incident tickets, and figures out what actually broke and why, and tells the team exactly what to do next or simply takes care of it.
Neubird connects to the tools your team already relies on including Datadog, Splunk, PagerDuty, ServiceNow, AWS CloudWatch, and more. It reasons across all of them the way a senior engineer would, at any hour, without the 2 AM wake-up call. Incidents that once took hours now close in minutes, with MTTR reduced by up to 90%.
Neubird AI runs continuously, deploys as SaaS or inside your own VPC, and fits within your existing security controls. No rip and replace. Just faster resolution, less noise, and more time back for the work that actually matters - The on-call coverage your team deserves, without the 2 AM wake-up calls
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Edge Delta
Edge Delta is a new way to do observability. We are the only provider that processes your data as it's created and gives DevOps, platform engineers and SRE teams the freedom to route it anywhere. As a result, customers can make observability costs predictable, surface the most useful insights, and shape your data however they need.
Our primary differentiator is our distributed architecture. We are the only observability provider that pushes data processing upstream to the infrastructure level, enabling users to process their logs and metrics as soon as they’re created at the source. Data processing includes:
* Shaping, enriching, and filtering data
* Creating log analytics
* Distilling metrics libraries into the most useful data
* Detecting anomalies and triggering alerts
We combine our distributed approach with a column-oriented backend to help users store and analyze massive data volumes without impacting performance or cost.
By using Edge Delta, customers can reduce observability costs without sacrificing visibility. Additionally, they can surface insights and trigger alerts before data leaves their environment.
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Resurface
Resurface is a runtime API security tool. Resurface continuous API scanning allows you to detect and respond in real time to API threats and risks. Resurface is a purpose-built tool for API data. It captures all request and response payloads, including GraphQL, to instantly see potential threats and failures. Receive alerts about data breaches for zero-day detection.
Resurface is mapped to OWASP Top10 and alerts on threats with complete security patterns. Resurface is self-hosted and all data is first-party.
Resurface is the only API security system that can be used to perform deep inspections at scale. Resurface detects active attacks and alerts them by processing millions of API calls. Machine learning models detect anomalies and identify low-and slow attack patterns.
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