Telmai Data Observability
TelmaiReviews from AWS customer
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Effortless Implementation and Outstanding Support
What do you like best about the product?
The ease of implementation, the quality of customer support, and how often I use the product are all important factors for me.
What do you dislike about the product?
To be honest, there isn't really anything noteworthy in my opinion.
What problems is the product solving and how is that benefiting you?
to keep my data safe and secure
Powerful Data Observability with Real-Time Insights, Worth the Initial Setup
What do you like best about the product?
he most helpful thing about Telmai is that it provides complete, end-to-end data observability without relying on sampling. It continuously monitors data across the entire pipeline — from ingestion to consumption, detecting anomalies, drifts, and quality issues in real time. Its support for multiple data formats and open architectures makes it easy to integrate with modern data stacks, while the no/low-code interface helps both technical and business users identify and fix problems quickly. Overall, Telmai is most helpful in ensuring trust, accuracy, and reliability of enterprise data with minimal operational effort.
The main upsides of using Telmai are its strong data reliability, visibility, and ease of use. It ensures full data observability across pipelines without sampling, so every record is checked for accuracy. Telmai’s real-time anomaly detection helps catch issues early, preventing bad data from affecting analytics or AI models. It’s highly integrative, supporting diverse data formats and cloud or on-prem systems, making it flexible for complex enterprise environments. The low-code interface and automated insights save time for data engineers and make it accessible to business teams too. Overall, Telmai improves data quality, trust, and operational efficiency while reducing manual monitoring effort.
The main upsides of using Telmai are its strong data reliability, visibility, and ease of use. It ensures full data observability across pipelines without sampling, so every record is checked for accuracy. Telmai’s real-time anomaly detection helps catch issues early, preventing bad data from affecting analytics or AI models. It’s highly integrative, supporting diverse data formats and cloud or on-prem systems, making it flexible for complex enterprise environments. The low-code interface and automated insights save time for data engineers and make it accessible to business teams too. Overall, Telmai improves data quality, trust, and operational efficiency while reducing manual monitoring effort.
What do you dislike about the product?
he main downsides of Telmai are its initial learning curve and the effort needed to train and configure it effectively. Managing a large number of data assets can be a bit cumbersome, and some users feel the UI could be more intuitive for large-scale operations. Additionally, because Telmai offers full data validation and advanced monitoring, it can be costlier than simpler data-quality tools. Overall, while powerful, it requires some setup time and planning to get the most value from it.
What problems is the product solving and how is that benefiting you?
Telmai solves the problem of poor data visibility and quality across complex data pipelines. It detects issues like missing values, schema drifts, and data anomalies in real time, ensuring every record is validated instead of relying on samples. This helps catch problems early, preventing bad data from affecting analytics or AI models. For users, it brings greater trust, faster issue resolution, and reduced manual monitoring, ultimately improving data reliability and decision-making across the organization.
Telmai offers a solution for managing data streams into your data warehouse
What do you like best about the product?
Monitoring the inflow of multiple data streams into a data warehouse can be extremely labor intensive especially if you are in an industry where data standards and transfer protocols are not well-established like in our business, advertising, where partners often change content format and structure without notice. Telmai’s software offers the power of AI with an ability to learn the intricacies and nuances of our data streams, flagging changes that represent anomalies that need attention.
What do you dislike about the product?
As with any AI product there is a need to spend time and effort training the system. There is also a learning curve for the data analysts so that they fully understand the true capabilities of the software. However, these requirements are not ponderous and still represent a significant reduction in time and effort versus trying to build similar capabilities in-house.
What problems is the product solving and how is that benefiting you?
We manage over 130 different data channels representing the full activities we have engaged in with our different ad campaigns. It goes beyond ‘simple’ bookkeeping. These data represent the raw material used for ROI analyses and all other efforts to validate the impact of these campaigns. Data capture and data quality are of paramount importance. Without a tool like this, we would be looking at the need for several additional headcounts strictly purposed for data monitoring and QA.
Fast and Easy Data Observability for the Enterprise
What do you like best about the product?
The tool was quick to set up, is cloud-native, has an intuitive UI and workflow, and generates ML-based anomalies out of the box without the need for complex configurations. It is the fastest tool to onboard data for observability, while also using its own external compute to keep costs from accruing in costly warehouses. It integrates well with our data source systems and the Telmai team has been able to work within our preferred communication tools to provide real-time support and advice. The tool is running smoothly in production and I use it every day.
What do you dislike about the product?
Management of large numbers of tables can be a hassle if not properly planned. There is some room for UI enhancements that would make that management easier.
What problems is the product solving and how is that benefiting you?
Telmai allows us to implement both business and general data quality rules on out critical data assets to ensure the highest quality data products for our internal and external customers. It is easy to onboard new data assets, customize rules for existing assets, and set up meaningful anomaly detection. We are able to use Telmai to run data quality tests, data regression tests, and provide assurance to our customers that the data is of the highest quality.
Streamline Your Data Monitoring with Telmai.
What do you like best about the product?
Telmai is a platform that appears to be designed to help data teams detect and investigate anomalies in real time. Using machine learning and artificial intelligence algorithms, Telmai can help identify unusual patterns and behaviors in data that may indicate potential issues or abnormalities.
What do you dislike about the product?
Telmai is a technological platform designed for real-time data monitoring, which may come at a higher cost than other more general-purpose data monitoring tools. However, the cost can be customized as per the utilization and need
What problems is the product solving and how is that benefiting you?
Telmai helps data teams proactively address problems before they become more significant issues or threats.
It is a valuable platform for data teams looking to proactively detect and investigate anomalies in real-time, potentially improving their ability to mitigate risks and respond to potential threats more quickly and effectively.
It is a valuable platform for data teams looking to proactively detect and investigate anomalies in real-time, potentially improving their ability to mitigate risks and respond to potential threats more quickly and effectively.
Seamless Data Manager
What do you like best about the product?
It is was way easy to use at it is a no-code Saas tool to start off with. Second, it was a seamless experience all together to manage large datasets and to get the entire info within seconds.
What do you dislike about the product?
The biggest drawback is that it does not provide API. This eventually does not help with integrations with major applications and services. They will need to work around it soon.
What problems is the product solving and how is that benefiting you?
We had it for a limited time, and it helped us a little bit when it came to collecting data and viewing it all under one umbrella. The dashboard was quite intuitive.
Great tool with low code
What do you like best about the product?
1. Easy to onboard.
2. Easy integration with different systems.
3. Simple yet interactive UI.
4. Overall improvement in the data quality.
2. Easy integration with different systems.
3. Simple yet interactive UI.
4. Overall improvement in the data quality.
What do you dislike about the product?
Since launch the product has improved a lot, there were certain issues in the starting but all thanks to responsive team to get them fixed in time.
What problems is the product solving and how is that benefiting you?
Overall process of customers deliverables was simplified.
Great tool to get a quick grasp on data inconsistencies and anomalies
What do you like best about the product?
For me, the biggest highlight is a very approachable team that was super engaged with us right from the beginning to understand our needs and wants. They are very open to feedback and can quickly act upon it.
As I led the data engineering team, my job was to build a modern and efficient data platform with highly automated data pipelines. New data ingestions happened with minimal development efforts but came with a trade-off that assumed correct and consistent data. Therefore a system that could catch data inconsistencies and provide a seamless data ingestion process is valuable.
Since our first collaboration, the product has matured and evolved a lot; I am happy to see new promising features that can help any data organization.
As I led the data engineering team, my job was to build a modern and efficient data platform with highly automated data pipelines. New data ingestions happened with minimal development efforts but came with a trade-off that assumed correct and consistent data. Therefore a system that could catch data inconsistencies and provide a seamless data ingestion process is valuable.
Since our first collaboration, the product has matured and evolved a lot; I am happy to see new promising features that can help any data organization.
What do you dislike about the product?
Nothing major. The data organization of every company and industry is very complex and different, so building one solution that works for everyone is a challenging feat.
What problems is the product solving and how is that benefiting you?
Detecting exact data anomalies and inconsistencies and sharing them with the stakeholders and partners to act upon is very useful.
AI-based quality monitoring and anomaly detection for complex data
What do you like best about the product?
A broad range of data sources including semi-structured sources, can be analyzed
Their no-code anomaly detection is a game changer and it makes for a very compelling data quality tool for my team
Their no-code anomaly detection is a game changer and it makes for a very compelling data quality tool for my team
What do you dislike about the product?
Nothing major so far. I have tried the product and will be adopting it down the road.
What problems is the product solving and how is that benefiting you?
Identifying issues in large volumes of data without writing complex rules and maintaining them over time.
Great Data Quality and observability with granular details and easy to share summary!
What do you like best about the product?
Analyze and detect in a timely manner data quality issues from a deep perspective. Having a variety of views makes it easier to detect issues, prioritize which ones to tackle, and size their impact.
Data Observability with great details is critical to us as a data company, as is being able to drill down to help the investigation and pinpoint the root cause, as well as high level summaries for non-technical teams to share to show improvements in data quality.
Data Observability with great details is critical to us as a data company, as is being able to drill down to help the investigation and pinpoint the root cause, as well as high level summaries for non-technical teams to share to show improvements in data quality.
What do you dislike about the product?
Everything has been going well so far. Each request has been taken into consideration by the product team.
What problems is the product solving and how is that benefiting you?
The ability to have an overview of all the data at a glance, with segments, and to apply different rules to validate the quality at the same time, simplifies my work as a Data Quality PM. I like that ML-based engine components are available out-of-the-box to speed up the setup process. To make the detection more precise, I need and enjoy the flexibility to create and implement my own rules easily.
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