The data observability tool for the entire modern data stack

Monitor your data pipelines within minutes, without a single line of code

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No code setup. Simple, fast and secure.

A no-code on-boarding. Connect to your data source and specify alerting channels

Telmai will automatically learn from data and alert you when there are unexpected drifts

Get alerted on data metrics drift

Get alerted on unexpected drifts on data metrics like row counts, schema changes, completeness of column values, outliers in values and unexpected drifts in distribution of values.

Faster investigation

Once alerted, quickly analyze Data and Metadata to identify the root cause of issues.Our investigator UI will provide visual hints on value distributions, pattern masks, and anomaly scores on aspects like length, frequency, tokens to find the root cause of issues in minutes.

Data migration quality metrics
The data observability platform with customized alerting policies

Customize alerting policies

Fine-tune our alerting to include your business needs. Users can set expectations on data like controlled list values, expected data types, and patterns.Get automatically alerted when these policies get violated.

How it works

Create Account

Sign-up for trial and get an account within minutes.

Connect Datasource

Connect to your datasource, or send data via REST, or load a local file.

Alert

Telmai will learn your data and its trends and automatically alert on unexpected drifts.

Telmai Offers

70%

Faster detection
and resolution

10X

Reduction on TCO

< 1 Hour

Time to value

50%

Drop in alert noise

CUSTOMER TESTIMONIALS

“During the pilot with Telmai, we were impressed with the no-code, low-code and visual interface that provided the right insights on our data overtime. Moreover, we had excellent consulting support and fast turnaround times for the features that were requested. This helped us with the decision to go ahead and finalize Telmai as our centralized data observability solution.”

Shaji Thomas

VP of Cloud and Data Engineering, Merkle

"When dealing with data sets comprising millions of records, Telmai quickly becomes an incredibly useful tool, saving a lot of time and ultimately increasing data quality."

Maria Grineva

SVP Engineering, Dun & Bradstreet

“To prepare data for product usage analysis we needed data quality metrics beyond monitoring operational data pipelines and job status checks. While we continue to monitor the quality of the pipeline, we chose Telmai to detect the quality of the data that moves through the pipeline.”

Raghu Nadiger

Data & Analytics Leader, DataStax

“We chose Telmai because of its flexibility and architecture. Telmai will remain our data observability platform as our data landscape changes. Telmai has lots of adapters in place to quickly integrate with various data sources across cloud providers. In addition, it supports real time API integration for automated decisions in complex workflows.” 

Kishore Damodara

AVP of Cloud and Data Engineering, Merkle

"Data anomaly investigations that used to take hours now take minutes and gives us more time to focus on the business needs."

Darius Kemeklis

EVP, Myers-Holum

“Our customers deserve the best possible data to make their business grow. Telmai's Data Observability enables us to show the quality of the data that we are delivering to our customers. With Telmai we are able to build data quality KPIs that reflect our data's freshness, completeness, and accuracy to keep and extend the trust that our customers have put in us.”

Harlow Ward

CTO, Clearbit


“In searching for a data quality and observability solution, we looked at a few solutions. They were limited to tracking just the data volumes, row counts, completeness, and uniqueness. That was not enough for us. We needed to look inside each attribute and each record to see if our data is drifting or its patterns are changing. Telmai was the only solution that empowered us to do so.”

Alejandra Cabrera

Data Product Manager, Clearbit


Get started on your data observability

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Telmai is a platform for the Data Teams to proactively detect and investigate anomalies in real-time.
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