Understand our key product differentiation
Make an informed choice of tool based on your use case and needs.
NO sampling, NO blind spots
Data quality monitoring often requires users to detect issues, identify their impact across the entire data set, and exclude the impacted data from model inputs or review/remediate it before consumption.
Our low-cost, no-sampling approach ensures that users will have full control over automation around the impact and action after a data quality issue or anomaly is detected.
No cloud cost surge
While Data metrics like schema change, volume drift, lineage, and freshness can be detected using table meta-data, data quality metrics like validity and accuracy require processing data and comparing it against thresholds(user-defined or ML-driven). These operations are often compute-intensive and can increase the overall cloud cost.
Telmai is natively designed as a metric calculation system, i.e., we do not send excessive queries to the underlying analytical system like your data warehouse. Instead, our highly optimized spark-based engine can process billions of records with hundreds of attributes at extremely low cost.
Open architecture-connect to any data source
Most enterprise data is semi-structured and stored in difficult-to-use formats like JSON, XML, and CSV, not tables. Modern data architectures are moving towards decoupled storage engines, where AI models will directly query the raw data stored in open formats like Iceberg, Hudi, and Delta using the query engine of their choice.
Telmai enables you to design a data quality strategy for this open ecosystem. Our platform is natively designed to connect and process structured and semi-structured data stored in raw formats like JSON, XML, and CSV. No data cleanup, pre-processing, or transformation required.
Secured, zero-copy data
With Telmai, you never have to worry about moving data. Our control plane will manage Telmai within your secured Virtual Private Cloud (VPC), and we will process data where it’s stored, i.e., in Data lakes, Data lakehouses, or CDW
Additionally, our decoupled spark-based engine is designed for elastic processing at a low cost, so all the metric calculations will be done in the spark engine without incurring excessive queries on your underlying analytical systems like Snowflake, Redshift, or BigQuery.
For example, the Telmai engine can process every data value within billions of records with nested JSONs of 100 attributes within hours without sampling at a fraction of the cost. Also, you can monitor the exact cost of Telmai queries; our clients never have to worry about cloud costs.
Data observability leader
“Great Data Quality & Observability with granular details and easy to share summary”
“Accelerated our data validations and anomaly detection work-flow using Telmai”
“Telmai offers a top-tier SaaS-based data observability platform with no/low-code development”
“AI-based data quality monitoring and anomaly detection for complex data”
Data Quality
Ensure every decision is based on reliable data
Anomaly Detection
Find anomalies in column-values and aggregated business metrics
Cross-System Consistency
Data consistency across every system and source
Data Health Analysis
Discover powerful new health insights. No code required
Complete Pipeline Observability
Secure monitoring across entire pipeline without performance impact
Incident Management
Take action before data issues impact your business
See what’s possible with Telmai
Request a demo to see the full power of Telmai’s data observability tool for yourself