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Enterprise Layer Intelligence
Categories/Data Platform & Integration/Telm.ai
Telm.ai

Telm.ai

Founded by Unknown in 2023

Monitor data pipelines and detect anomalies across data lakes continuously

Pricing model

Paid

Rating

★ People love it

Time to value

Quick Setup (< 1 hour)

You can use Telmai to monitor data quality and track unexpected anomalies across your data pipelines and data lakes. It automatically scans structured, semi-structured, and unstructured data as it arrives, creating detailed quality signals before bad data impacts downstream applications. The system uses automated agents to diagnose incidents, map data lineage, and explain root causes in plain language. You can also configure validation rules with natural language prompts, trace pipeline dependencies across multi-cloud environments, and ensure reliable data for machine learning models and business reporting.

What Telm.ai does

Set up automated anomaly detection monitors on raw data feedsMap complete data lineage across sources and destinationsInvestigate pipeline incidents with automated root cause diagnosisGenerate visual summaries and reports on data consistencyValidate unstructured and semi-structured datasets as they land in storageCreate custom data validation rules using plain-language instructionsExport data quality metadata to external catalogs and systemsContinuously scans structured, semi-structured, and unstructured data upon arrivalIdentifies anomalies and pinpoints root causes across pipeline dependenciesMaps data flows to trace upstream sources and downstream impactGenerates plain-English summaries and visual charts for quality trendsSuggests validation rules automatically based on historical data patternsEnables natural language queries to investigate data quality issuesProvides quality metadata directly accessible via Model Context Protocol

Pricing breakdown

Pricing model: Paid

Frequently asked

Apache Iceberg, Microsoft OneLake, Azure Data Lake Storage, AWS S3, Google Cloud Storage, Databricks, Snowflake, Apache Spark

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Telmai, data quality monitoring, data observability, anomaly detection, data reliability, data pipeline monitoring, data lakehouse, lineage tracking, root cause analysis, incident diagnosis, autonomous data validation, data health analysis, open architecture