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Powering the
Data Economy

Spectre is an AI-powered data platform designed to manage and monitor critical production-grade data.

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Streamline data productization, drive accelerated business value.

The Spectre data platform manages your production-grade data ensuring that it is reliably sourced, seamlessly integrated with your internal systems, and monitored for good quality.  

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Data Productization

Spectre productizes batch data streams and APIs and integrates them directly into your data stack. 

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Pipeline Management

Spectre orchestrates data ingestion, cleaning, and normalization pipelines so that you don’t have to.  

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Data Monitoring

Spectre monitors all data and jobs across several dimensions and routes alerts appropriately. 

With Spectre

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Without Spectre

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Our Solution


Spectre Data Management

  • Pre-built common data and enterprise system integrations ready out-of-the-box

  • Productization of batch data streams and APIs integrated directly into your data stack

  • Registration, version control, and computational resources guaranteeing reliability at every stage


Spectre Data Quality Monitoring

  • Ongoing AI-powered data quality monitoring

  • Automatic dataset evaluation for freshness, volume, completeness, and more

  • Comprehensive root cause analysis for data quality failures


Spectre Data Pipeline Management

  • Seamlessly normalize and clean raw data

  • Easily enrich data from internal and external sources to deliver continuous insights

  • Quickly create ETL pipelines on Spectre. Automatically gain insights into your data by measuring quality, running ML inference, and extracting metadata

Manage your data with Spectre

Effortlessly manage the flow of your data by streamlining data quality management and data pipeline management into a simple, unified, autonomous solution.


Data Engineering

Our AI-powered solution can solve your data engineering needs! We help data engineering teams with:

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Data Orchestration

  • Specifying scheduled data workflows and dynamically trigger data jobs as configured 

  • Deploying new containerized versions directly from code

  • Accounting for data dependencies and data quality

Data Operations

  • Improving the observability of data flow between datasets, jobs and quality checks

  • Triaging when a process fails or an issue occurs with a dataset

  • Rerunning of portions of the data network that were paused during a period of unhealthy dataa

Data Quality Assurance

  • Monitoring of critical data to detect issues and anomalies that are hard to predict

  • Prioritizing data issues based on SLAs and data importance

  • Preventing unhealthy data from contaminating downstream systems



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Data Operations Hubs

Our data operations hub will be available for larger scale use cases involving complex data and ML scenarios with interconnected dependencies.

Connectors & Integrations

Connectors and integrations to most commonly used enterprise and data systems for simplified onboarding to the Spectre platform.

ML Data Service Suite

Our Machine Learning Data Service Suite can be run as an added layer that performs data science tasks such as anonymization, entity extraction, and annotation on data at any step of every Spectre ETL pipeline.

Contact Us

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