Speed up your data science journey
with Gathr

Streamline the end-to-end ML lifecycle

Integrate data quickly and easily

Enrich both batch and streaming data

Build or import models effortlessly

Train on curated, enriched datasets

Operationalize models 10x faster

Manage versions and retrain with ease

Track model performance with drift detection

Enable advanced analytics use cases

Legacy ETL failing you?

Upgrade your data engineering with next-gen data integration platform

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Drag-and-drop machine learning

Use Gathr’s self-service, visual canvas to easily build, train, and deploy complex models. Select from the platform’s 300+ built-in operators to create models faster than ever before.

Import ML models from platforms like TensorFlow and Scikit-learn. Get complete support for multiple algorithms for classification, clustering, and regression analysis.

Connect to a variety of batch and streaming data sources, perform quality checks, and identify outliers. Get instant access to massive, enriched data sets for faster model building.

Train models on curated datasets and build streaming pipelines for model scoring in real-time. Optimize model hyper-parameters to maximize performance.

Operationalize models at scale

Easily distribute your models on a Spark cluster for linear scalability. You can also use Kubernetes to scale models that you want to expose as a REST endpoint.

Apply A/B testing for monitoring model performance in the production environment. Swap the best-performing models based on real-time performance or accuracy using ‘Champion Challenger and Hot Swap’ techniques.

Once built, migrate your stand-alone data science models to an application exposed as a REST service for use across teams and use cases.

Use models trained in Gathr’s in-built notebooks to score pipelines. Sync and manage all datasets, notebooks, models, workflows, tags, and versions of your work with GIT.

Embrace MLOps across the enterprise

Enroll multiple teams into the MLOps paradigm and leverage automated and
reproducible workflows across use cases

Faster cycles for model deployment and monitoring​

Central registry to store and track data, models, and metadata​

Pre-built tools for fast-and-easy model engineering and training​

Robust model & experiment versioning for flexibility of usage

Expert Opinion

Gathr is an end-to-end, unified data platform that handles ingestion, integration/ETL (extract, transform, load), streaming analytics, and machine learning. It offers strengths in usability, data connectors, tools, and extensibilty.

Customer Speak

Gathr helped us build “in-the-moment” actionable insights from massive volumes of complex operational data to effectively solve multiple use cases and improve the customer experience.

Meet Gathr.

The only all-in-one data pipeline platform

  • One platform to do it all - ETL, ELT, ingestion, CDC, ML
  • Self Service, zero-code, drag and drop interface
  • Built-in DataOps, MLOps, and DevOps tools
  • Cloud-agnostic and interoperable
  • Data

  • Change Data

  • ETL/ELT Data

  • Streaming

  • Data

  • Machine

Why Gathr

Why Gathr


reasons to upgrade to Gathr

Up your ETL game today.

Take it for a spin or get a 1:1 personalized demo


Unified DI platform

Unified DI platform

Avoid product suite hassles with a unified platform for ETL, ELT, Reverse ETL, CDC, real-time analytics


Drag-and-drop ML

Drag-and-drop ML

Enrich data streams and enable advanced analytics with built-in drag-and-drop ML capabilities


Best-in-class real-time

Best-in-class real-time

Analyze the current moment now by integrating batch, micro-batch and streaming data




Simple, from start to end – empower tech and non-tech users to build, deploy and manage pipelines in few clicks




Break silos by enabling data engineers, data scientists & ops engineers to collaborate on a single platform


Built-in XOps

Built-in XOps

Accelerate the entire analytics lifecycle using built-in DataOps, MLOps and DevOps tools




Get production-ready output from day 1 - extensively tested for scale, security, and stability


Open and extensible

Open and extensible

Quickly adapt to changing technologies with an open and extensible architecture




Designed and built to run in any cloud environment including multi-cloud and hybrid-cloud setup


Lowest TCO

Lowest TCO

TCO less than cost of 1 skilled data engineer – choose from free/ flat/ consumption-based pricing models

Customer Stories

Powering breakthrough success

Driver profiling and risk assessment

Built an end-to-end analytics application to analyze telematics data in real-time and offer customers dynamic, usage-based insurance plans.

Pre-emptive fault detection in auto parts

Implemented a pre-emptive fault detection solution to help predict malfunction of auto parts, enable on-time maintainence, and ensure fault-free production.

Real-time insider threat detection

Used predictive analytics and machine learning to automatically detect threat scenarios and raise alerts for preventing predicted breaches across sensitive applications.

Superior omni-channel customer experience

Delivered proactive insights to help contact center representatives present customers with relevant and personalized offers across multiple channels.

Real-time business activity monitoring

Enabled 10x faster data processing and efficient, near real-time KPI tracking with an end-to-end solution for data ingestion, transformation, enrichment, and analysis.

360-degree view of the customer

Enabled micro-segmentation and targeting, dynamic marketing campaigns, proactive error resolution, and contextualized customer service in real-time.

Processed 1.5 billion events per day

Modernized legacy ETL frameworks to process over 1.5 billion user interactions per day from multiple real-time feeds and reduce the overall release cycle time.

Real-time call monitoring solution

Improved performance metrics such as call abandonment rate, average speed of answer, and average call length by monitoring call activities in real-time.

Real-time multi-lingual sentiment analysis

Enabled rapid and accurate real-time text categorization and multi-lingual sentiment analysis for massive volumes of data from diverse sources.

Call center agent monitoring solution

Reduced annual call center costs by $5M and improved agent productivity by tracking desktop activities of call center representatives in real-time.

Learning and Insights

Stay ahead of the curve

Q&A with Forrester

Building a modern data stack: What playbooks don’t tell you


4 common data integration pitfalls to avoid


Why modernizing ETL is imperative for massive scale, real-time data processing

Fireside Chat

Don’t just migrate. Modernize your legacy ETL.

Data integration just got free – forever

Choose between fully-managed SaaS or customize according to your requirements

Start your free trial Schedule a demo