Datatailr for Quants:

Add a decorator. Run at scale in your own cloud.

From Jupyter to Production in days, not weeks.

Focus on your models, let Datatailr handle the rest.

    • Datatailr for Quants:

    Add a decorator. Run at scale in your own cloud.

    From Jupyter to Production in days, not weeks.

    Focus on your models, let Datatailr handle the rest.

    • Why Quants Choose Datatailr

    Why Quants Choose Datatailr

    Write Once, Run Anywhere:

    Write Once, Run Anywhere:

    Use a simple Python decorator to turn local code into a scalable cloud workflow.

    Use a simple Python decorator to turn local code into a scalable cloud workflow.

    one decorator · any scale

    Zero-Migration Data Access:

    Zero-Migration Data Access:

    Connect to your data (Snowflake, S3, SQL) and run backtests in the matter of minutes

    Connect to your data (Snowflake, S3, SQL) and run backtests in the matter of minutes

    API access

    Elastic Scale:

    Elastic Scale:

    Burst to 1,500 VMs for running intensive jobs and return to baseline automatically.

    Burst to 1,500 VMs for running intensive jobs and return to baseline automatically.

    burst to zero

    Full Reproducibility:

    Full Reproducibility:

    Every run is fully logged, versioned, and reproducible, with built-in rollback and audit capabilities.

    Every run is fully logged, versioned, and reproducible, with built-in rollback and audit capabilities.

    versioned · auditable · rollback

    Challenges and How Datatailr Solves Them

    Challenges and How Datatailr Solves Them

    Instant Research

    Reproducible Runs

    Unified Access

    Actionable Insights

    The Challenge

    Waiting weeks for IT/DevOps to provision compute or deploy code at scale

    Capability

    On-demand access to pre-configured Python environments and data

    Result

    Immediate experimentation with the latest frameworks and packages

    Instant Research

    Reproducible Runs

    Unified Access

    Actionable Insights

    The Challenge

    Waiting weeks for IT/DevOps to provision compute or deploy code at scale

    Capability

    On-demand access to pre-configured Python environments and data

    Result

    Immediate experimentation with the latest frameworks and packages

    Faster Research

    Reproducible Runs

    Unified Access

    Actionable Insights

    The Challenge

    Waiting weeks for IT/DevOps to provision compute or deploy code at scale

    Capability

    On-demand access to pre-configured Python environments and data

    Result

    Immediate experimentation with the latest frameworks and packages

    From Idea to Live Signals

    From Idea to Live Signals

    1


    Instant onboarding

    Login to a pre-loaded workspace with your packages and data permissions.

    Login to a pre-loaded workspace with your packages and data permissions.

    2


    Research & backtesting 

    Write code and run massive parallel simulations on pre-warmed instances.

    Write code and run massive parallel simulations on pre-warmed instances.

    3


    Secure promotion

    Move your model to Pre and Prod with built-in approvals and expose signals directly via Dashboards, Services or Excel Add-ins.

    Move your model to Pre and Prod with built-in approvals and expose signals directly via Dashboards, Services or Excel Add-ins.

    Measurable outcomes

    Measurable outcomes

    100% Research Focus:

    100% Research Focus:

    No more waiting on infrastructure or managing cloud clusters.

    No more waiting on infrastructure or managing cloud clusters.

    Standardized Workflows:

    Standardized Workflows:

    Every piece of code is versioned, logged, and reproducible by default.

    Python and Jupyter for research. Deploy apps and services in minutes.

    Every piece of code is versioned, logged, and reproducible by default.

    Zero Hurdles:

    Zero Hurdles:

    Move from research to production-grade services rapidly.

    Code or no-code DAGs with built-in versioning and one-click rollback.
    No YAML.

    Move from research to production-grade services rapidly.

    Scalable Output:

    Scalable Output:

    Run more workloads with zero manual infrastructure oversight.

    Python and Jupyter for research. Deploy apps and services in minutes.

    Run more workloads with zero manual infrastructure oversight.

    What You Ship on Datatailr

    What You Ship on Datatailr

    Scalable Backtests:

    Scalable Backtests:

    High-throughput simulations spanning thousands of cores.

    High-throughput simulations spanning thousands of cores.

    Live Dashboards:

    Live Dashboards:

    Interactive dashboards for Portfolio Managers. Native support for streamlit, panel, voila, bokeh and many more frameworks.

    Interactive dashboards for Portfolio Managers. Native support for streamlit, panel, voila, bokeh and many more frameworks.

    Governed Excel Add-in:

    Governed Excel Add-in:

    Your models stay in Python. Your PMs stay in Excel. We handle everything in between.

    Your models stay in Python. Your PMs stay in Excel. We handle everything in between.

    Air-Gapped AI:

    Air-Gapped AI:

    Secure LLMs for code refactoring and signal generation inside your secure cloud account.

    Secure LLMs for code refactoring and signal generation inside your secure cloud account.