Multi-tenant • Your cloud • No data migration

Focus on your strategy, not
the infrastructure behind it

Access your data from scattered sources, build models, run massive backtests, and deploy signals directly inside your own cloud.

No data movement - just faster research, deployment, and enterprise-grade control.

    • Multi-tenant • Your cloud • No data migration

    Focus on your strategy, not
    the infrastructure behind it

    Access your data from scattered sources, build models, run massive backtests, and deploy signals directly inside your own cloud.

    No data movement - just faster research, deployment, and enterprise-grade control.

    • Multi-tenant • Your cloud • No data migration

    Focus on your strategy, not
    the infrastructure behind it

    Access your data from scattered sources, build models, run massive backtests, and deploy signals directly inside your own cloud.

    No data movement - just faster research, deployment, and enterprise-grade control.

    • Why hedge funds choose Datatailr

    Why hedge funds choose Datatailr

    Go live fast

    Go live fast

    Deployment and testing usually take several days. One case study onboarded in under a month

    Elastic at market speed

    Elastic at market speed

    Burst to thousands of VMs. Run about 50K jobs with around 10 seconds start spread and scale to about 100K jobs in roughly 10 minutes

    Self service for quants and analysts

    Self service for quants and analysts

    One click deploy, SDLC, and an Excel add in that exposes Python as native functions

    Predictable TCO

    Predictable TCO

    License based platform. Compute is billed by your cloud with no platform markup

    Built for your team

    One platform based
    on 4 pillars

    Datatailr unifies the building blocks of modern analytics in a secure BYOC platform

    Datatailr unifies the building blocks of modern analytics in a secure BYOC platform

    Portfolio Manager

    Portfolio Manager

    Launch new strategies quickly while keeping costs governable and auditable

    Launch new strategies quickly while keeping costs governable and auditable

    Head of Quant Research

    Head of Quant Research

    Research, test, and deploy in one governed workspace with fewer handoffs

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

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

    CTO / Head of IT

    CTO / Head of IT

    SSO with optional MFA, RBAC, approvals from Dev to Pre to Prod, audit trails, and outbound egress control

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

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

    Quants & Analysts

    Quants & Analysts

    Focus on research and alpha, not infrastructure. Connect data, code in familiar tools like Jupyter/VS Code, backtest and analyse results in Excel – without developer queues.

    Unified SQL that queries Snowflake, S3, Postgres and 40+ more databases where the data already lives. No migration.

    Focus on research and alpha, not infrastructure. Connect data, code in familiar tools like Jupyter/VS Code, backtest and analyse results in Excel – without developer queues.

    What you can ship

    What you can ship

    Real time signals for energy and commodities desks at massive scale, including about 50K parallel jobs and bursts to roughly 2,000 VMs

    Periodic batch jobs run by quants themselves, reducing reliance on infra core engineering

    Excel driven analytics backed by governed services and caching

    Security
    and Compliance

    Security
    and Compliance

    Runs in your cloud in a single tenant deployment. SSO with optional MFA. Granular RBAC. Encryption in transit. IP allowlists and outbound firewall. Full audit logs.

    Runs in your cloud in a single tenant deployment. SSO with optional MFA. Granular RBAC. Encryption in transit. IP allowlists and outbound firewall. Full audit logs.

    Proof from Real Funds

    Use cases
    and outcomes

    Energy trading

    Energy trading

    about 50K jobs in parallel

    first to last job start around 10 seconds

    burst to roughly 2,000 VMs

    about 100K jobs in around 10 minutes

    Data provider and commodities

    Data provider and commodities

    100 to 200 batch jobs per day

    onboarding in under a month

    a proper SDLC

    Challenges and what solves them

    Use cases
    and outcomes

    Challenge

    Research and market data live across Snowflake, S3, Postgres, and external feeds

    New strategies wait on infrastructure tickets and cluster work

    Intraday bursts around opens, closes, and news exceed web style autoscaling

    Backtests and live runs must be reproducible for investors and auditors

    Finance needs cost per run, per signal, and per strategy

    Risk grows when data leaves the fund cloud

    Use

    No migration

    Federated SQL in your cloud with role based access and masking

    Result

    Query in place under one policy layer with no centralization project

    Challenge

    Research and market data live across Snowflake, S3, Postgres, and external feeds

    Use

    No migration

    Federated SQL in your cloud with role based access and masking

    Result

    Query in place under one policy layer with no centralization project

    New strategies wait on infrastructure tickets and cluster work

    Intraday bursts around opens, closes, and news exceed web style autoscaling

    Backtests and live runs must be reproducible for investors and auditors

    Finance needs cost per run, per signal, and per strategy

    Risk grows when data leaves the fund cloud

    See how this maps to your stack

    See how this maps to your stack