AI Toolkit

Out of the box, Apolo spins up a full-fledged AI/ML development environment with all the tools you need at your fingertips. If you don’t see something you want on the table, let us know, and we’ll add it to your deployment.

All the tools you need



All tools are open-source.

Unified environment

All tools are installed in the same cluster.


CV and NLP projects on Python.

Resource agnostic

Deploy on-prem, in any public or private cloud, on Apolo or our partners' resources.

Streamline Data Management

Data preparation — collection, consolidation, cleansing, and labeling — can eat up to 80% of your productive time. With Apolo, you do the experimentation while the platform handles the mundane. Connect all the necessary data sources (cloud or on-premises) and have data pipelines for automatic extraction or batch fetching in a suitable format set up for you.

When configuring your ML environment, we ensure that all incoming data gets automatically validated against the set parameters and then transferred to a centralized repository.
Benefit from access to ready-to-use feature sets for model training, re-training, and validation.

Optimize Infrastructure Management

Can’t find the right balance between underpowering and overpowering your machine-learning projects? We can help determine when, where, and how to deploy AI applications at a minimal cost for maximum gains.

Your custom-built Apolo platform provides complete visibility into models’ GPU/CPU usage across nodes and clusters, enabling you to continuously optimize job scheduling and resource allocation.

We also keep the data-hungry models at bay while ensuring that other ML pipelines get access to the right amount of storage they need at the optimal speed your networks can muster.

Deploy ML models with confidence

Unlike other proprietary AI/MLOps platforms, Apolo does not constrain how you can deploy your models. Rely on containers or serve your models as API services using the framework you prefer—Flask, Spring, or TensorFlow.js.
Do you have another approach? We accommodate that, too.

At any rate, we’d help you set up semi-automated pipelines for risk-averse model deployments and ensure that your models can be easily integrated with or within other apps. Similarly, we help you stay flexible with your choice of supporting libraries, tools, notebooks, or cloud computing resources.

We can add, upgrade, or replace any component of your MLOps platform as per your latest needs to ensure that your team has access to the exact resources they need for the upcoming project.

Apolo Ecosystem

  • Transparent budgeting & control of AI development costs

  • Resource agnosticism

  • Simple scaling

  • Interoperability with best-in-breed ML/DL tools, libraries, and SDKs

  • A unified environment with
    CLI, API, and web interfaces

  • Remote Collaboration

  • Reduction of the CO2 footprint of your AI development


Reduction in related DevOps and MLOps expenses

Your team can focus on actual AI development, leaving hardware provisioning and pipelines setup to Apolo.


Hours to Launch

Apolo GPUs and AI development toolkit will be up and running within 1 business day. Get your AI workloads ready!


Reduction in Time-to-Market

Teams using Apolo significantly reduce their AI models' time-to-market.

Footprint on lunar regolith
Footprint on lunar regolith

Contact us

Whether you have a request, a query, or want to partner with us, use the form below to get in touch with our team.

We will get back to you within 2 business days, but probably much sooner.