Poolside

Developer Tools , Productivity , Content Creation

Poolside is an enterprise-focused AI platform for software development that offers custom model training and on-premise deployment for enhanced security and privacy.

Best for enterprises prioritizing security and customizability in AI coding tools, weaker for individual developers or those needing immediate, out-of-the-box solutions.

Ai Ai Coding Assistant Code Generation Code Completion Llm Developer Tools Automation

Analysis based on product data, pricing structure, traffic signals, and public user sentiment.

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Who Should Use Poolside?

Typical users

Large enterprises, particularly those in regulated industries like finance, defense, and technology, that require strict data security and privacy. Development teams looking to fine-tune AI models on their proprietary codebases.

Maturity fit

scaling to advanced

Choose this if…

You need to deploy AI models within your own security boundary.
You require models fine-tuned on your specific codebase and development practices.
Your organization handles sensitive data and demands strict privacy controls.
You are looking for an AI partner with a strong focus on the future of AGI.

Skip this if…

You are an individual developer looking for a free or low-cost AI coding assistant.
Your organization does not have stringent security or privacy requirements.
You need a tool with a vast array of pre-built integrations with non-enterprise tools.
You prefer a cloud-based, fully managed AI solution without on-premise considerations.

About Poolside

Poolside is a generative AI platform built specifically for software development, aiming to create the most capable AI for coding tasks. It offers proprietary models and a full-stack solution, emphasizing on-premise deployment and custom model training for enterprises. The company's long-term vision includes contributing to Artificial General Intelligence (AGI).

What it actually does

Poolside provides an AI assistant for IDEs that can generate code, complete code in real-time, assist with testing and documentation, and be fine-tuned on an organization's specific codebase. It aims to automate and enhance various aspects of the software development lifecycle.

What makes it different

Poolside differentiates itself by focusing exclusively on software development with proprietary models like Malibu and Point, trained using Reinforcement Learning from Code Execution Feedback (RLCEF). Its core differentiator is the ability to deploy entirely within an enterprise's security boundary, offering on-premise solutions and full model weight ownership, which is crucial for highly regulated industries.

Proprietary LLMs for software development On-premise and within-boundary deployment Custom model fine-tuning on enterprise codebases Real-time code completion Code generation AI-assisted testing and documentation IDE integration Data security and privacy focus

Key Features

Malibu and Point LLMs

Purpose-built foundation models for software engineering, offering multi-step reasoning and autonomous task execution.

On-Premise Deployment

Allows AI to run entirely within an organization's security boundary, ensuring data never leaves their infrastructure.

Custom Model Fine-Tuning

Enables organizations to tailor AI models using their own codebases and documentation for proprietary, continuously learning AI.

Reinforcement Learning from Code Execution Feedback (RLCEF)

A proprietary training methodology that improves model performance by learning from code execution, not just code data.

Poolside Assistant

An AI pair programmer integrated into IDEs for writing, editing, and reviewing code, with context awareness.

Security and Compliance

Designed for environments where cloud-only platforms cannot go, with options for air-gapped and disconnected deployments.

Full Model Weight Ownership

Enterprises receive full model weights, not just API access, providing control and permanent asset ownership.

AWS Partnership

Availability on Amazon Bedrock and EC2 for secure deployment and cost-efficient inferencing.

Pricing

Popular

Contact Sales

Custom

Pricing is not publicly listed and is likely custom-based on usage and enterprise needs.
On-premise deployment options.
Custom model fine-tuning.
Full model weight ownership.
Dedicated support and engineering resources.

Pricing checked 6 months ago

Pricing guidance

Best plan for most users: Poolside's pricing is custom and enterprise-focused, meaning there isn't a single 'best' plan. The optimal solution will depend on the specific needs, scale, and security requirements of a large enterprise.

Free plan enough? No, Poolside does not offer a free plan. Its services are targeted at enterprises with custom pricing structures.

Upgrade when:

Need for advanced features like custom model fine-tuning.
Increased usage requiring scaled infrastructure.
Requirement for dedicated enterprise support and deployment services.
Expansion of AI usage across more development teams or projects.

Watch out for:

Custom pricing can lead to unpredictable costs if not managed carefully.
On-premise deployment requires significant internal infrastructure and IT expertise.
Integration capabilities may be limited to enterprise-specific tools and platforms.

Premium, enterprise-focused positioning with custom pricing tailored to large organizations' security and customization needs.

Pros & Cons

Strengths

Enterprise-grade security and privacy
Poolside's ability to deploy entirely within an organization's security boundary is a significant advantage for enterprises with strict data governance and privacy requirements.
Customizable AI models
The option to fine-tune models on proprietary codebases allows for highly tailored AI assistants that understand an organization's specific development practices and libraries.
Domain-specific models
Focusing exclusively on software development with proprietary LLMs (Malibu and Point) trained with specialized techniques like RLCEF aims for superior performance in coding tasks compared to general-purpose models.
On-premise control and ownership
Providing full model weights and on-premise deployment gives enterprises complete control over their AI assets, reducing vendor dependency and ensuring data sovereignty.

Weaknesses

Limited public pricing and accessibility
Pricing is not publicly listed and appears to be custom, suggesting a higher cost and less accessibility for smaller businesses or individual developers.

Affects: Smaller businesses and individual developers
Enterprise-centric focus
The product is heavily geared towards large enterprises, which may mean a steeper learning curve or less immediate value for smaller teams or individual developers.

Affects: Individual developers and small teams
Newer market entrant
As a relatively new company, its long-term track record and the maturity of its enterprise-level support and integrations are still being established.

Affects: Risk-averse enterprises
Potential complexity of on-premise deployment
While a strength for security, managing on-premise AI infrastructure can be complex and require significant internal IT resources.

Affects: Organizations lacking dedicated IT/ML Ops teams

Real User Sentiment

User sentiment is not yet widely available due to its enterprise focus and recent market entry. Early indicators suggest positive reception for its security and customization features among target clients.

Users tend to like

Strong security and privacy features for enterprise deployment.
Ability to fine-tune models on proprietary codebases.
Focus on specialized AI for software development.
Potential for AGI development.

Users commonly complain about

Limited public information on pricing and features.
Steep learning curve for non-enterprise users.
On-premise deployment complexity.

Recurring tradeoffs

High security and customization come with higher cost and complexity.
Enterprise focus means less accessibility for individual developers.

Happiest users

Large enterprises in highly regulated industries that prioritize data security and require tailored AI solutions.

Often frustrated

Individual developers or small businesses seeking readily available, cost-effective AI coding tools.

Use Cases

Enterprise-level code generation and completion for large projects

Developing secure AI models for sensitive government or defense applications

Fine-tuning AI for specific company codebases and development standards

Automating testing and documentation processes within an enterprise

Building custom AI-powered developer tools for internal use

Exploring advanced AI capabilities towards Artificial General Intelligence (AGI)

Frequently Asked Questions

What is Poolside and what does it do?

Poolside is an AI platform focused on software development. It offers proprietary large language models (LLMs) like Malibu and Point, trained with advanced techniques, to provide AI assistance for code generation, completion, testing, and documentation. Its key differentiator is its ability to deploy entirely within an enterprise's security boundary, prioritizing security and privacy for businesses, especially in regulated industries. The company also has a long-term vision of contributing to Artificial General Intelligence (AGI).

Who are Poolside's main competitors?

Poolside competes in the AI coding assistant market. Its primary competitors include well-established tools like GitHub Copilot, as well as other AI coding assistants such as Tabnine, Codeium, and Amazon Q Developer. Larger AI companies like OpenAI and Anthropic are also indirectly competitors in the broader AI development space.

What are the security features of Poolside?

Poolside emphasizes security and privacy by allowing its AI stack to be deployed entirely within an enterprise's own infrastructure. This means that no data or code ever leaves the customer's security boundary. They offer options for air-gapped and disconnected deployments, making it suitable for highly regulated industries like defense, finance, and government. The company also provides full model weights, giving customers complete control over their AI assets.

How does Poolside's pricing work?

Poolside's pricing is not publicly disclosed and is offered on a custom, pay-per-use basis, often described as a 'scale-out' model. This means pricing is tailored to the specific usage and needs of enterprise clients, with potential discounts for increased usage. Interested parties need to contact Poolside directly for a quote, as there is no standard pricing tier available.

Can individual developers or small teams use Poolside?

Poolside is primarily designed for large enterprises with a strong emphasis on security, customization, and on-premise deployment. While its advanced capabilities could theoretically benefit individual developers or small teams, the custom pricing, enterprise-centric focus, and deployment model make it less accessible and potentially cost-prohibitive for this segment. The company's go-to-market strategy is heavily focused on enterprise clients.

What makes Poolside's AI models different from general-purpose LLMs?

Poolside's models, Malibu and Point, are purpose-built foundation models specifically trained for software engineering tasks. They utilize proprietary techniques like Reinforcement Learning from Code Execution Feedback (RLCEF) to achieve a deeper understanding of code. Unlike general-purpose LLMs that include code as one of many data types, Poolside's AI is exclusively oriented towards software development, aiming for superior accuracy and reasoning in coding contexts. This specialized approach allows for more effective code generation, completion, and complex problem-solving within the software development lifecycle.

Why trust this page?

This evaluation combines product positioning, pricing analysis, traffic and market signals, and public user sentiment into a single decision-support page. Content is generated editorially — not copied from the vendor's website.

Funding & Company

Founded

2023

Stage

Series b

Total Raised

$626M

Latest Round

Series B (Oct 2024)

Notable Investors

Bain Capital Ventures Nvidia DST Global Felicis Redpoint Ventures Xavier Niel

Poolside has raised a total of $626 million, with a significant $500 million Series B round in late 2024. This substantial funding from major investors like Bain Capital Ventures and Nvidia indicates strong market confidence and provides a long operational runway.

Full funding report high confidence

Market Signals & Traffic

Estimated visits, global rank, geography, traffic sources, monthly visit trends, and organic search keywords (Similarweb)—on a dedicated page built for depth and search.

Estimated visits: 50,339
Global rank: #565,359
Snapshot: Apr 2026
Traffic trend: Surging