Poolside
Open-weight coding models for secure enterprise software engineering.
If your enterprise needs secure, long-context code reasoning with full audit trails and is willing to invest in a high-touch partnership, Poolside is unmatched. The 256K context and open-weight models are powerful, but the cost and engagement model exclude smaller teams. For self-serve alternatives, consider GitHub Copilot or Cursor.
Verified 17d ago · liveness 93/100 · cite: rightaichoice.com/tools/poolside
- Large enterprises in regulated industries needing on-prem or air-gapped AI coding
- Teams requiring executive governance, audit trails, and role-based access
- Organizations embedding AI for complex, long-horizon software engineering
- CISOs and compliance officers in defense, finance, and healthcare
- Startups or small teams wanting a low-cost, self-service coding assistant
- Individual developers seeking a free or lightweight AI tool
- Projects with simple, repetitive coding tasks that don't need deep reasoning
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Skip Poolside if you need a self-serve, low-cost AI coding assistant for personal projects or small teams.
On-prem deployment may require dedicated hardware and IT setup, adding infrastructure costs.
Poolside's pricing is contact-only and tailored for large enterprises, making it expensive compared to self-serve tools like GitHub Copilot ($19/mo) or Cursor ($20/mo). The high-touch model suits organizations with six-figure budgets for AI transformation but excludes cost-sensitive buyers.
In short
Poolside — Open-weight coding models for secure enterprise software engineering. Best for Large enterprises in regulated industries needing on-prem or air-gapped AI coding, Teams requiring executive governance, audit trails, and role-based access, Organizations embedding AI for complex, long-horizon software engineering. Contact Sales pricing.
What's new in Poolside
Checked 6 days agoAcross the latest 5 updates: 1 feature update, 3 launches and 1 news mention.
Introducing Laguna XS 2.1
Poolside releases Laguna XS 2.1, an upgraded version of Laguna XS.2 model.
Long context update: Laguna XS.2 and M.1
Laguna XS.2 and M.1 models now served at 256K context lengths.
Through the looking glass of benchmark hacking
Poolside outlines reward hacks encountered and strategies to resolve them.
AI, your way: introducing the Poolside Platform
Production-grade AI agents deployed inside security boundary with full auditability and governance.
Laguna XS.2 and M.1: A Deeper Dive
Poolside releases first two Laguna models and runtime for agents in research preview.
Viability Score
How likely is Poolside to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Laguna XS 2.1: 33B params, 3B active, runs on-device
- Laguna M.1: 225B params, 23B active, API access
- 256K context length on both models
- Multi-agent orchestration with planning and tool use
- Sandboxed execution environments for agents
- Executive governance with RBAC and audit trails
- On-prem, VPC, or air-gapped deployment
- C2C activation offloading on Grace Blackwell (6-13% throughput gain)
- Forward Deployed Research Engineers embedded with customer teams
- Custom evaluations co-created with customers
About Poolside
Poolside builds open-weight foundation models and agentic systems tailored for long-horizon software engineering in regulated industries like defense, finance, and healthcare. Its latest Laguna XS 2.1 model (33B params, 3B active) runs on-device, while Laguna M.1 (225B params, 23B active) is available via API—both now support 256K context lengths for processing large codebases per query. The Poolside Platform orchestrates single and multi-agent workflows with planning, tool use, and sandboxed execution, all within a governance framework featuring RBAC and end-to-end audit trails. Deployable on-prem, in VPC, or on air-gapped networks, Poolside pairs its technology with Forward Deployed Research Engineers to drive adoption and measurable outcomes. Unlike generic AI coding assistants, Poolside takes joint responsibility for results and offers deep integrations with code repositories, databases, and data warehouses, making it a strong choice for security-conscious enterprises.
Behind the Verdict
Poolside is built for the few enterprises that require airtight security, long-horizon reasoning, and executive governance—things most coding assistants ignore. The Laguna XS 2.1 and M.1 models, with 256K context, let agents reason across enormous codebases in one pass, and the Poolside Platform adds sandboxed execution with RBAC that auditors love. We'd reach for this when the code is complex, the stakes are high (defense, finance, healthcare), and your organization can afford a high-touch partnership with Forward Deployed Engineers embedded in your team. Where it bites: the upfront cost and engagement model are prohibitive for startups or individual devs. For simple tasks or low-budget teams, GitHub Copilot or Cursor are cheaper, self-serve alternatives. In practice, the reward hacking blog post shows Poolside is actively improving reliability, but early adopters should expect some rough edges. This is not a tool you plug in and forget—it's a multi-month commitment that pays off for mission-critical code.
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Real-world workflow fit
Concrete scenarios for the personas Poolside actually fits — and what changes day-one when you adopt it.
You need to refactor legacy C++ code while maintaining strict security and audit trails.
Outcome: Poolside multi-agent system runs inside your VPC, plans the refactor across modules, sandboxes execution, and produces a full trace for compliance review.
You must ensure all AI-generated code changes are auditable and meet regulatory standards.
Outcome: Poolside Platform's executive governance features capture every agent action with RBAC and end-to-end traces, satisfying audit requirements.
You want to evaluate custom models on your proprietary codebase before committing to a deployment.
Outcome: Poolside's Forward Deployed Research Engineers co-create custom evaluations and benchmarks, tailoring models to your specific codebase.
Use Cases
- Deploy secure AI agents inside your VPC for autonomous code review and refactoring.
- Orchestrate multiple AI agents to plan and execute complex software migrations across legacy systems.
- Embed Forward Deployed Research Engineers to co-build custom agent workflows within your development pipeline.
- Maintain full audit trails and governance over AI-assisted code changes in regulated industries.
- Automate end-to-end testing and deployment pipelines using multi-agent orchestration.
- Run evaluation benchmarks collaboratively with Poolside to tailor models to your specific codebase.
- Process entire enterprise codebases in a single query using 256K context windows.
Models Under the Hood
as of 2026-07-14
Limitations
- Poolside's models and products are currently in research preview, so availability and feature completeness are limited.
- The platform requires close collaboration with Poolside's Forward Deployed Research Engineers, which may not suit teams wanting a self-serve tool.
- No public pricing is available, and on-premise deployment may entail significant infrastructure requirements.
- The focus on enterprise and government customers means individual developers and small teams are not the target audience.
as of 2026-07-02
Where the pricing makes sense
The company stage and team size where Poolside's pricing actually pencils out — and where peers do it cheaper.
Poolside's pricing is contact-only and tailored for large enterprises, making it expensive compared to self-serve tools like GitHub Copilot ($19/mo) or Cursor ($20/mo). The high-touch model suits organizations with six-figure budgets for AI transformation but excludes cost-sensitive buyers.
Setup time & first value
How long it actually takes to get something useful out of Poolside — broken out by persona, not the marketing-page minute.
Initial setup takes 1-2 weeks for on-prem deployment including model installation, sandbox configuration, and connector setup. The Forward Deployed Engineers then spend 1-2 months embedding with your team to co-build workflows and achieve measurable impact.
Switching to or from Poolside
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From GitHub Copilot: Poolside offers on-prem governance and longer context for complex migrations not possible with a cloud-only assistant.
- →From Cursor: Teams needing air-gapped deployment and audit trails can transition to Poolside's platform, with custom connector integration.
- ↗To GitHub Copilot: If you find Poolside's high-touch model too expensive, Copilot provides a simpler, lower-cost alternative for basic code completion.
- ↗To Cursor: Cursor offers a more self-serve experience for individual developers and small teams while still providing AI-powered code assistance.
Integrations
Resources & Guides
- Resourcepoolside.ai
The latest stories from Poolside
Thoughts from the team building the foundation models and platform redefining how software gets made—securely, intelligently, and at scale.
- Resourcepoolside.ai
Upcoming events Poolside is attending
Meet our team and learn how to power your organization with foundational AI.
Official links
Tools that pair well with Poolside
Common stack mates teams adopt alongside Poolside, with the specific reason each pairing earns its keep.
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Frequently Asked Questions
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