
Laguna by Poolside offers foundation models optimized for complex software agent workflows.

Laguna focuses on creating capable AI systems that handle extended reasoning and tool use for software engineering tasks. These models are designed to integrate across development tools while maintaining strict boundaries around sensitive information. Enterprises benefit from forward-deployed support that aligns AI capabilities with existing workflows and compliance needs. This approach allows organizations to adopt agentic technologies without disrupting established security protocols or infrastructure. The underlying vision connects advanced model training to broader goals of achieving general intelligence through practical software applications. By prioritizing high-stakes environments, Laguna contributes to systems that can scale toward more autonomous operations over time.
Single and multi-agent systems that plan, use tools, and execute tasks in sandboxed environments governed by policies and end-to-end traces.
Foundation models deployed inside enterprise security boundaries on-prem, in VPCs, or on workstations with role-based access control and no data leaving customer control.
Agents, TUI, IDE extensions, binaries, and workflows that connect to repositories, databases, and private corpora to support engineering work across heterogeneous environments.
Pricing model: Paid. Plan details are indicative — check the site for current prices.
Our take: Laguna by Poolside is a solid coding & dev choice. It's valued for inside security boundary deployment with no data leaving control and joint outcome ownership with forward-deployed engineers. The main trade-off is public pricing and plans pages unavailable. Best when you need reliable, professional output.
Laguna refers to Poolside's foundation models such as Laguna XS.2 and M.1 designed for long-horizon work starting with software agents.
Laguna by Poolside is a solid coding & dev choice. It's valued for inside security boundary deployment with no data leaving control and joint outcome ownership with forward-deployed engineers. The main trade-off is public pricing and plans pages unavailable. Best when you need reliable, professional output.
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