Poolside vs Devin
Detailed side-by-side comparison to help you choose the right tool
Poolside
🔴DeveloperAI Coding Assistants
Foundation-model company building enterprise-grade AI software engineers trained on private code with on-prem deployment.
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Starting Price
CustomDevin
🔴DeveloperAI Coding
Devin is an autonomous AI software engineer by Cognition that plans, executes, and reports on complex engineering tasks without constant human input.
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Starting Price
$500/moFeature Comparison
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💡 Our Take
Choose Poolside if you need a custom foundation model and multi-agent platform deployed inside your own VPC or on-prem, with Forward Deployed Research Engineers co-owning outcomes in regulated or air-gapped environments. Choose Devin if you want a hosted autonomous engineering agent with public pricing that a team can start using in days rather than running a multi-month enterprise deployment.
Poolside - Pros & Cons
Pros
- ✓Best-in-class data residency story — model can run fully inside your VPC or air-gapped environment
- ✓Custom training on private code produces depth no public copilot can match
- ✓Founding team (ex-GitHub) has credibility with enterprise procurement and security teams
- ✓Includes evals and observability so you can prove ROI to a CIO, not just guess
Cons
- ✗Enterprise-only — no self-serve tier and no way to try it without a long sales cycle
- ✗You take on a heavy GPU footprint and the operational burden of running foundation models in-house
- ✗Product surface and exact naming are still shifting — flagged for manual verification
- ✗For most companies, GitHub Copilot Enterprise or Cursor delivers 90% of the value at a fraction of the cost
Devin - Pros & Cons
Pros
- ✓Genuinely autonomous — handles multi-step tasks without constant prompting
- ✓Parallel agents allow multiple tasks to run simultaneously
- ✓Documented enterprise case studies with real efficiency numbers (12x at Nubank)
- ✓Core plan entry price dropped from $500 to $20 in 2026, much more accessible
- ✓Works inside existing GitHub/Slack/CI workflows
- ✓Can tackle migrations and test generation at scale that would be prohibitively manual
Cons
- ✗ACU costs add up fast on longer tasks — real monthly spend can reach $300-500
- ✗Struggles with ambiguous or architecture-level tasks that require deep context
- ✗Output still needs human review before merging PRs
- ✗Not an in-editor experience — separate from Cursor, VS Code workflows
- ✗Requires clear task specifications to produce good output
- ✗Enterprise features (VPC, SSO) only available at custom pricing tiers
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