Poolside vs Magic

Detailed side-by-side comparison to help you choose the right tool

Poolside

🔴Developer

AI 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

Custom

Magic

🔴Developer

AI Coding Assistants

Frontier AI lab building ultra-long-context coding models aimed at automating software engineering at scale.

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Starting Price

Custom

Feature Comparison

Scroll horizontally to compare details.

FeaturePoolsideMagic
CategoryAI Coding AssistantsAI Coding Assistants
Pricing Plans83 tiers6 tiers
Starting Price
Key Features
  • Software-engineering focused foundation-model company rather than a lightweight autocomplete plug-in
  • Enterprise positioning for private, secure, and regulated development workflows
  • Targets teams that need coding assistance with stronger control over data, deployment, and governance

    💡 Our Take

    Choose Poolside if you want a productized enterprise platform today with IDE surfaces, agents, connectors, and on-prem deployment backed by $626M in funding and a Forward Deployed Engineer delivery model. Choose Magic if you're specifically interested in long-context frontier research for software engineering and are comfortable with an earlier-stage, research-forward partner rather than a deployment-ready platform.

    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

    Magic - Pros & Cons

    Pros

    • Genuinely novel technical bet on ultra-long context
    • Tier-1 investor list signals serious capital runway
    • If LTM thesis pays off, leapfrogs RAG-based coding agents
    • Focused enterprise design-partner approach avoids consumer noise

    Cons

    • No public API or product — unbuyable for most teams today
    • Pricing, latency, and accuracy unverified outside private trials
    • Long-context claims need independent benchmark validation
    • Vendor risk: research-stage companies pivot or stall

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