Capy suits engineering teams of three or more that want to hand whole workstreams to AI rather than pair with a single assistant. Born in Y Combinator's Fall 2024 batch, it replaces the one-agent loop with delegated branches that come back as reviewable pull requests, so the team's job shifts from typing code to reviewing it.
Capy is a cloud coding platform from Scrapybara that launched its browser-based IDE on April 2, 2026. Every task passes through three dedicated agents: a planner that turns the request into a spec, builders that write and test the code, and a reviewer that critiques the diff before a human merges it.
Maker: Scrapybara · Autonomy: semi autonomous · Maturity: GA
Underlying models: Claude Opus 4.6, Claude Sonnet 4.6, GPT-5.2, GPT-5.2 Codex, Gemini 3 Pro, Grok 4.1 Fast, Kimi K2.5, Qwen 3 Coder
About Capy
Capy is the flagship product of Scrapybara, Inc., a San Francisco startup founded in 2024 by Nalin Semwal and Justin Sun, who met while building AI agents at MultiOn. The company went through Y Combinator's Fall 2024 batch, raised a $500K seed round from YC, BoxGroup, and CRV, and shipped its cloud IDE in spring 2026. The pitch is delegation over pair programming: instead of sitting with one assistant, an engineer files jobs and reviews the pull requests that come back. Isolation is the core design choice, with every job confined to its own disposable virtual machine and branch so parallel work never collides. Model choice is open, letting teams route each job to whichever large language model fits, and human sign-off on every merge is the safety backstop.
Pricing
Pro is $20/mo ($16/mo billed annually) and includes 3 seats, with extra seats at $10/mo each. Usage-credit packs add bonus credit: $100 for $105, $500 for $550, and $2,000 for roughly $2,300. Enterprise pricing is custom and includes bring-your-own API keys, custom VM sizing, and SSO/SAML.
Key Features
- Captain planning agent: A read-only agent reads the codebase and turns a request into a refined spec broken into tickets before any code is written.
- Parallel Build agents: Up to 25 Build agents can run concurrently, each in its own sandboxed Ubuntu VM and git branch, editing files and running commands.
- Automated Review agent: A dedicated Review agent checks each diff and leaves feedback before a human approves the pull request for merge.
- Model-agnostic task routing: Teams can assign a task to Claude, GPT, Gemini, Grok, Kimi, or Qwen depending on the job, instead of being locked to one model vendor.
- SOC 2 Type II certified sandboxing: Every task runs in an isolated VM under a SOC 2 Type II program with zero-data-retention agreements with model providers.
Strengths
- Parallel delegation is the differentiator reviewers cite most against single-agent coding tools.
- Security terms (certification plus zero-retention agreements with the big model providers) hold up in enterprise review.
- The pipeline covers planning through review, automating more of the pull-request cycle than autocomplete assistants.
Weaknesses
- Cloud-only with no CLI or terminal mode, unlike competitors that offer a local workflow.
- Independent reviewers estimate parallel agent fleets burn roughly 7x the tokens of a single session, so the entry tier can run dry before a big workload finishes.
- No published SWE-bench, GAIA, or other standard benchmark scores, which makes raw coding quality hard to compare against benchmarked rivals.
Frequently Asked Questions
How much does Capy cost in 2026?
Capy Pro runs $20 per month, or $16 on annual billing, covering 3 seats with extras at $10 each. Heavier usage comes from credit packs whose bonus grows with pack size, and credits drain fast when many agents run at once since overage bills 1:1. There is no free tier; Enterprise adds custom VM sizing, SSO, and the option to bring your own API keys.
Is Capy fully autonomous?
No, it is semi-autonomous by design. Build agents write code, install dependencies, run commands, and fix failing CI on their own, but every diff waits for review. A human approves each pull request before it merges, so nothing ships untouched.
What are the best alternatives to Capy?
Cursor fits a single developer who wants AI in a familiar editor rather than a team platform. Devin suits teams willing to pay a premium for a benchmarked, end-to-end autonomous engineer. Windsurf lands in between, keeping a local IDE feel while adding agentic features.
How does Capy compare to Devin in 2026?
Devin publishes benchmark results and leans into full autonomy; Capy keeps a human approval gate and has released no benchmark numbers as of mid-2026. Capy's counterargument is throughput and model freedom rather than raw autonomy. Pick Devin for hands-off delegation with documented performance, Capy for many reviewable branches at once.
How do you get started with Capy?
Sign up at capy.ai and connect GitHub so Capy can reach the repositories you choose. Describe a task; the planning agent reads the code and produces a spec and tickets before any build work begins. Your first deliverable arrives as a pull request with review feedback already attached.
Top Alternatives
- Cursor: Pick Cursor if you want a single-developer editor experience; pick Capy when a team needs several delegated branches at once.
- Devin: Pick Devin if you need a documented, benchmarked autonomous engineer; pick Capy for parallel throughput across a team.
- Windsurf: Pick Windsurf for an integrated local editor experience; pick Capy if your team wants a cloud-native multi-agent pipeline.