All-Hands
Generative AI software
AI coding assistants software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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$500 per month
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What is All-Hands
All-Hands is an AI-assisted software development tool positioned as a coding assistant for writing, modifying, and reviewing code. It targets developers and engineering teams that want help with routine implementation tasks, code understanding, and iteration inside a development workflow. The product centers on using generative AI to propose code changes and respond to developer prompts, with an emphasis on practical coding support rather than general-purpose content creation.
Developer-focused AI assistance
The product is oriented around software engineering tasks such as generating code, explaining code, and helping iterate on changes. This focus can make it more relevant for day-to-day development work than general-purpose generative AI tools. It aligns to common developer workflows where quick suggestions and refactors reduce manual effort.
Supports iterative code changes
All-Hands is designed for back-and-forth prompting to refine implementations, which fits how developers typically work through requirements and edge cases. Iteration helps users converge on acceptable solutions faster than one-shot generation. This is especially useful for boilerplate, small features, and incremental refactoring.
Useful for code comprehension
AI-driven explanations can help developers understand unfamiliar code paths, APIs, or patterns. This can support onboarding and maintenance work where reading and summarizing code consumes significant time. It also helps when documenting intent or translating requirements into implementation steps.
Limited public product details
Publicly verifiable information about exact capabilities (supported IDEs, languages, deployment options, and governance controls) is limited based on the product name alone. This makes it difficult to validate fit for enterprise requirements such as auditability, data handling, and administrative controls. Buyers typically need a vendor-led demo and documentation review to confirm scope.
Quality depends on context
Like other AI coding assistants, output quality depends heavily on prompt clarity and the amount of project context available. Without strong context, suggestions can be incorrect, insecure, or inconsistent with internal standards. Teams still need code review and testing to manage risk.
Unclear security and compliance posture
For many AI coding assistants, key differentiators include data retention policies, model hosting options, and access controls. Those elements are not verifiable here without official documentation. This can be a blocker for regulated environments or organizations with strict source-code confidentiality requirements.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Open Source (Local) | Free | MIT-licensed open-source version; runs locally; Web GUI, Terminal UI, CLI; Git integrations; community support. |
| Individual (Cloud) | Free | Hosted cloud access; bring-your-own-LLM key or use OpenHands LLM provider at-cost; API support; Jira & Slack integrations; supports BYOK; intended for 1 user. |
| Growth (Cloud) | Starts at $500 per month | Shared workspace for teams; variable seats; shared projects & agents; multi-user RBAC; centralized billing & usage reports; ticket-based support. |
| Enterprise | Custom pricing | SaaS or self-hosted in customer VPC; Enterprise SAML/SSO; unlimited concurrent conversations per user; Large Codebase SDK; priority support & shared Slack channel; contact sales. |
