Dropstone vs Everywhere: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Dropstone and Everywhere — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Dropstone
Blankline
Self-hosted AI agent with long-term memory that spans CLI, chat, SDK and real-world actions, running on open-weight models you host.
Key features
- Persistent Cross-Surface Memory: Teach the agent something once in the CLI and it already knows it in chat, in the SDK and on a phone call — memory persists per user across sessions and surfaces instead of dying with one login.
- Self-Hosted Open-Weight Stack: Run the entire agent inside your own walls on your keys, machines and network, using open weights the company hosts or local models through Ollama, so source code never leaves your infrastructure.
- Proactive Background Operation: The agent is already running rather than waiting to be opened — it monitors what you asked it to watch and hands back only the decision that was actually yours.
- Approval-Gated Real-World Actions: Control smart-home devices, monitor an inbox around the clock, place phone calls and look up half-remembered contacts, with every action gated behind an explicit approval.
- 1M-Token Context on Every Tier: A one-million-token context window is included even on the free plan, letting the agent hold an entire repository in mind at once.
- Model-Agnostic Tiering: Dropstone Fast, Pro and Heavy each run whatever tops the open-weight leaderboards that month rather than being tied to a single lab.
- Learned Skills: The agent picks up skills it does not yet have, retains them and reuses them without being asked twice, with the skill list growing month over month.
- Multi-Surface Access: Reach the same agent through the Dropstone CLI, a web dashboard, VS Code / Cursor / Windsurf extensions and Remote MCP connectors, with sandboxed code execution and plan mode before changes apply.
Best for
- Air-Gapped Engineering Teams: Ship real code with an AI agent while keeping the models, the repository and the network entirely inside company infrastructure.
- Always-On Inbox Triage: Let the agent watch an inbox around the clock and surface or act on the messages that matter instead of checking it yourself.
- Terminal-Native Development: Use the CLI agent to generate code, run it in a sandbox and open diffs, with plan mode and approval gates before anything is applied.
- Personal Operations Automation: Hand off recurring real-world tasks — smart-home control, placing a call, chasing a contact — to an agent that already has your context.
- Cost-Sensitive Heavy Usage: Get several times more weekly coding usage per dollar than subscription coding CLIs by running on self-hosted open-weight models.
- Custom Agent Integration: Embed the same memory-backed agent into your own stack through the SDK and Remote MCP connectors.
Everywhere
Sylinko (DearVa)
Context-aware desktop AI assistant that senses your screen, understands application context, and acts in-place across platforms.
Key features
- Context-Aware Invocation: Captures text and UI context directly from the screen so the assistant can answer or act without manual screenshots, copying, or app switching.
- Multimodel Provider Support: Connects to numerous LLM/MCP providers (OpenAI, Anthropic/Claude, Google Gemini, Ollama, DeepSeek, Moonshot, OpenRouter, SiliconCloud) allowing flexible model selection and fallbacks.
- Inline Overlay UI: Modern frosted-glass overlay summoned via keyboard shortcuts that renders Markdown, supports voice input, and displays contextual responses adjacent to the relevant UI element.
- Actionable Responses: Beyond explanations, the assistant can draft emails, translate text, summarize web pages, analyze error messages, and propose step-by-step fixes based on captured context.
- Cross-Platform Desktop Integration: Built with .NET and Avalonia to run on Windows, macOS, and Linux with deep desktop integration for consistent experience.
- Extensibility and Open Source: Distributed under Apache-2.0 with community discussions and contribution paths on GitHub; supports plugins and integration with external tools.
- Privacy and Self-Hosting Friendly: Local client that can be configured to use user-supplied API keys and model endpoints, enabling control over which services process data.
- Context-aware screen sensing that captures and understands visible content without manual screenshots
- Direct desktop integration with context-aware invocation beside content
- Supports multiple model providers and runtimes (OpenAI, Anthropic/Claude, Google Gemini, Ollama, OpenRouter, Moonshot/Kimi, DeepSeek, SiliconCloud, etc.)
- Retrieval-augmented workflows (RAG) and integration with external search / web summarization
- UI-automation capabilities to take actions in applications based on assistant instructions
- Modern UI (frosted-glass style), Markdown rendering and rich text output
- Voice input and keyboard shortcut invocation
- Cross-platform support via Avalonia for Windows, macOS, and Linux
- Extensible via chat/plugins and connectors to model service providers
- Open-source codebase (Apache-2.0) with public documentation and GitHub repository
Best for
- Error Troubleshooting: Summon Everywhere next to an application error message to get a diagnosis and step-by-step remediation without copying the text or leaving the app.
- Quick Research Summaries: Call the assistant while reading a long article or documentation page to produce concise multi-point summaries in-place.
- Instant Translation: Select foreign-language text on-screen and request immediate translation without switching to a separate translator app.
- Email and Writing Polishing: Highlight draft text in an email or editor and ask Everywhere to rephrase, professionalize, or shorten the content inline.
- Contextual Code Help: Invoke the assistant on snippets of code or logs shown on-screen to get explanations, bug-hunting tips, or suggested fixes informed by surrounding context.
- Desktop Task Automation: Use the assistant to perform contextual actions (e.g., copy structured data, open related resources, or run configured workflows) based on UI elements.
- Diagnosing and resolving on-screen error messages by invoking assistant next to the error
- Summarizing long web articles with three-point summaries without leaving the page
- Instant translation of selected foreign text in-place
- Drafting and polishing emails or other text directly from a desktop editor
- Using multiple LLM providers or local runtimes for redundancy, privacy, or cost control
- Automating UI tasks by having the assistant take actions in applications