Dropstone vs Triggered Agents That Start Working Instantly | Adaptive: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Dropstone and Triggered Agents That Start Working Instantly | Adaptive — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Dropstone
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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.
Triggered Agents That Start Working Instantly | Adaptive
Adaptive
Event-triggered agents that start automatically to turn bookings, payments, forms, and updates into completed work.
Key features
- Event-Triggered Agent Launch: Monitors events (bookings, payments, form submissions, updates) and automatically instantiates the appropriate agent to act immediately when a trigger occurs.
- Task Automation Across Business Functions: Agents execute concrete tasks such as sales follow-up, marketing campaign actions, customer lifecycle updates, market research tasks, and small website or content changes without manual input.
- E-commerce Actionability: Integrates with commerce workflows so that inventory or order events can prompt agents to find suppliers, draft purchase orders, or take other procurement actions (example: Shopify low-stock → supplier search and PO draft).
- Instant Orchestration: Agents start working instantly on detected events to reduce response time and ensure time-sensitive tasks are handled promptly.
- Event-to-Action Mapping: Allows mapping of specific event types to specialized agent behaviors so businesses can tailor what agent runs for each kind of signal.
- Operational Efficiency: Reduces manual handoffs by converting routine updates, payments, and bookings into automated work items that complete end-to-end tasks or hand back structured results.
- Automatic agent invocation on predefined triggers (bookings, payments, forms, updates)
- Converts events into executable tasks and workflows without manual start
- Prebuilt event-action patterns (e.g., low-stock → supplier search → draft PO)
- Integration-ready design for business tools and platforms
- Applies to multiple business domains: sales, marketing, customer lifecycle, market research, website tasks
Best for
- Automated procurement: When Shopify or inventory monitoring indicates low stock, an agent locates suppliers, drafts purchase orders, and prepares procurement follow-up.
- Sales follow-up after bookings: Immediately trigger automated outreach and next-step scheduling when a customer booking is recorded.
- Payment-triggered workflows: Launch reconciliation, invoicing, or fulfillment tasks automatically when payments are received or fail.
- Lifecycle-driven marketing: Start targeted marketing campaigns or onboarding sequences when a user signs up or reaches lifecycle milestones.
- Market research tasks: When signals or form responses indicate interest or trend, spawn agents to gather data, summarize findings, and recommend actions.
- Website and content updates: Convert form submissions or business updates into tasks to build, update, or publish small sites and content changes automatically.
- Monitor Shopify inventory and auto-generate purchase orders when stock is low
- Turn completed booking or payment events into downstream fulfillment tasks
- Automate responses and follow-ups for leads and customer lifecycle events
- Trigger marketing campaign actions based on form submissions or customer updates
- Run market research tasks automatically when relevant data or updates arrive