Gotcha vs Grass: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Gotcha and Grass — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Gotcha

Samosa-AI

Freemium

On-device Android AI copilot that turns natural language into 100+ real device actions with dual safety modes.

On-device Copilot: Runs entirely on the user's Android phone with a bring-your-own-model architecture, so prompts, screen context, and actions never require a cloud round-trip.
Dual Copilot Modes: Instant switch between Monitor mode (40+ read-only tools for planning) and Operator mode (all 100+ tools for execution) so users choose inspection vs action per task.
100+ Native Device Tools: Send SMS, place calls, manage storage, toggle torch, set wallpapers, read the screen, control volume, and automate any app through a curated Android tool library.
Tiered Permission Model: Four permission tiers (from everyday battery/storage access to Tier 4 privileged root actions) with explicit gates so nothing runs without user consent.
Assistive Ball & Push-to-Talk: A floating orb accessible from any app supports 'Hey Gotcha' voice calls where Gotcha sees the current screen and acts on the user's behalf.
Visual Safety Indicators: A colored ring around the screen shows when Gotcha is reading the display (blue) or working in the background (orange), backed by an append-only audit log.
BYOK Model Choice: Bring your own local or cloud model — or use free Samosa AI credits routed through the OpenAI-compatible Samosa AIR API for zero setup.
Skill Hub Extensibility: Add third-party skills through the Gotcha Skill Hub so the copilot's action library grows with the community.

Hands-free Messaging: Say 'Text mom I'm running late' and Gotcha finds the contact and sends the SMS without touching the screen.
Storage Cleanup: Ask Gotcha to free up space and it inspects app usage, then confirms uninstalls of games or apps you haven't opened in months.
Screen-aware Shopping: While browsing a page, ask 'find similar shirts to the one worn here' and Gotcha reads the screen, searches the web, and returns matches.
Quick Device Control: Toggle the torch, set the volume, change wallpaper, or open a specific playlist in Spotify with one spoken sentence.
Privacy-first Automation: Users who don't want cloud LLMs running their phones can plug in a local model and keep prompts, screen content, and actions on-device.
Developer Copilot Extensions: Ship a Gotcha Skill so a niche workflow (e.g., custom-app automation) becomes a first-class action inside the copilot.

Freemium

VM-first compute platform that gives coding agents a dedicated, always-ready virtual machine for running and testing code without local setup.

Dedicated VM Allocation: Provides each coding agent with a dedicated virtual machine that is pre-provisioned and kept ready to execute code, eliminating per-run provisioning delays and local resource use.
Zero-Configuration Runtime: Removes developer setup and configuration by supplying preconfigured runtimes so agents can run, test, and iterate on code immediately.
Agent Integrations: Works natively with agent runtimes such as Claude Code and OpenCode to allow LLM-based agents to connect directly to the VM environment for code execution and debugging.
Free Trial Hours: Offers an initial free allocation (10 hours) so teams can evaluate the platform and run early experiments without payment.
Remote Execution & Isolation: Executes agent workloads inside isolated VMs to protect developer machines from heavy compute, long-running processes, or accidental resource exhaustion.
Warm VM Availability: Keeps VM instances ready-to-use to reduce cold-start latency for interactive agent-driven coding sessions.
Provisioned, dedicated VM per coding agent that stays ready to run tasks
No local setup or configuration required
Compatibility stated with Claude Code and OpenCode agent platforms
Managed compute to avoid using developer laptop resources
Free initial allocation (10 hours) to start

Agent-driven Code Testing: Run language-model-based coding agents to generate, compile, and run test suites in a safe remote VM without installing dependencies locally.
Offloading Heavy Builds and Tests: Execute CPU- or memory-intensive compilation and test jobs in remote VMs to avoid overloading developer laptops or CI runners.
Interactive Agent Pair-Programming: Connect Claude Code or OpenCode agents to a persistent VM for fast, iterative coding and debugging sessions with immediate execution feedback.
Automated Repair and Refactoring: Allow agents to run refactoring scripts or automated repair tools on real runtime environments and verify results in-isolation.
Prototyping and Experimentation: Quickly spin up agent-backed development environments to prototype integrations or reproduce bugs using a predictable, preconfigured VM.
Running autonomous coding agents that need persistent compute
Offloading heavy or long-running code execution from developer machines
Integrating external code-focused LLM agents (e.g., Claude Code, OpenCode) with dedicated runtime environments
Quick experimentation with agents using the free trial hours before committing to paid plans