Oskar vs Proto-Mind: Features, Pricing & Which Is Better (2026)

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

Oskar

Skarbe

Paid

AI-powered sales assistant that captures emails and meetings, suggests next steps, and keeps deals on track for non-salespeople.

Automatic Capture: Continuously captures emails and meeting data to record interactions and preserve deal context without manual entry.
Next-Step Suggestions: Analyzes conversation and meeting context to recommend actionable follow-ups and priorities for each deal.
Deal Tracking: Maintains visibility into deal progress and surfaces items that need attention to keep opportunities moving.
Non-Sales Friendly Interface: Designed for users who are not sales specialists, reducing friction and training required to manage sales activity.
Contextual Reminders: Prompts users about outstanding tasks and recommended actions based on captured communications and timelines.
Passive capture of emails related to deals
Capture and logging of meetings
Contextual next-action suggestions to progress deals
Automated deal tracking to reduce manual CRM entry
Designed for non-salespeople to manage sales workflows

Managing inbound leads from email by capturing correspondence and receiving recommended follow-ups without a CRM.
Empowering founders or product teams to track sales conversations and next steps directly from their inbox and calendar.
Customer success teams tracking renewal conversations and action items by capturing meetings and suggested next actions.
Small teams avoiding CRM adoption but needing automated deal tracking and reminders based on real communications.
Streamlining follow-up workflows by surfacing prioritized next steps after sales calls or email exchanges.
Small teams that want pipeline visibility without adopting a full CRM
Non-sales employees who need help following up and progressing opportunities
Automating meeting and email capture to maintain deal history
Providing suggested next steps to accelerate stalled deals

VIRENCORE

Free

A native macOS floating workspace that keeps AI conversations, project memory, files and live voice together on your Mac.

Floating Cube Workspace: Hover the cube to reveal the workspace and click to pin it, or move away to hide it while tasks keep running in the background.
Per-Conversation Model Routing: Each chat picks its own model and account — ChatGPT with Codex access, supported model APIs, or a local Ollama model.
Editable Project Memory: Notes, decisions and preferences stay attached to a project and carry into later conversations, and you can review, change or remove any of them.
Live Voice Control: Speak to open a project, steer a running task or send new work, and add a correction while the task is still going.
Detachable Companion Windows: Pull out and resize a browser, a file or a second conversation so reference material sits beside the work.
Explicit Mac Access: Codex can work with files and run commands only after you turn Mac access on; screen control additionally requires Codex Desktop's signed Computer Use helper.
Local Data Storage: Conversation history and saved memory live on your Mac, and cloud processing happens only when you choose a cloud model or voice.
Open Source Beta: The macOS installer and the Apache 2.0 source are both published, so the workspace can be inspected and built from source.

Long-Running Project Work: Keep a website or client project's decisions in project memory so each session resumes instead of re-explaining the brief.
Brief to Deliverable: Have the agent read a client brief and save a proposal document, then open it in a companion window next to the conversation.
Parallel Task Execution: Start several tasks across different models at once and check back on them without blocking the conversation you are in.
Hands-Free Steering: Dictate a correction or open a project by voice while your hands are busy elsewhere on the Mac.
Privacy-Sensitive Drafting: Run a local Ollama model so conversation content never leaves the machine.
Model Comparison: Put the same question to a Codex route and a local model in adjacent windows to compare the answers side by side.