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

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

Ami

AiSDR

Paid

AI GTM agent that picks the audience, writes and launches outbound campaigns, reads the results and fixes what stops working.

Autonomous Campaign Loop: Ami picks the target audience, builds and launches the campaign, reads what comes back and changes what is not working, so each campaign sharpens the next without a human restarting the cycle.
Baked-In GTM Experience: Arrives with 27 industry playbooks and the lessons of 17,150 prior AiSDR campaigns and 19,501 meetings, so a first campaign launches with patterns other teams paid to learn.
Signal-Triggered Outreach: Watches hiring, funding and job-change signals and acts at the moment they happen rather than months later.
Performance Triage: When response rates slip, Ami digs into audience, message and sequence to pinpoint what is breaking and proposes fixes before the budget is spent — flagging, for example, a positive response rate under 1% after 21+ days.
Omnichannel Sequences: Configurable sequences combining email via Gmail or Outlook, LinkedIn connection requests, DMs and InMail, and AI call steps through the Aircall dialer with scripts and automated follow-ups.
Deep Per-Lead Personalization: Researches the top three most relevant data points per lead and personalizes from ICP data, activity, LinkedIn data and HubSpot properties.
Native CRM Sync: Two-way HubSpot sync on every plan and two-way Salesforce sync on higher tiers, with AI research and monitoring running over that CRM data.
Review Mode: Campaigns and Ami's proposed corrections stay drafts until approved, so the agent's autonomy is opt-in rather than assumed.

Founder-Led Outbound: A solo founder builds pipeline without hiring an SDR, starting self-serve with no sales call required.
Rescuing Stalled Campaigns: A revenue team catches a dying sequence early when Ami flags a collapsing positive-response rate and rewrites the audience or message.
Replacing Outbound Agencies: A company that has paid outside firms without results brings the motion in-house under one agent.
Warm-Signal Prospecting: A sales team reaches buyers right after a funding round, a relevant hire or a job change instead of cold-listing an industry.
CRM-Grounded Targeting: A HubSpot or Salesforce team has outreach built from and logged back into existing CRM data rather than a disconnected tool.
Multichannel Follow-Up: A team runs email, LinkedIn and dialer touches in a single sequence with replies handled in 5-10 minutes or in co-pilot mode.

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.