Welcome to Vanish

AI Co-workers that complete tasks 100x faster across your entire stack

Three things that make Vanish different

AI Co-workers remember everything important
Your AI Co-workers remember your projects, tools, workflows, and preferences. They maintain context across all your apps and tasks.
AI Co-workers work across your entire stack
From databases to APIs to deployment - your AI Co-workers handle tasks across all your tools, finishing in minutes what used to take hours.
AI Co-workers multiply your productivity
Deploy multiple AI Co-workers that work in parallel. Watch them complete complex multi-step tasks 100x faster than traditional methods.

Getting Started

1. Describe what you need done

Tell your AI Co-worker what you want to accomplish - AI Co-workers understand complex, multi-step tasks.

2. Watch them work across your tools

AI Co-workers access databases, call APIs, update code, run tests, and deploy - all automatically.

3. Get results 100x faster

Tasks that took hours now complete in minutes. Your AI Co-workers handle the tedious work while you focus on what matters.

Pro tip: For best results, break complex tasks into steps.

Read our Best Practices Guide →

See it in action

You:
"When high-priority support emails come in, create Jira tickets and notify the team in Slack"
AI Co-worker:

I'll set up this workflow across Gmail, Jira, and Slack. Here's what I'm doing:

  • Monitoring Gmail inbox for emails with "urgent" or "critical" keywords ✓
  • Found new high-priority email from customer@company.com
  • Creating Jira ticket: "SUPPORT-4521: Database connection timeout issue"
  • Adding customer details and email content to ticket description ✓
  • Assigning to on-call engineer based on schedule ✓
  • Posting to #support-alerts Slack channel with ticket link
  • Added 👀 reaction and threaded the customer's email content
  • DM'd assigned engineer with context and suggested solutions

Workflow complete! Your team is notified and ticket is tracked.

Time elapsed: 15 seconds (vs 10-15 minutes manually)

Best Practices

Break Complex Tasks into Steps

❌

Don't:

"Create a complete CRM system with reporting and notifications"

✅

Do:

1. "Let's set up the customer database"

2. "Now add the contact management features"

3. "Great! Let's create the reporting dashboard"

Why: Prevents token limits, maintains context, allows verification at each step

Wait for Completion Between Steps

Let your AI co-worker finish each task before giving the next instruction. This ensures quality and prevents confusion.

Handle Rate Limits Gracefully

If you see rate limit errors, wait 1-2 minutes before continuing. Break large data operations into smaller batches.

Use Memory Effectively

Your AI co-worker remembers previous conversations in the same chat. Reference past work: "Using the schema we created earlier..."

Perfect for tasks like

Customer Support Automation

Monitor Gmail for support requests, create Jira tickets, update CRM records, and notify teams in Slack - all automatically.

Sales Pipeline Management

Track emails from prospects, update HubSpot deals, create follow-up tasks in Asana, and send Slack alerts when deals move stages.

Project Status Updates

Gather updates from Jira, GitHub, and Google Docs, then compile and send weekly reports via Gmail and post summaries to Slack.

Lead Routing & Assignment

Parse incoming leads from Typeform, enrich data with Clearbit, assign to sales reps in Salesforce, and notify via Slack.

Your data is always private. AI Co-workers only access what you explicitly allow, and you maintain full control over your workspace and tools.

Start Working 100x Faster →