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Pazi

Third-party toolFreemiumAgents & Automation

AI agents mapped to company roles — developer, SDR, marketer — each given a goal and left to plan its own work.

Highlights

  • Create AI agents mapped to specific company roles and assign each a concrete objective
  • Goal-based tasking: each agent generates its own plan toward the stated outcome
  • Multi-step, end-to-end execution rather than single-trigger rule automation
  • Parallel agents that run different workstreams at the same time
  • More than twenty integrations, including Slack and Microsoft Teams
  • A single dashboard for oversight, progress check-ins, and human approval
  • Founder-in-the-loop control over what agents are allowed to do
  • Positioned for solo founders building lean, one-person operations
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About Pazi

What it is

Pazi asks you to create agents that correspond to job roles rather than tasks, then give each one an objective. The agent writes its own plan, executes multi-step work across more than twenty integrations including Slack and Teams, runs in parallel with other agents, and reports into a single dashboard. The framing the company uses is the autonomous company, with the founder supervising rather than doing.

Why it's different

Goal-based tasking is meaningfully different from the trigger-and-action model of Zapier or Make: you state an outcome instead of a sequence. When it works, it handles the branches you did not anticipate. The honest caveat is that this is the hardest thing in the field and nobody has convincingly solved it. Agents given open-ended goals reliably drift, repeat themselves and act confidently on wrong premises, and the cost of that is higher when the agent has write access to your CRM. Treat the autonomous company framing as ambition rather than description, and supervise anything that touches customers.

How people use it

The sensible use is narrow and reversible — research, drafting, internal reporting, anything where a bad output is discarded rather than sent. Founders without staff use it to cover functions they have no one for, which is the real appeal. Start with one agent on one bounded objective, read everything it produces for a fortnight, and widen access only where its judgement has actually held up.

Written by the n3os team. We are not affiliated with Pazi.

This listing was written from public information, without Pazi’s involvement. If you own it and something here is wrong — or you would rather not be listed at all — email us and we will correct or remove it.

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