What we’re building at Barie, and why reliability comes first

Hi everyone, I’m part of the team at Barie.ai. I wanted to share a bit about what we’re working on and the thinking behind it.

As AI adoption grows, one issue keeps showing up across tools: confidently incorrect outputs. For casual use, that’s annoying. For research, planning, or decision-making, it becomes a real risk. At Barie, we started with a simple question: what would AI look like if trust was the primary constraint, not speed or flair?

Barie is being built as a general AI agent that focuses on deep research, source-backed answers, and multi-step task execution, with a strong emphasis on minimizing hallucinations. We’re designing systems that verify information, expose reasoning through citations, and prioritize correctness over instant responses.

Another core part of Barie is connectors. Instead of working in isolation, Barie can connect to the tools and apps people already use. Once connected, users can ask Barie to research, reason, and then perform actions directly within those apps. The idea is to move from “AI that answers” to “AI that reliably executes,” while keeping humans in control.

We’ll be launching Barie soon on Product Hunt, but for now, this thread is a place for us to share progress, ideas, and learn from others building in this space. Looking forward to discussions around accuracy, agent design, and responsible AI execution.

Happy to answer questions or exchange ideas.