Beezi AI

Congrats on the launch! Might be helpful for us

The insight that AI amplifies whatever you give it rather than creating clarity on its own is something more people building with AI need to hear. I have experienced this firsthand building DocMetrics alone — the AI coding tools are genuinely fast but if your own thinking about what you are building is unclear the AI just gets you to the wrong place faster. The ticket clarification piece before coding starts is the part I find most interesting because most teams treat requirements as a formality rather than the actual foundation of everything that follows. Curious how Beezi handles situations where the ticket looks clear on the surface but the underlying requirement is actually ambiguous — does it flag that or only catch structural issues? Congrats on launching.

The real-time AI cost tracking is something I didn't know I needed until I started using multiple models for the same project and had no idea what I was actually spending.As a solo maker, does Beezi work for individual developers or is it built exclusively for teams?

Nice launch! Quick one on the Smart Ticket System, does it give live feedback while someone's writing a ticket (e.g. "this is too vague, clarify X"), or is it a structured template?

Great project! Exactly what industry needs but what I feel a lot of companies are not ready for yet. How does PM or PO integrates with this tool? To my understanding this tool tries to take a part of their responsibility, and the quality of this orchestration is yet unknown.

smart ticket system sounds like it could solve a real problem. half our AI prompts end up being too vague and we waste cycles on back-and-forth. curious how you're structuring the prompts - are you using specific templates for different development tasks or is it more dynamic based on the ticket content?

the model routing optimizer caught my attention - we've been manually switching between Claude and GPT for different coding tasks and it's such a pain. does Beezi learn from your team's patterns to suggest the best model for each ticket type, or is it more rule-based routing?

Curious about the privacy side of this, are prompts or code stored anywhere, or does everything stay private within the customer environment?

Congrats on your launch, ticket structuring before coding is very important because tickets decide quality of code produced. I was wondering though, is manual override possible, for example in case I want to push a particular ticket?

So with Ollama I can bring my own model like: ZLM? or are there a set of models that you provide?

Congrats on the launch @oleksandr_semeniuk @oleglysiak @yuliia_melianytska 🎉 Most teams jump straight to prompting and wonder why output is still messy. How long does setup typically take for a team already on Jira + Slack?

Interesting concept. If a company stops using Beezi AI, what happens to their stored data and history?

Hey Product Hunt! 👋 I am Yuliia, as CMO of Beezi AI, I want to share what's behind today's launch, because this isn't a product we dreamed up in a vacuum.Before writing a single line of marketing packaging and copy, we ran dozens of customer interviews. Engineering leads, CTOs, dev team managers across different industries and company sizes.What struck me most from those conversations? People weren't asking for more AI. They were asking for control, structure, predictability.That's the north star we've been building toward not just another wrapper that makes AI feel fancy. We want to make a platform that makes AI-driven development something you can actually manage, measure, and trust at scale.We're genuinely proud of what the team built. And genuinely curious what you think. 🙏What's your biggest frustration with AI in your dev workflow right now?If you'd like a demo or want to participate in our customer interviews — we'd love to connect! 🎯

Very cool - I'm super interested in products in this space, this looks like a good one - congrats on the launch!

Hey Product Hunt 👋
I’m Alex, co-founder of Beezi AI — an orchestration layer for AI-driven software development.
Over time, I kept noticing the same pattern: AI speeds up coding, but everything around it gets messy. Unclear requirements, too many retries, rising costs, and very little visibility.
So my team and I came up with Beezi AI to bring structure, control, and clarity to the process.

What Beezi does:
• Clarifies and structures tickets before coding (Smart Ticket System)
• Routes tasks to the most efficient models (Model Routing Optimizer)
• Tracks delivery speed, AI usage, and cost in real time (Analytics Hub)
• Works inside your existing tools (Jira, Azure DevOps, GitHub, Bitbucket, GitLab, Slack, MS Teams) — no workflow disruption
• Supports secure, on-prem or private cloud setups with full data control

Who it’s for:
Engineering leaders and their teams already using AI, who want more predictable delivery, better cost control, and less chaos in their workflows.

Why we built it:
AI doesn’t create clarity — it amplifies whatever you give it.
Most teams focus on prompting, but the real bottleneck is everything around it: task definition, workflow consistency, and visibility.

Beezi is our attempt to fix that at the system level.
We’d really love your feedback!
• Where does AI slow your team down today?
• What’s hardest to control — cost, quality, or consistency?
• Does this approach make sense for your workflow?

Happy to answer any questions and dive deeper into how it works!