Thoughts on the new Helicone Teams feature?

Hey everyone, I've been poking around the new Teams feature in Helicone for the past few days, and I wanted to share some initial thoughts and see if anyone else has been diving in. As someone who's constantly juggling different projects and API keys, the promise of better team-level management and cost tracking was immediately appealing.

So far, the core idea is solid: creating a shared workspace separate from personal usage. I've set up a team for our internal chatbot evaluation project. The good stuff first:
* **Unified Request Logging:** This is huge. Being able to see all prompts, responses, and costs from my team members in one dashboard saves us from the nightmare of merging CSV exports from individual accounts.
* **Separate Budgets & Alerts:** We can finally set a project-specific budget and get alerts when we're nearing it, instead of just having a global personal budget. This makes forecasting for individual experiments or client work way simpler.
* **Member Roles (Admin/User):** Basic but necessary. I can grant teammates access to the project's data without giving them my personal API key or making them an admin on my whole account.

However, coming from a tinkering mindset, I immediately started looking for the edges and comparison points. A few things I'm curious about or think could be more fleshed out:

* **Granularity of Permissions:** Right now, roles seem to be all-or-nothing at the team level. I'd love to see something like "can view logs and costs but cannot modify alert settings" for certain members. Has anyone found a workaround for this?
* **Integration with Existing Personal Logs:** When you create a team, it seems like a totally fresh start. I wish there was a way to migrate or associate some of my past personal requests into the team bucket for historical context, especially since some of that work was the genesis for the team project.
* **How does this compare to building similar oversight internally?** I've also used a approach where we pipe all our LangChain/LLM calls through a custom wrapper that logs to a shared database. Helicone Teams is definitely easier to set up, but I'm still evaluating the trade-off on custom analytics vs. their provided dashboard.

The feature feels like a strong v1.0. It solves the immediate, painful problem of "whose cost is this?" and provides a clean audit trail. I'm really hoping future updates lean into the *evaluation* aspect—like allowing us to tag team requests by experiment version or dataset, and then comparing costs/latency/quality scores across those groups.

What's everyone else's experience been? Have you hooked it up to a CI/CD pipeline for testing? Are you using it to track costs across different embedding models (that's my next experiment)? 🧪