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Bravolity•

6h ago

What's your biggest headache with LLM cost management in production?

Hey everyone

I'm Bravolity building AgentGate, a lightweight LLM gateway designed for small AI teams (5 50 people).

Before writing a single line of code, I spent a few weeks on Reddit and developer forums just listening. A few pain points kept coming up independently:

  • Cost visibility token-level costs exist, but teams can't tell which agent task or workflow run caused a spike

  • Model lock-in when a new model drops, teams are stuck waiting weeks for their gateway to support it

  • Enterprise-gated basics SSO, audit logs, cost controls... all locked behind $1,000+/month tiers

We're building specifically for the teams that fall through the cracks between "too small for Enterprise" and "too busy to self-host LiteLLM."

My question for you: what's the most frustrating part of managing LLM API costs in your current stack? Is it the observability, the tooling, or just the sheer unpredictability of agent-driven workloads?

Would love to hear what you're running into this is exactly the kind of input that shapes what we build first.

Waitlist: https://agentgate-theta.vercel.app

Bravolity•

6h ago

AgentGate - Agent-aware LLM cost tracking for small teams.

Lightweight LLM gateway for teams of 5-50, without Enterprise pricing. ā‘  Per-task cost trees, not flat logs See Task → 30 calls across 3 models → $0.47 total. Not just a bill. ā‘” New models work on day one Transparent proxy. OpenAI-compatible models route instantly. No waiting. ā‘¢ Team controls included Usage alerts, rate limiting, data export. No "contact sales" wall. Waitlist live. Built for teams who've outgrown hacky scripts but can't justify $500/mo plans.