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AgentGate

Launching today

Agent-aware LLM cost tracking for small teams.

3 followers

Agent-aware LLM cost tracking for small teams.

3 followers

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Lightweight LLM gateway for teams of 5-50, without Enterprise pricing. ① Per-task cost trees, not flat logs See Task → 30 calls across 3 models → $0.47 total. Not just a bill. ② New models work on day one Transparent proxy. OpenAI-compatible models route instantly. No waiting. ③ 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.

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Launch tags:API•Developer Tools•Artificial Intelligence

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Hey Product Hunt! Solo founder here — I started AgentGate after talking to 20+ dev teams and hearing the same thing over and over: "Why are basic features like cost dashboards and usage alerts locked behind Enterprise plans?" I'm currently in validation phase (pre-code, pre-revenue) and genuinely looking for honest feedback on three things: ① Is "no Enterprise pricing wall" actually a differentiator you care about, or do most teams just accept it? ② When you think about LLM cost tracking — is it a "nice to have" or a "can't ship without it"? ③ What would make you switch from whatever you're using today? Landing page is live and I'm collecting early waitlist signups. Happy to answer any questions about the approach or what I learned from the user research so far!

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19h ago

Forum Threads

p/agentgate-2

•

5h 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

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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