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Show HN: AI Cost Board – Track LLM Cost, Requests, and Errors Across Providers
Hi HN,
I just launched AI Cost Board, a small project I built to make multi-provider AI usage easier to operate in production.
It gives you a unified dashboard for:
total spend
token usage
request volume
latency and error rates
What it enables:
one proxy layer for multiple providers
request logs for debugging and visibility
budgets + alerts for cost control
workspace/project structure for teams
pricing + subscription flow for Free/Pro plans
The goal is simple: make AI costs and performance observable in real time, without stitching together multiple tools.
I’d really appreciate feedback on:
product usefulness
onboarding flow
pricing model
missing features you’d expect for production use
Thanks for checking it out.
- robinbanner 9mo agoNice dashboard. Cost visibility is the first step — you cannot optimize what you cannot measure. We have found that the natural next step after tracking is automated routing. Once you see that 70% of your frontier model calls could have been handled by something much cheaper, you want a system that does that automatically. At Komilion we route each API call to the cheapest model that fits based on benchmarks. The combination of monitoring (like this) + routing gives you both visibility and automatic savings. One thing I would suggest adding: cost-per-quality metrics. Raw cost is not the full picture — $0.80/M tokens that fails 20% of the time is more expensive than $2/M tokens that works reliably.