AICosts.ai

Most multi-provider AI stacks produce fragmented billing: each vendor has its own portal, its own billing cycle quirks, and its own unit taxonomy — tokens here, characters there, operations somewhere else. AICosts.ai addresses that fragmentation by ingesting read-only billing data from 50+ providers — OpenAI, Anthropic, Google Vertex, AWS Bedrock, Azure OpenAI, Cohere, Groq, and more — and normalizing everything into a unified daily spend view broken down by platform and model. For providers without a billing API, the tool accepts PDF or CSV invoice uploads and parses them into the same structured format. Export in CSV or JSON covers any date range across any provider subset.

The differentiating feature relative to rolling your own spreadsheet is the forecast card: it projects 30-day spending from a 7-day trailing sample and renders an 80% confidence interval as a visible band rather than a single number. That spread matters when you are setting a quarterly budget and need to communicate uncertainty honestly to a finance team, not just report a point estimate that will inevitably be wrong.

The tool fits squarely in an observability role. It does not sit in your inference path, does not read prompts or completions, and does not reroute or switch your traffic based on cost signals — the vendor is explicit about this. The ‘what-if’ comparison page shows what the same token volume would have cost on a cheaper model; acting on that finding is your call. Peer benchmark data for a given model unlocks only when at least three customers in the cohort use it — below that threshold, the tool tells you plainly rather than fabricating a benchmark.

API keys are encrypted server-side with AES-256-CBC before storage, and the read-only scope means the tool never modifies provider configuration. Budget alerts are deduped monthly, so crossing the 80% threshold does not generate a new email every day — one notification per threshold crossing per month.