Anyone else integrating specialized AI tools like the Tavily search API into their agents or workflows? It’s fantastic for getting relevant, concise web info for LLMs, but it adds another line item to the already complex AI bill.
You’ve got your main LLM costs (OpenAI, Claude, Gemini), maybe some vector storage (Pinecone?), workflow tools (Make/n8n/Zapier), API calls to Tavily, etc. Figuring out the total cost per task or per user query when it involves multiple API calls across these services can get really messy, really fast.
I found myself struggling to consolidate these costs. How much did that complex agent interaction really cost, factoring in the LLM, the Tavily search, and maybe a database lookup? Spreadsheets weren’t cutting it, and the lack of a unified view was frustrating.
That’s why I built AIBillingDashboard.
What it helps with:
- Unified Cost View: Upload logs from services like Tavily, OpenAI, Claude, Gemini, Pinecone, Make, etc., to see all your AI spending in one dashboard.
- Service Breakdown: Understand how much you’re spending specifically on Tavily versus your LLMs or other components in your stack.
- Usage Analytics: Track API calls and associated costs to identify which parts of your agent or workflow are most expensive and where optimization might be possible.
- Budget Tracking: Monitor overall AI spending against budgets and get alerts for billing cycles across all connected platforms.
It’s designed to give you clarity on costs, especially when using a mix of general-purpose LLMs and specialized tools like Tavily.
Curious to hear from others using Tavily or similar specialized AI APIs. How are you tracking the costs associated with these tools in the context of your broader AI usage? Any specific challenges?