Stop losing money on forgotten SaaS subscriptions and "ghost" licenses. Toolspend is the ultimate command center for your stack, designed to give you 100% spend visibility without the manual upkeep. While other tools just list your apps, Toolspend deep-dives into your actual usage and spend patterns. We identify underutilized seats, detect duplicate tools across teams, and alert you before every renewal. Toolspend helps you automate the toil of procurement so you can focus on building!
Lancepilot
Excited to hunt ToolSpend today 😎
Teams are rapidly adopting tools like ChatGPT, Claude, Midjourney, Cursor, and more but visibility into actual AI spend is lagging behind.
AI usage (tokens) and real cash out the door rarely live in the same place. That’s the gap ToolSpend is solving by connecting AI services with financial data to show what you’re truly spending and where you can optimize.
If you're scaling with AI, this is a problem worth paying attention to.
Congrats to the team on the launch 👏
Makes sense companies suddenly have 10+ AI tools per team and nobody knows who’s using what 😅 If it actually tracks real usage + catches ghost seats before renewal, that’s legit ROI. AI spend visibility is quickly becoming finance infra, not just ops tooling.
Toolspend
@julia__watson Julia — 100%.
What’s changed is that now anyone can spin up a product with AI APIs. You don’t need a full engineering org anymore — just an API key and an idea.
That’s powerful… but it also means:
• more experiments
• more tools per team
• more shared accounts
• more silent renewals
Suddenly you have “micro-products” and internal automations everywhere — and finance has zero visibility into which ones are still active or delivering value.
That shift is exactly why AI spend visibility is becoming infrastructure, not just ops tooling.
Are you seeing more bottom-up experimentation in your circles, or is this mostly top-down AI initiatives driving the sprawl?
@istiakahmad @visagar @priyankamandal @Toolspend @om_pandey12
Two months ago, when I asked ChatGPT for ideas, the first idea they gave me was this same tool and in the end, they asked me to select this idea. But I ignored this toolspending idea and today someone else executed this SaaS idea. What I learned from this is that whatever you think, research it and do it as soon as possible.
Toolspend
@istiakahmad @priyankamandal @om_pandey12 @rajeevmallik it was way harder to execute than we initially thought. AI billing + usage data is messy. But we kept iterating.
The token-to-dollar thing hits different when you're running multiple products. We've got 4 AI apps going and trying to compare spend across Anthropic, OpenAI, etc just gets stupid complex - per-token vs per-seat vs credit buckets, they're all over the place. Do you normalize all that into a single view, or just show raw costs? Been thinking it'd be useful to see which devs are burning tokens fastest too, spotted some hilariously inefficient prompts that way.
Congrats on the launch!! The 'AI ghost license' problem is so real in 2026. It's way too easy for a team to have three different Claude Pro accounts and an API key running on a forgotten test server.
It's great that you’re connecting both banking data via Plaid and direct API usage. Would love to know the average 'savings' you're finding for a typical seed-stage startup!
minimalist phone: creating folders
I think it is kinda useful for people who have like million subscription plans. :)
Toolspend
@busmark_w_nika You’re right — at first glance it feels like this would only help people juggling a ton of subscriptions
But what we’re seeing is something slightly different.
It’s about how even one AI provider now behaves like 10 different cost centers.
Take OpenAI as an example. A single team might be using:
• GPT-4o for their customer-facing chatbot
• GPT-4o mini for internal automation scripts
• GPT-4 Turbo for long-context document processing
• Embeddings API for semantic search
• Whisper for call transcription
• Image generation endpoints for marketing assets
• Assistants API with tool calls for internal workflows
On the invoice, that all shows up as one line item: “OpenAI.”
But operationally, each of those is a separate cost driver.
For example:
– A developer switches a background job from GPT-4o mini to GPT-4o “temporarily”
– An embeddings process runs more frequently than expected
– A support bot accidentally defaults to a higher-cost model
– A script forgets to cache responses
Suddenly the invoice jumps — and no one knows exactly why.
ToolSpend breaks usage down by model, endpoint, and token consumption so you can see what’s driving spend and whether a cheaper alternative could achieve similar results.
So it’s less about having a million subscriptions — and more about visibility inside the ones you already rely on.
minimalist phone: creating folders
@visagar aaa, I didn't know, that it "tracks" it this way, interesting!
Hello Toolspend Team : How do we contact you ?