Launched this week
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!
Very Nice and useful idea, will you consider offering a white label solution as well?
Toolspend
@viva_jam Thanks Saga, really appreciate that.
White-label is definitely something we’re considering — especially for agencies and consultancies managing AI spend across multiple client accounts.
Curious — would you be thinking about using it internally, or offering it as part of a service to your own clients?
Toolspend
Hey Product Hunt
AI tools are exploding inside companies.
What isn’t exploding? Visibility into what they actually cost.
Teams are subscribing to ChatGPT, Claude, Midjourney, Cursor, Perplexity, ElevenLabs… and finance only finds out when the bill hits.
The real problem?
AI usage (tokens) and actual spend are completely disconnected.
That’s why we built ToolSpend.
It connects your AI services + banking data and shows:
• What you're really spending
• Which teams are driving usage
• Where you’re overpaying
• Smarter model alternatives
AI shouldn’t be the next AWS surprise bill.
Excited to hear your feedback — especially from founders & dev teams already scaling with AI
Lancepilot
Hey Product Hunt 👋
We’re the makers of ToolSpend - and we built this because we ran into the same problem ourselves.
Inside our own team, we were using ChatGPT, Claude, Midjourney, Cursor, Perplexity AI, and ElevenLabs across different projects.
Everyone was moving fast.
No one knew what we were actually spending.
Engineering saw token usage.
Finance saw card charges.
Those two worlds never met.
We realized AI spend is fundamentally different from traditional SaaS:
Usage (tokens) ≠ invoices
Teams experiment constantly
Model pricing changes fast
“Just $20/month” tools multiply quickly
So we built ToolSpend to connect AI services + banking data into one clear view:
Real AI spend across providers
Usage by team/project
Overlapping subscriptions
Smarter / cheaper model alternatives
Our goal: make AI spend observable before it becomes your next surprise bill.
We’re early and building this with founders & dev teams who are scaling fast with AI.
We’d love your honest feedback:
What’s hardest about managing AI spend today?
What metrics do you wish you had?
What would make this a no-brainer to adopt?
Thanks for checking us out 🙌
Meet-Ting
@priyankamandal The chokehold I'm in with all our tools is bananas.
Toolspend
@priyankamandal @dbul 😂 I feel this.
That “we’ll just try one more AI tool” phase turns into 15 subscriptions real fast.
That’s exactly the chokehold we’re trying to fix with ToolSpend — visibility before the month-end surprise hits.
@visagar This is such a smart niche to go after! 👏 I (well, the whole team) use a lot of AI tools daily, and tracking what we’re actually spending manually… it gets messy fast. Love the idea!
I’m curious – how granular can the team-level visibility get? Can you attribute usage down to specific projects or cost centers, or is it mainly per tool / per team right now?
Toolspend
@tereza_hurtova Love this question and honestly… I’ll give you the real answer.
Right now, it’s strong at:
Per tool visibility (OpenAI, Anthropic, etc.)
Per API key / account
Team-level rollups
Token + cost breakdown where the provider allows it
But project-level / cost-center attribution?
That’s where we want to go — and we’re figuring that out with users.
Truthfully, we didn’t want to overbuild assumptions about how teams structure AI spend. Some companies use separate API keys per project. Others share keys across everything. Some think in “cost centers,” others think in “clients,” others just want “who ran this model and why did it spike?”
So instead of guessing the perfect structure upfront, we’re starting with clear usage visibility and letting real usage patterns guide the next layer.
What we’re already seeing:
Even one provider (like OpenAI) behaves like 5–10 different cost centers depending on models, environments, and use cases. That’s the real chaos we’re trying to bring clarity to.
So short honest answer:
Granular at tool + key + team level today.
Project-level attribution is something we’re actively shaping based on feedback like yours.
If you had your ideal setup — would you want spend broken down by client, by internal product, or by something else entirely?
@visagar Appreciate the transparent answer! That approach makes a lot of sense to me. We’re building our product too, and I relate to that tension between the long-term vision and what’s realistic today. There’s always the “ideal structure” in your head… and then there’s the messy reality you discover through users. 😀
Starting with clear visibility and letting real usage patterns shape the next layer feels like the right call.
If I imagine an ideal setup, I’d probably want flexibility – the ability to view spend by client and by internal product/project.
In our case, cost centers shift depending on whether we’re experimenting, building core features, or running infra. So being able to re-group dynamically would be powerful.
And you’re right – even one provider can behave like multiple cost centers. That’s exactly where the chaos starts.
Excited to see how you evolve the attribution layer! 🙂
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 👏
Makers Page
Yep, rogue AI seats are killing us. Surprise Midjourney/Cursor/Claude charges and then finance pings me. If this actually maps tokens to teams + nudges before renewals, that’d help. Does it catch stuff paid on personal cards that get expensed later?
Toolspend
@alexcloudstar Yep — Runway, Midjourney, Cursor, Claude are usually the usual suspects
ToolSpend connects via Plaid, so both company accounts and personal cards (that later get expensed) can be pulled in and don’t stay invisible.
From there we map usage to teams and nudge before renewals so finance doesn’t get surprise bills.
We’re actively adding more AI services over the coming days.
This is super timely with everyone subscribing to 5 different AI tools. :D
Does the tool separate variable costs from fixed seat-based subscriptions?
Toolspend
@valeriia_kuna Yes — that separation is core for us.
We split variable usage (like token-based API costs that can spike) from fixed seat-based subscriptions (which quietly stack up across teams).
Without that distinction, finance just sees one big number — and it’s hard to know what’s actually driving spend.