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Thank you for the support 🙌
Thank you to everyone who supported us during our Product Hunt launch
We finished #9 Product of the Day on a very competitive day, with some big launches happening as well. Even @OpenAI and @LiveDocs with very useful products was in the mix
We re genuinely happy with the traction so far. More importantly, we ve already welcomed our first international teams who are actively testing Intrascope in real workflows, which means a lot to us.
Intrascope was built to solve a real internal problem for our own team, and seeing others resonate with it confirms we re on the right path.
Use case: Cost savings for a 10-person team using Intrascope
A common setup we see in 10-person teams looks like this:
Before Intrascope
Most teams end up paying for multiple AI subscriptions.
6 10 people on individual ChatGPT or Claude plans.
Some teammates even share accounts, which mixes context and leads to poor outputs.
Typical cost
10 $20/month = ~$200/month
And that s before any advanced usage or extra tools.
With Intrascope
The team works inside a single shared workspace using their own API keys.
One admin controls which models are available and sets usage limits.
How we’re handling API key trust in a BYO-key AI workspace
We re currently in beta with Intrascope and one question keeps coming up around trust and API keys.
Some people are understandably cautious about entering their LLM API keys into any tool. That concern makes sense especially with new products. What s interesting is that in our case bringing your own API key is the core of how Intrascope works and why it exists in the first place.
We built Intrascope because we experienced the opposite problem. Teams using multiple AI tools had no real visibility into usage or costs until it was too late. By using your own API keys you stay in full control of spending limits usage and access across the whole team.
This approach is already common across many tools from WordPress plugins to internal dashboards and browser extensions. Still trust has to be earned not assumed.
The real problem we’re solving with Intrascope
Most AI tools look shiny on the surface, but the moment a real team starts using them, the same problems appear again and again.Everyone has separate accounts and API keys.
Everyone chats in isolated windows.
Context gets lost.
Costs grow without anyone noticing.
Teams end up using 5 7 different apps just to use AI.
We built Intrascope because we were dealing with exactly this chaos inside our own company.
There was no single place where teams could use multiple AI models together, share context, track usage, set limits, collaborate, and actually optimize cost instead of guessing.
So the real problem we are solving is simple:
AI is becoming essential for teams, but the way teams use AI today is messy, expensive, and completely fragmented.
With Intrascope, we created a workspace that gives you:


