Intrascope.app
Centralize your team’s AI, cut costs and stay organized
258 followers
Centralize your team’s AI, cut costs and stay organized
258 followers
Intrascope helps companies scale AI without fragmented tools, unpredictable costs, or loss of control. It brings leading AI models, company knowledge, and agentic workflows into one shared workspace. Teams work smarter with intelligent model routing, MCP, RAG, and reusable context, while admins manage access, budgets, policies, and usage analytics. With BYOK, managed AI usage, local models, and private deployments, Intrascope makes enterprise AI simpler, safer, and more cost effective.
This is the 3rd launch from Intrascope.app. View more
Intrascope 2.0
Launching today
What's different: ChatGPT and Claude lock you into one vendor. Intrascope 2.0 gives your team 120+ models (GPT-6, Claude, Gemini, Grok, Qwen) plus an AI agent that works in 1,650+ apps like Gmail, Slack, Drive and Notion. The company stays in control: admins approve apps and models, set budgets per team, project and person, and see every token and dollar. New in 2.0: agent, connectors, Skills, Auto routing, full redesign. Private and on-prem deployments for enterprise.
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Launch Team / Built With
Hey Product Hunt 👋 Vladimir here, co-founder of Intrascope.
You may remember us from our last launch (#5 Product of the Week in SaaS, thank you!). Since then 170+ companies have used Intrascope, and they all told us the same thing:
"Love having every model in one place. Now give us our own tools, our own knowledge, and even tighter control over cost."
So we rebuilt Intrascope from the ground up. Today we're launching Intrascope 2.0.
What's new for every team:
• 120+ models, incl. Claude Opus 5.5, GPT-6, Gemini, Grok 4.20, Qwen 3.8, Kimi, DeepSeek
• Smart routing: pick "Auto" and the agent chooses the right model for each task, so simple questions never burn premium tokens
• Agentic answers that use your company context: Manifests, project files, web search and your connected apps
• 1,650+ connectors (Gmail, Slack, Notion, GitHub, HubSpot, Salesforce...). Admins decide which apps the company can use, people connect with their own permissions
• Skills: built-in playbooks plus your own, triggered with "/"
• Limits and budgets per company, team, project and person
• Smarter context control that trims tokens on every request
• A completely new design
For larger orgs: private deployments (VPC or on-prem), custom RAG over internal knowledge, local LLMs/SLMs next to public models, and a white-label edition for telcos and universities.
Why we care: most companies pay for 4 to 6 AI subscriptions and still can't answer "who used what, and what did it cost?" Intrascope gives people freedom and gives the company one view, one budget and one bill.
🎁 PH community: grab the exclusive Product Hunt offer on this page and start your free 7-day trial (no card needed) at portal.intrascope.app.
We'd love your honest feedback:
Would you trust Auto routing, or do you always pick the model yourself?
Which connector should we make deeper first?
The whole team (Jakov, Stefan, Mihajlo and me) is here all day. Ask us anything!
Looks promising! Could Solofounders use it in their SaaS business?
Thanks! @hovakimyan
Honestly, Intrascope is built mainly for teams, where the governance and orchestration layer really matters: model approvals, budgets per team, usage tracking and control over which tools people can connect.
That said, solo founders can absolutely use it and get a lot out of it. You’d have 120+ models in one place with your own API keys, separate projects for product, marketing and support, a Manifest so the AI always knows your SaaS context, and Skills for repeat work like changelogs or support replies. And once you start hiring, the control layer is already there.
Hey Product Hunt! Stefan here, Chief of Engineering at Intrascope.
Vladimir covered the “why.” I’ll add a bit of the “how.”
Rebuilding 2.0 meant treating AI like real infrastructure, not a chat wrapper. The hard parts weren’t the demos -
they were the edges:
• Smart routing was the biggest rabbit hole. “Auto” isn’t just cheapest-model-wins. We had to model each LLM’s capabilities, strengths, and trade-offs - reasoning depth, tool use, speed, context window, multimodal support, cost - then match that profile to the intent of the request in real time
• Agent + MCP that can reach into 1,650+ apps without turning every workflow into a brittle custom integration
• Shared company context (Manifests, projects, permissions) so answers use your knowledge - without leaking context across teams
• BYOK + usage controls so finance and security stay in the loop while the product still feels fast for everyday use
A lot of nights went into making that stack boringly reliable. The goal was simple - teams should scale AI without trading control for convenience.
If you run AI across a team: what’s the messiest part for you right now - picking the right model, costs, or getting agents to work with your real tools?
Happy to dig into any of the engineering decisions in the thread.
"Boringly reliable" is the nicest thing an engineer can say about their own code 😄 Thanks@stefan_car , and thanks to the whole team for all those late nights ☕☕☕
Spoiler: the kitchen is already open again. 3.0 is cooking 👨🍳🔥 Nobody sleeps, but at least the routing knows exactly which model to wake up 😅
Looks promising :)
Which types of companies can get the most benefit from the app?
@esergijevic Thanks, glad you like it! 🙂
The sweet spot is companies with roughly 50 to 500 employees that already use several AI tools across teams, especially:
• Software and tech companies
• Agencies (marketing, sales, SEO, creative)
• Consultancies and professional services
They usually have the same story: everyone uses a different AI tool, costs are scattered across cards and invoices, and IT has no idea which data goes where. Intrascope gives them one workspace with all the top models, connected to their real tools, while IT and finance keep control over models, budgets and access.
Smaller teams can start self-serve in a few minutes, and for larger or regulated companies we also do private and on-prem deployments.
This looks really interesting! How does Intrascope handle shared context across different AI models? Can team members collaborate on the same projects without constantly repeating context?
@dvoretskii Great question, and thanks for asking!
This is actually one of the core problems we built Intrascope to solve.
Instead of managing isolated conversations, teams work within shared Projects, each with its own persistent context, instructions, and knowledge.
For example, your team can start working on a project using GPT, continue with Claude or Gemini, and still have access to the same project context without starting from scratch.
We also introduced Project Manifests, which allow teams to capture important decisions, insights, and information from conversations and make them available for future interactions.
The goal is simple: AI shouldn't just remember individual conversations. It should help teams build and retain collective knowledge, regardless of which model they're using.
And we're continuing to expand this with RAG integrations and more advanced context management capabilities!
I pick it myself, but by task type, not per message. a cheaper model for search and mechanical edits, the strong one for drafts and anything a client reads. could Auto routing take rules like that instead of guessing?
@olia_nemirovski Great question, and that's a really sensible way to work!
Not yet. Right now Auto doesn't guess per message though: it classifies the task (search, edits, drafting, reasoning...) and picks the best model for that type of work. You can already shape what it chooses from with limits per model and provider, so admins can block or cap anything they don't want in the mix.
Custom rules like "cheap model for search and edits, strong one for anything client-facing" are something we haven't been asked for by clients yet, but it makes a lot of sense. Thanks for the feedback, this one looks like a good candidate for 2.1 🙂