I

I made a unified productivity OS for teams

Hacker News

I made a unified productivity OS for teams

Context: In the last decade, the B2B SaaS landscape has expanded exponentially. As a result, businesses today often find themselves juggling between 150-250 different SaaS tools to operate. Such a hyper-fragmented work environment raises the question: is it time for SaaS consolidation? Consequence: * Employee Productivity Concerns: The frequent switching between different apps and contexts results in a notable 10% drop in productivity, as reported by HBR. * SaaS Financial Impact: Companies often allocate funds for SaaS features that remain underutilized. Such expenditures can unnecessarily strain budgets. * Data Modeling Challenges: Every SaaS platform introduces its unique interface, adding another layer of complexity to how business data is structured, often leading to data redundancy and confusion. * Operational Demands of SaaS: Introducing a new SaaS solution means setting up and managing one more user system, data labeling system, and file organization structure. AI increases the need for a clean, centralized data AI an be seen as an accelerator for the importance of having centralized, clear, and coherent business data. Streamlined and well-labeled data sets enhance the quality of AI-driven insights. However, even for the best AI, if key information, like a work-related note, is locked away in personal tools, its value cannot be harnessed for business insights. I decided to take on SaaS fragmentation by creating a unified collaboration OS for teams. In a Nutshell: Frame comes with 5 apps: Notes, Tasks, Wiki, Whiteboard and Goals Our design principles are: Minimalism: we go back to the core of what you need in each app (think Apple Note or Medium.com) Interoperability: seamlessly refer docs across apps (e.g., insert a link to a note from the whiteboard) Collaboration: co-create in real-time docs in every app Frame comes packed with super-powers: Cross-apps search (Cmd-K bar): search content across all apps & team members Templates: leverage powerful templates for any department and apps (e.g., a sprint review template for PMs on the whiteboard app) AI magic: from automatic labeling of docs to summarizing any text - we got you covered Blazing fast: Lightning-fast navigation using shortcuts for the ultimate Superhuman-like experience Advanced filters: easily retrieve docs with a unified labeling system across apps (e.g., find my notes and whiteboard docs created by John or Adam, last month with the label ‘Fundraising’) Real-time co-creation: co-create docs in any app in real-time with your teammates Our Vision: Frame’s vision is to create a unified way of working across the company. We value minimalism and a unified interface, ala MacOS. Our long-term vision is to create a one-stop shop for your team so they can access any business data from Frame and get business insights. What’s coming next: More apps: Contacts, Dashboard, Processes - we’re only getting started Advanced AI interaction: get better insights on your business by having all your business data in one place, with a unified labeling system. Video real-time co-creation: Launch video calls while co-creating docs. Beyond Frame: access Frame from anywhere on the web Data import: easily import your data from your most popular apps Integrations: Google for Work, Slack, Figma: integrations are coming soon We’ve managed to ship this under $700K using open source tech and are looking for feedback from developers & PMs

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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, model · Missing: agents, agent, cursor
98%98% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: created, started · Missing: supports, reddit linkedin, podcasting
97%97% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: personal, apps, video · Missing: mobile apps, ios, entrepreneurs
66%66% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: open source, ide, io · Missing: https docs, excited, just released
42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, interface, soon · Missing: plus, intuitive, reviews
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: introduce · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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