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Plato – Google-like search for company APIs and docs

Hacker News

Plato – Google-like search for company APIs and docs

Hi HN, We noticed a common issue working at companies like Amazon and Capital One, searching for documentation relevant to our projects was time-consuming and difficult. After doing some research, we found: - Service catalogs and internal search tools at many companies rely on keyword search (so you can’t just search in natural language for a package that “fetches user favorites”) - Relevant docs can be scattered in many different places - If bugs arise or docs are missing, you have to wait to talk to the right engineer on another team Plato lets teams create “spaces” for their services/repos with: - An OpenAPI spec plus links to documentation, GitHub, and Slack support. - A chat window that can read your docs using RAG to answer questions about the service and help with debugging issues. The idea is to fit this all into one page, to let devs get the necessary information to start implementing as quickly as possible. We looked at other developer-portal-like tools such as Backstage and Cortex, but didn’t see anything that focuses on making services searchable and making the documentation experience better. We thought that enterprise-search companies like Glean didn’t optimize the workflow of a developer well enough for our liking. That being said, we’re still looking for ways to significantly improve the documentation and API search experience, and are open to feedback. Feel free to sign up, try it out, and email us directly if you have feature requests, suggestions, or other ideas: rohan@platoportal.com arjun@platoportal.com Link: https://platoportal.com

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3points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, google, user · Missing: mac, agents, macos
97%97% 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 · Missing: supports, reddit linkedin, podcasting
60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: google, way · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: plus · Missing: platform, intuitive, reviews
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
10%10% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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