Assistaan, the AI-Powered Customer Support Tool for Scalable Support

Hacker News

Hi Hacker News community, My name is Israel Cauich, co-founder and CEO of Neuraan and I would like to introduce you to Assistaan, a customer support tool designed to help teams provide standardized, fast, and scalable support without the need for investing in additional staff to maintain service response quality. Assistaan leverages AI technology to maximize the attention volume, learning automatically from agent responses and asking agents for the best answer when uncertain or lacking information. This ensures that your customers receive high-quality support, and your team can handle a larger volume of inquiries without sacrificing quality. Unlike other chatbot solutions that require a team to create a knowledge base, define a conversational flow, and create response variants, Assistaan simplifies the process by learning from your existing support interactions, enabling your team to provide efficient, accurate, and personalized responses with minimal effort. To see Assistaan in action, please check out our demo at https://youtu.be/Uwb8A4XKTNI . If you're interested in signing up for access or providing feedback, please visit our website at https://www.neuraan.com Thank you for your time, and we look forward to hearing from you soon. Israel Cauich Co-founder & CEO

Visit product View on Hacker NewsFeb 27, 2023

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Indie HackersFits the IH revenue-focused audience · Strong signals: maximize · Missing: supports, reddit linkedin, podcasting

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best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, new · Missing: mac, macos, cursor

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, hacker news · Missing: https docs, excited, just released

55%55% 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: soon, efficient · Missing: plus, platform, intuitive

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

32%32% predicted probability of success on TrustMRR, 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, introduce · 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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