Mo
Monitor LLMs Using LangChain and Infino
Hacker NewsMonitor LLMs Using LangChain and Infino
Monitor LLM prompts, outputs, errors and token usage using LangChain and Infino
Share cardActual performance
1points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos87%87% 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.
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto81%81% predicted probability of success on BetaList, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive35%35% 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, revenue13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
Ra
Raink – Document ranker using LLMs60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Raink – Document ranker using LLMs
Hacker News2Be
BerriAI – Monitor Hallucinations in LLMs (Sentry for LLM Apps)66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
BerriAI – Monitor Hallucinations in LLMs (Sentry for LLM Apps)
Hacker News4Us
Using LLMs and Embeddings to classify application errors80%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Using LLMs and Embeddings to classify application errors
Hacker News65Ne
Neurooo – DeepL clone using LLMs for translations40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Neurooo – DeepL clone using LLMs for translations
Hacker News18GP
GPTCache – Redis for LLMs69%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
GPTCache – Redis for LLMs
Hacker News7pr
prompttest – pytest for LLMs34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
prompttest – pytest for LLMs
Hacker News2Sy
System monitor for OSX50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
System monitor for OSX
Hacker News1SL
SLA Monitor by StatusGator50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
SLA Monitor by StatusGator
Hacker News1Ma
Magellan VHDL Monitor40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Magellan VHDL Monitor
Hacker News2Pe
Per-monitor workspaces for Compiz 0.8.x51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Per-monitor workspaces for Compiz 0.8.x
Hacker News8