LLMWise

Get insightful text analysis with machine learning that extracts, analyzes, and stores text. Train high-quality machine learning custom models without a single line of code with AutoML. Apply natural language understanding (NLU) to apps with Natural Language API. Use entity analysis to find and label fields within a document, including emails, chat, and social media, and then sentiment analysis to understand customer opinions to find actionable product and UX insights. Natural Language with speech-to-text API extracts insights from audio. Vision API adds optical character recognition (OCR) for scanned docs. Translation API understands sentiments in multiple languages. Use custom entity extraction to identify domain-specific entities within documents, many of which don’t appear in standard language models, without having to spend time or money on manual analysis. Train your own high-quality machine learning custom models to classify, extract, and detect sentiment.

Sudo offers “one API for all models”, a unified interface so developers can integrate multiple large language models and generative AI tools (for text, image, audio) through a single endpoint. It handles routing between different models to optimize for things like latency, throughput, cost, or whatever criteria you choose. The platform supports flexible billing and monetization options; subscription tiers, usage-based metered billing, or hybrids. It also supports in-context AI-native ads (you can insert context-aware ads into AI outputs, controlling relevance and frequency). Onboarding is quick: you create an API key, install their SDK (Python or TypeScript), and start making calls to the AI endpoints. They emphasize low latency (“optimized for real-time AI”), better throughput compared with some alternatives, and avoiding vendor lock-in.