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AI or Not
✓ verifiedFreemium
AI or Not detects AI-generated and deepfake images, video, audio and text via API with a claimed 98.9% accuracy.
240K visits/mo2.9K saves
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Krira Labs
✓ verifiedPaid
Generative-AI infrastructure startup building production RAG pipelines, fine-tuning, and agentic systems for developers.
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LlamaIndex
✓ verifiedFreemium
Developer framework and LlamaParse service for parsing documents and building AI agents and RAG workflows over them.
455K visits/mo1.9K saves
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Agentset
✓ verifiedFreemium
Open-source RAG infrastructure with SDKs and an API for developers to build accurate, cited AI chat and search on their own data.
24K visits/mo
Pricing
No public pricing
Free: $0 ($5 in credits, 1M words + 20 image checks)
Pro: $5/mo ($10 credits/mo)
No public pricing
No public pricing
Free: $0 (1,000 pages, 10,000 retrievals)
Pro: $49/mo (10,000 pages, unlimited retrievals)
Core features
- ✦Markdown to Notion publishing
- ✦Automatic subpage creation from directory structure
- ✦CLI flag support for title and emoji
- ✦Integration with Notion's AI, search, and formatting
- ✦AI image, video, audio and text detection
- ✦Deepfake detection
- ✦Detection API with key included
- ✦Per-use credits across all modalities
- ✦Model-level breakdown of results
- ✦Enterprise/on-prem and reseller options
- ✦End-to-end RAG pipeline engine
- ✦Rust-based document chunking
- ✦Model fine-tuning (low-rank adaptation)
- ✦Autonomous multi-agent systems
- ✦Model Context Protocol integration
- ✦Integrated coding/dev tools
- ✦LlamaParse document parsing and extraction
- ✦Open-source framework for AI agents and workflows
- ✦Document indexing for retrieval/RAG
- ✦Prebuilt solutions by industry and use case
- ✦Free starter credits for LlamaParse
- ✦Managed RAG pipeline (extraction, chunking, retrieval)
- ✦Automatic source citations
- ✦Multimodal support (images, tables, graphs)
- ✦Model-agnostic: choose vector DB, embeddings, LLM
- ✦Metadata filtering
- ✦MCP server and AI SDK integration
- ✦22+ file-format ingestion
Use cases
- →Publishing documentation to a Notion workspace
- →Creating a public website from markdown documentation
- →Maintaining documentation alongside code in a repository
- →Verify whether media is AI-generated
- →Screen content for deepfakes
- →Integrate AI detection into workflows via API
- →Building RAG-based applications
- →Fine-tuning models to a domain
- →Multi-agent reasoning systems
- →Enterprise AI application infrastructure
- →Parse complex documents for AI apps
- →Build RAG and agent workflows
- →Automate invoice and claims processing
- →Search across technical documents
- →Build a chatbot over private documents
- →Add semantic or deep search to an app
- →Ground answers in a large corpus with citations
- →Ship production RAG without building it in-house
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