Spring AI alternatives in 2026: 24 tools like Spring AI

Closest: LLM Frameworks & RAG

DSPy

Framework for algorithmically optimizing LM prompts and pipelines

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Haystack

End-to-end NLP framework for LLM apps

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LangChain

Framework for developing LLM-powered applications

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LlamaIndex

Data framework for LLM applications

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Semantic Kernel

Microsoft's AI orchestration SDK; successor is Microsoft Agent Framework

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More in RAG & Memory

BGE Reranker

BAAI's high-performance multilingual reranker

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Cohere Rerank

Reranking models from Cohere for improving RAG relevance

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ColBERT

Late interaction retrieval model with token-level embeddings

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Jina Reranker

Multilingual reranker for improving RAG precision

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Sentence Transformers

Python framework for training and running embedding models

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Docling

Document conversion and parsing toolkit for gen AI pipelines

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LandingAI

APIs that extract structured data from documents, from Andrew Ng's company

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LlamaParse

Optimized document parsing for RAG by LlamaIndex

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Marker

Convert PDFs to markdown quickly and accurately

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Reducto

High-accuracy document extraction for complex PDFs

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Sarvam Vision

Document parsing model for Indian-language PDFs, forms and handwriting

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Unstructured

Document processing for RAG pipelines

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Upstage Document Parse

Converts complex documents into formats LLMs can read, plus data extraction

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Cognee

Semantic memory layer building knowledge graphs for AI agents

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Letta (MemGPT)

Platform for stateful agents with advanced memory that learns over time

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Mem0

Universal persistent memory layer for AI agents and assistants

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Supermemory

Memory and context API that gives AI agents long-term recall

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Zep

Temporal knowledge graph memory for agents (Graphiti)

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F

FlashRank

Ultra-lite cross-encoder reranking for RAG

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Questions

What are the closest alternatives to Spring AI?

DSPy, Haystack and LangChain sit on the same sub-line as Spring AI (LLM Frameworks & RAG) on AI Landscape, with 2 more.

How are these alternatives chosen?

They are the other products on the RAG & Memory stop of the map: curated products first, the ones on Spring AI's sub-line before the rest, then by name until members have marked enough of them.