AI · alternatives · 2026

24 alternatives to Tilores Identity RAG

Customer data search, unification and retrieval for LLMs

Tilores Identity RAG is a tool that connects to large language models to search and retrieve unified customer data from multiple source systems. Data scientists use it to gather scattered customer information across… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Tilores Identity RAG launched in 2024; newer entries below may have overtaken it.

1
Ragie Connect▲353
Build RAG applications on your user data
2025 · ragie.ai · its alternatives →
2
Tilores Studio desktop entity resolution▲30
Tilores is cloud-based entity resolution software used for fraud-detection, AML, RAG - but being cloud based makes it difficult for people to test as they are reluctant to upload sensitive data. To fix that we built a downloadable version of Tilores that runs entity resolution on your desktop. No data egress. Works best with the demo data as it is currently fixed schema and matching rules.
Jul 2026 · tilores.io · its alternatives →
3
Turn any website into a knowledge base for LLMs▲305
I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications. It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically. I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...
2024 · embedding.io · its alternatives →
4
Ragas – Open-source library for evaluating RAG pipelines▲121
Ragas is an open-source library for evaluating and testing RAG and other LLM applications. Github: https://docs.ragas.io/en/stable/, docs: https://docs.ragas.io/. Ragas provides you with different sets of metrics and methods like synthetic test data generation to help you evaluate your RAG applications. Ragas started off by scratching our own itch for evaluating our RAG chatbots last year. Problems Ragas can solve - How do you choose the best components for your RAG, such as the retriever, reranker, and LLM? - How do you formulate a test dataset…
2024 · github.com · its alternatives →
5
RAGstack▲111
Deploy a private ChatGPT alternative hosted within your VPC
2023 · github.com · its alternatives →
6
LiquidIndex 2.0▲134
I'm building LiquidIndex, an RAG API service that makes it easy to add personalized context to AI apps. Instead of building a whole system to upload, process, and search through a user’s files or notes, you just call a few APIs. It handles the hard parts - like connecting to Notion or Google Drive, breaking the data into usable pieces, and making it searchable. Then, when you want to answer a question using that data, you just query it, and it gives you the most relevant results - optionally with an LLM-generated answer. No pipelines, no infrastructure, no headaches. Here are the core APIs:…
2025 · liquidindex.dev · its alternatives →
7
Demystifying Advanced RAG Pipelines▲131
I've built an advanced RAG (Retrieval-Augmented Generation) pipeline from scratch to demystify the complex mechanics of modern LLM-powered Question Answering systems. This repository features: -- An implementation of a sub-question query engine from scratch to answer complex user questions. -- Illustrative explanations that unveil the inner workings of the system. -- An analysis of the challenges I faced while working with the system, like prompt engineering and cost estimation. -- Qualitative comparison with similar frameworks like LlamaIndex, offering a broader perspective. Key Takeaway:…
2023 · github.com · its alternatives →
8
IdentityRAG – customer identity resolution for LLM applications▲6
Connect to your customer data using any LLM and gain actionable insights. IdentityRAG creates a single comprehensive customer 360 view (golden record) by unifying, consolidating, disambiguating and deduplicating data across multiple sources through identity resolution. - tilotech/identity-rag-custom
2024 · github.com · its alternatives →
9
FastGraphRAG – Better RAG using good old PageRank▲457
Hey there HN! We’re Antonio, Luca, and Yuhang, and we’re excited to introduce Fast GraphRAG, an open-source RAG approach that leverages knowledge graphs and the 25 years old PageRank for better information retrieval and reasoning. Building a good RAG pipeline these days takes a lot of manual optimizations. Most engineers intuitively start from naive RAG: throw everything in a vector database and hope that semantic search is powerful enough. This can work for use cases where accuracy isn’t too important and hallucinations are tolerable, but it doesn’t work for more difficult queries that…
2024 · github.com · its alternatives →
10
PageIndex – Vectorless RAG▲192
Not all improvements come from adding complexity — sometimes it's about removing it. PageIndex takes a different approach to RAG. Instead of relying on vector databases or artificial chunking, it builds a hierarchical tree structure from documents and uses reasoning-based tree search to locate the most relevant sections. This mirrors how humans approach reading: navigating through sections and context rather than matching embeddings. As a result, the retrieval feels transparent, structured, and explainable. It moves RAG away from approximate "semantic vibes" and toward explicit reasoning…
2025 · github.com · its alternatives →
11
RAGatouille, a simple lib to use&train top retrieval models in RAG apps▲15
Hey HN! If you’re at all interested in LLMs/LLM-apps, you’ve probably heard of RAG: Retrieval-Assisted Generation, i.e. retrieving relevant documents to give to your LLM as context to answer user queries. Today, I’m releasing RAGatouille v0.0.1, whose aim is to make it as easy as can be to improve your RAG pipelines by leveraging state-of-the-art Information Retrieval research. As of right now, there’s quite a big gap between common everyday practice and the IR literature, and a lot of the gap is because there just aren’t good ways to quickly try out and leverage SotA IR techniques.…
2024 · github.com · its alternatives →
12
Rag About It▲48
Dive deep into AI Retrieval Augmented Generation (RAG)
2024 · ragaboutit.com · its alternatives →
13
Vectorize▲246
Build RAG pipelines that are optimized for your data.
2024 · vectorize.io · its alternatives →
14RA
ragapi – an API for using LLMs on your own data▲12
2023 · ragapi.com · its alternatives →
15
Verta RAG System▲84
Go from dataset to custom RAG prototype in 5 minutes
2024 · cloudera.com · its alternatives →
16TL
Tiny LLMs – Browser-based private AI models for a wide array of tasks▲142
2023 · tinyllms.vercel.app · its alternatives →
17AW
A web-based Excel/Database hybrid▲82
2012 · ragic.com · its alternatives →
18
RAGLite – A Python package for the unhobbling of RAG▲19
RAGLite is a Python package for building Retrieval-Augmented Generation (RAG) applications. RAG applications can be magical when they work well, but anyone who has built one knows how much the output quality depends on the quality of retrieval and augmentation. With RAGLite, we set out to unhobble RAG by mapping out all of its subproblems and implementing the best solutions to those subproblems. For example, RAGLite solves the chunking problem by partitioning documents in provably optimal level 4 semantic chunks. Another unique contribution is its optimal closed-form linear query adapter…
2024 · github.com · its alternatives →
19
R2R – Open-source framework for production-grade RAG▲167
Hello HN, I'm Owen from SciPhi (https://www.sciphi.ai/), a startup working on simplifying˛Retrieval-Augmented Generation (RAG). Today we’re excited to share R2R (https://github.com/SciPhi-AI/R2R), an open-source framework that makes it simpler to develop and deploy production-grade RAG systems. Just a quick reminder: RAG helps Large Language Models (LLMs) use current information and specific knowledge. For example, it allows a programming assistant to use your latest documents to answer questions. The idea is to gather all the relevant information…
2024 · github.com · its alternatives →
20IB
In-Browser Graph RAG with Kuzu-WASM and WebLLM▲158
We show the potential of modern, embedded graph databases in the browser by demonstrating a fully in-browser chatbot that can perform Graph RAG using Kuzu (the graph database we're building) and WebLLM, a popular in-browser inference engine for LLMs. The post retrieves from the graph via a Text-to-Cypher pipeline that translates a user question into a Cypher query, and the LLM uses the retrieved results to synthesize a response. As LLMs get better, and WebGPU and Wasm64 become more widely adopted, we expect to be able to do more and more in the browser in combination with LLMs, so a lot of…
2025 · blog.kuzudb.com · its alternatives →
21
Korvus▲122
Search SDK to unify RAG pipeline in a single database query
2024 · github.com · its alternatives →
22
Ragas – Open-source library for evals and testing RAG systems▲15
Ragas is an open-source library designed for evaluating and testing RAG (Retrieval-Augmented Generation) and other LLM applications. It offers a diverse set of metrics and methods, including synthetic test data generation, to help you assess your RAG applications. Ragas was initially developed to address our own needs for evaluating RAG chatbots last year. ### Problems Ragas Can Solve: - How can you select the best components for your RAG, such as the retriever, reranker, and LLM? - How can you create a test dataset without incurring significant expenses and time? We believe there's a need…
2024 · github.com · its alternatives →
23SA
ShapedQL – A SQL engine for multi-stage ranking and RAG▲80
Hi HN, I’m Tullie, founder of Shaped. Previously, I was a researcher at Meta AI, worked on ranking for Instagram Reels, and was a contributor to PyTorch Lightning. We built ShapedQL because we noticed that while retrieval (finding 1,000 items) has been commoditized by vector DBs, ranking (finding the best 10 items) is still an infrastructure problem. To build a decent for you feed or a RAG system with long-term memory, you usually have to put together a vector DB (Pinecone/Milvus), a feature store (Redis), an inference service, and thousands of lines of Python to handle business logic…
Jan 2026 · playground.shaped.ai · its alternatives →
24
Using LLMs and Embeddings to classify application errors▲65
Hi Hacker News! We’re Vadim and Chris from Highlight.io [1]. We do web app monitoring and are working on using LLMs/embeddings to add new functionality to our error monitoring product. Given that there’s a lot of founders/engineers using LLMs in their products, we figured we’d share how we built the new functionality, their impact on our workflows, and how you can try it out. Our goal was to build two features: (1) tagging errors (e.g. deeming an error as “authentication error” or a “database error”); and (2) grouping similar errors together (e.g. two errors that have a different…
2023 · github.com · its alternatives →

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