Graphlit is a cloud-native, API-first platform designed to aid developers in constructing knowledge-driven AI applications. Leveraging LLMs and multimodal AI, Graphlit enables efficient knowledge extraction from multimedia content, accelerating domain-specific application development. Accessible via a GraphQL API, Graphlit finds relationships between people, organizations, places, and topics located in unstructured data, providing capabilities to search, summarize, and repurpose that knowledge.
External link for Graphlit, by Unstruk Data
Graphlit is a cloud-native, API-first platform designed to aid developers in constructing knowledge-driven AI applications. Leveraging LLMs and multimodal AI, Graphlit enables efficient knowledge extraction from multimedia content, accelerating domain-specific application development. Accessible via a GraphQL API, Graphlit finds relationships between people, organizations, places, and topics located in unstructured data, providing capabilities to search, summarize, and repurpose that knowledge.
Seattle, WA, US
Graphlit, by Unstruk Data reposted this
I had an excellent time meeting folks at our booth at AIQCon, and got a warm reception to my talk on GraphRAG. Sharing the slides here, and welcome anyone interested in #graphrag to try out the Graphlit Platform and our demo apps Website: https://www.graphlit.com Sample apps: https://lnkd.in/gFgEw9zz
Graphlit, by Unstruk Data reposted this
If you are considering attending the AI Quality Conference in SF, but haven’t gotten your ticket yet, please let me know. I’ll be speaking about GraphRAG and Graphlit, by Unstruk Data, and have some complimentary tickets available. https://lnkd.in/gas2UsZw
Graphlit, by Unstruk Data reposted this
Graphlit, made simple. Try our new native Python SDK today. Code: https://lnkd.in/gqjZjVw4 Docs: https://lnkd.in/gmpBXQyv
Graphlit, by Unstruk Data reposted this
Was such a pleasure to be on the TWiML podcast with Sam Charrington. Been an avid listener for years. Have a listen to our discussion about RAG, GraphRAG, and how we developed this in our Graphlit platform.
Today we're joined by Kirk Marple, CEO and founder of Graphlit, by Unstruk Data, to explore the emerging paradigm of "GraphRAG". Kirk shares the history of RAG, and the potential for deeper integration of databases and AI as RAG matures. We dive into Graphlit's multi-stage workflow for content generation and finally, explore agent-based applications and the future of Graphlit as a cloud service. 🎧 / 🎥 Listen or watch the full episode at: twimlai.com/go/681
🔉 GPT-to-Audio: Using LLMs to generate first-person scripts, which can be converted to audio with TTS models from ElevenLabs, makes content more consumable by end-users. 🔥 In the latest release of Graphlit, by Unstruk Data, Slack audio and text alerts are now supported for AI app devs. See our changelog: https://lnkd.in/gkJ_PuWA And our API documentation: https://lnkd.in/gn9ZzMiY
Simply by using GPT-4 Vision to analyze images, you can publish a written inspection report with LLMs. Read about how developers can use Graphlit, by Unstruk Data to build AI apps for visual inspections. https://lnkd.in/g2ZpifUv
Quickly extract structured data, such as postal addresses, from unstructured web pages with Graphlit, by Unstruk Data. Easy to integrate into your applications with one API call to extract structured data from multiple pieces of content at once: web pages, PDFs, audio transcripts and more. Learn more in our new blog post: https://lnkd.in/gmpvqe9w #unstructureddata #dataextraction #gpt4 #json
The knowledge locked in podcasts was a driving force behind creating Graphlit, by Unstruk Data. We have a new blog post which is a deep dive into using LLMs for podcast summarization, and creating conversational chatbots for podcast listeners. https://lnkd.in/gkYrurgx Thanks to Daniel O'Donohue for allowing us to use his MapScaping podcast for this blog post. #openai #chatbot #podcasting #knowledgegraph
We've been working on exciting new techniques for content repurposing in Graphlit, by Unstruk Data. Our first new feature is Auto-Suggestion of LLM Prompts. We have a new blog post that walks through creating a web feed to ingest a set of OpenAI blog pages, and then use an LLM to auto-suggest potential prompts, in order to extract more value out of long-form content. Next on our list is the creation of long-form content, like an SEO-friendly blog post - from a filtered set of multimedia content: PDFs, web pages, audio transcripts, etc. Any other use cases you're looking for, when prompting large sets of multimedia content? https://lnkd.in/gaG9BeHH
As the holiday season approaches, Graphlit has a present 🎁 for you. 💡Graphlit is offering a $100 usage credit against our paid tiers, as well as a complementary 60min call to help you leverage advances in Large Language Models (LLMs), how to build AI copilots, or to review your unstructured data workflows. For anyone exploring or building AI copilots with their data - PDFs, audio, Notion pages, Slack messages or web content - Graphlit makes it easy, with no assembly required. 🗣️ Feel free to setup your time to chat: https://lnkd.in/g4wgjbWk 👋 If anyone in your network is interested in using LLMs or the new multimodal vision models to build knowledge-driven applications, we'd appreciate you sharing this offer with them. More about Graphlit: https://www.graphlit.com