kirkmarple
Context Is the Missing Layer AI Agents Need
Show HN: I built a SaaS in 8 weeks, solo, using our own AI platform
https://www.zine.ai/blog/how-i-built-zine-in-3-months-with-ai-coding
I spent 8 weeks building Zine, an AI-powered search app for your team's knowledge, entirely solo. No team, no extra funding. Just me, AI coding tools, and the platform I had already built.Instead of building infrastructure (connectors, vector DBs, transcription, entity extraction, etc.), I reused Graphlit, the same stack our customers use. That saved about 4-5 months of backend work and let me...
Re:Show HN: McPoogle: Search Engine for MCP Servers
on Monday May 05, 2025 @11:20PM (#43901532)
We'll release an MCP server/tool for it, shortly, which anybody can install and use.
If anyone needs a REST API or something else around it, they should reach out on our Discord.
We've been doing some structured JSON extraction as well to build MCP server "cards" for better display in IDEs - and using imagegen to create visual "cards", if desired.
Show HN: McPoogle: Search Engine for MCP Servers
With all the MCP servers coming to AI IDEs like Cline, Windsurf, Cursor and VS Code, we realized that their MCP search sucks.So, we built a free MCP search engine using our Graphlit Knowledge platform, where you can ask about 4000+ MCP servers and tools, with LLMs from Groq, Anthropic, OpenAI and Google Gemini.McPoogle MCP Server coming soon, so you can search within your favorite IDE.
Re:
on Monday March 03, 2025 @03:48PM (#43246511)
We are excited to launch our MCP (Model Context Protocol) Server for Graphlit! It provides powerful new capabilities for content ingestion and retrieval to MCP clients like Claude Desktop, Goose, Cline, Cursor, and Windsurf.
Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Documents (PDF, DOCX, PPTX, etc.) and HTML web pages will be extracted to Markdown upon ingestion. Audio and video files will be transcribed upon ingestion.
The Graphlit MCP Server is open-source, and provides an interface between the Graphlit Platform API, and MCP clients.
By integrating the Graphlit Platform with MCP, we can now provide LLM-enabled, agentic workflows inside any MCP-compatible client.
Show HN: Multimodal PDF extraction using Sonnet 3.5/GPT-4o
https://github.com/graphlit/graphlit-samples/tree/main/dotnet/GraphlitIngest
Using the new graphlit-ingest CLI, you can ingest any document, audio/video, image or web page, and extract Markdown text or structured JSON. Also, supports summarization and auto-generated transcript chapters, bullet points, social media posts and more.Supports Anthropic Sonnet 3.5 and OpenAI GPT-4o for multimodal PDF extraction.Free to use, up to 1GB data.Built with our new cross-platform...
Re:
on Tuesday May 21, 2024 @03:25AM (#40425177)
Learn how to extract a knowledge graph from your content, using LLMs, and enrich entities with Wikipedia.
Use the KG to provide greater context to your RAG pipeline, with GraphRAG.
Code: https://github.com/graphlit/graphlit-samples/tree/main/pytho... Demo: graphlit-samples-sharepoint-graph.streamlit.app
Show HN: Audio summarized from Reddit posts, using ElevenLabs and GPT-4 Turbo
https://drive.google.com/file/d/10K8PPaCaxXnhEisrY1FF5xvr3ohHu2cD/view?usp=sharing
You can create an automated audio summary like this one - on any topic, from any data source(s) with Graphlit (https://www.graphlit.com).I ingested Reddit posts from r/Azure, with entity extraction, and filtered just on posts that were tagged with SharePoint.Then, with a custom publishing prompt, I had GPT-4 Turbo write a script for ElevenLabs, and posted it to a Slack channel.With just a few...
Re:
on Tuesday January 23, 2024 @11:08PM (#39113512)
I've been exploring the hybrid of multimodal models like GPT-4 Vision for image analysis, and GPT-4 Turbo for generating written content based on those image descriptions.
Here we're showing a use case for building a tool with Graphlit for apartment managers, and generating an instant inspection report purely from uploaded images.
Re:Show HN: Auto-Suggest LLM Prompts, with Graphlit and Azure OpenAI
on Tuesday November 28, 2023 @05:01AM (#38444198)
When creating a chatbot or AI copilot, which supports Q&A across ingested content, a common user problem can be knowing where to start asking questions.
Show HN: Auto-Suggest LLM Prompts, with Graphlit and Azure OpenAI
Show HN: Model-agnostic text summarization with Anthropic and OpenAI LLMs
https://www.graphlit.com/blog/model-agnostic-summarization
With OpenAI being unsettled this week, we compared the newly released Anthropic Claude 2.1 with Claude 2.0, and OpenAI GPT-3/4 LLMs, for model-agnostic text summarization.
Show HN: Using Multimodal RAG and OpenAI GPT-4 Vision for Insurance Industry
https://www.graphlit.com/blog/multimodal-rag-insurance-insights
With OpenAI's release of their GPT-4 Vision model, it has opened up the ability to analyze visual content (images and videos) and gather insights, which was previously not possible with existing Large Language Models (LLMs).We walkthrough how to build an image analysis pipeline and AI copilot for insurance companies with Graphlit, with just a few API calls, and no AI experience required.
Re:Ask HN: What is the most promising AI tool in cloud ecosystem?
on Monday October 30, 2023 @03:07AM (#38066492)
Have a look at Graphlit (https://www.graphlit.com). Managed cloud-native platform for knowledge ingestion and retrieval. Simple GraphQL API, and serverless backend to handle all the data ingestion, embeddings, and RAG LLM patterns. Free tier to try out without CC. (Disclaimer: I'm the founder)
Re:Show HN: Build Market Intelligence Apps with Graphlit, Reddit and A...
on Wednesday October 25, 2023 @03:55AM (#38010362)
With the use of Graphlit and Azure AI, market intelligence from Reddit can be automated - accelerating the time to business insights.
This tutorial walks through ingesting Reddit posts into Graphlit by creating a Reddit feed, along with a content workflow. The workflow describes how the content will be ingested, prepared, extracted and enriched into the Graphlit knowledge graph.
When all content has been ingested, you can analyze the observed entities that Azure AI found in the Reddit posts, and extract structured data via faceted queries for charting and analysis.