Search: “pinecone--x”

Knowledge is rather abstract and philosophical. So what does it mean from an agentic context? How does providing the right knowledge at the right time to an agent increase its accuracy, task completio

Next Tuesday, August 11, we're hosting the August LA Agentic AI Meetup, 5 to 7pm at Gulp in Playa Vista. May drew 70 people. July brought 80. Let's break 100 in August. Come hang out with builders, en

Decoupling embedding from ingestion means whatever hardware is on hand can do the work. One script, runtime device check: MPS on Apple Silicon, CUDA on NVIDIA, CPU fallback otherwise. 10K-20K records

We're hosting the August LA Agentic AI Meetup on Tuesday, August 11, 5 to 7pm at Gulp in Playa Vista. May drew 70 people. July brought 80. Let's break 100 in August. Come hang out with builders, engin

Your coding agent doesn't need to leave the terminal to use Pinecone. We now ship official plugins and skills for the agentic IDEs and CLIs you are already building in: Claude Code, Cursor, GitHub Cop

Pinecone has introduced Nexus, a knowledge engine built specifically for AI agents. Instead of repeatedly searching documents with traditional RAG, Nexus compiles knowledge once from sources like data

Sparse index posting data: BM25 exact matches, SPLADE transformer-expanded matches. Storage layout just changed from document-range blocks to term blocks. A query now loads only the blocks for the ter

New test data pipeline for Pinecone: CC News dataset, chunked, embedded with BAAI/bge-large-en-v1.5 (1024-dim), landed as Parquet. Past a few million vectors, embedding inline bottlenecks the pipeline

We're hosting the LA Agentic AI Meetup this Thursday, July 9, 5 to 7pm at Gulp in Playa Vista. Come talk to engineers, founders, and builders working across RAG, agentic workflows, and the broader AI

Pinecone has released Nexus, a new product in public preview designed to enable AI agents to access and leverage business knowledge more effectively. Nexus appears to be a solution that integrates wit

This X Spaces broadcast from Pinecone invites developers to join a live discussion about building applications and solutions using Pinecone's vector database platform. The session likely covers use ca

Jeff Zhu (VP of Product) and Jasmeet Singh Gujral (Principal PM) join @jennapederson and Arjun Patel on the livestream today to talk about what we've shipped and what's coming. Then we get into the us

Our Founder and Chief Scientist @EdoLiberty just kicked off the Search & Retrieval track @aiDotEngineer. 'Agents don't need to be smarter. They need a Knowledge Layer.' We've got a big update on this

Building Agent Skills is great, but testing them clearly and across agents is difficult. The Pinecone DevRel team has released Cultivar, a CLI tool and agent skill designed to solve this problem. With

Pinecone shared a GitHub repository called 'cultivar' and requested community feedback on the project. The post appears to be a call-for-comment on a new tool or resource developed by Pinecone, likely

ZoomInfo rebuilt contact discovery as real-time recommendation, now running on Pinecone DRN: 50x peak requests, 2x recall, 50% more engagement. Join engineers from Pinecone and ZoomInof as they discus

Managed SaaS needs vendor access security review won't approve. Self-hosted hands your team a vector database to run. Pinecone BYOC runs the data plane inside your own AWS, GCP, or Azure account. Zero

Most AI agents reset every session. @JenovaAIAgent's don't. Longest session on their platform: 16M tokens. All of it retrievable in <10ms via Pinecone vector retrieval. Result: Fast ramp to $1M+ ARR,

Proud to have Pinecone Nexus be a part of this along with our friends at @LangChain, @tavilyai, and @guardrails_ai! Most #AIAgents don't fail because of the model. They fail because of the infrastruct

Nebius AI announced the Agents Blueprint, a framework integrating multiple tools including LangChain Deep Agents, Tavily AI, Pinecone for vector storage, and Guardrails for building AI agents. This bl

This article from Apify's blog covers the process of training AI chatbots, likely including techniques for data preparation, model selection, and fine-tuning approaches. The content is shared by Pinec

Four weeks, three enterprise customers, same pattern across all three. Most inference spend goes to retrieval loops. A generic index carries no knowledge of domain, query types, or task structure, so

Your AI chatbot is only as good as the data behind it. This n8n template from our friends at @apify shows you how to wire up a RAG pipeline using Apify + Pinecone + Gemini so your chatbot can answer q

Bulk import is now free up to 1 TB. Reads directly from S3, GCS, or Azure Blob into the index builder. Standard and Enterprise get a 250 credit applied automatically. After 1 TB: 0.25/GB, down 75%. ht

95% token reduction. 30x faster execution. 90%+ task completion. Today at #MSBuild, we announced a major shift to move reasoning upstream: Pinecone Nexus now integrates directly with @Microsoft OneLak

Today at Microsoft Build: Pinecone Nexus now integrates with Microsoft OneLake. Your enterprise data, turned into task-scoped, governed, cited knowledge your agents can use directly. 95%+ token reduct

We just announced the integration of our knowledge engine, Pinecone Nexus, with @Microsoft OneLake at #MSBuild. Want to build a reliable, production-grade knowledge layer directly over your structured

Data agents don't fail at writing SQL. They fail at knowing your business. Schemas show you the columns, but they don't tell you which view is canonical for ARR, how often each metric updates, or whic

Connecting agents directly to Snowflake, Slack, or BigQuery via MCP/CLIs is a multi-token disaster. They default to brute-force exploration, firing 20-30 tool calls just to rediscover context on every

You can’t build an autonomous agent on a static RAG pipeline. Because goals mutate dynamically, agents require an advanced knowledge infrastructure, rather than forcing the model to hunt through a raw

Ralph Loops are powerful, but wrapping a naive loop in a shell script is a total token burner in production. Pinecone Principal Engineer Jen Hamon breaks down why standard loops collapse: ❌ The Bug: P

We're hosting an agentic AI meetup in LA on May 28th — 5–7pm at Gulp in Playa Vista. Builders, founders, engineers. Drinks, no fluff. RAG systems, agentic workflows, or just starting out — all welcome

Pinecone has updated its integration with Datadog to include expanded metrics and improved dashboards, enabling better monitoring and visualization of Pinecone vector database performance within the D

Pinecone hosted a live broadcast on X (formerly Twitter) inviting developers to build applications using their vector database platform. The broadcast likely covered Pinecone's capabilities for AI and

ICYMI Dedicated Read Nodes are now generally available. Predictable performance at scale. Up to 97% lower costs on real production workloads. Fixed hourly pricing. No read rate limits. Always-hot data

The official Pinecone plugin for @cursor_ai has been released! To install, run /add-plugin pinecone within Cursor. What you get: Agent Skills and scripts to help you build with our vector database and

Reasoning is becoming commoditized. The uniqueness of your knowledge is your real advantage. Check out our Head of Developer Relations @RoieSchwabco on @TheEntAIShow with @bgracely: 📺 https://www.yout

Recently @pinecone introduced Nexus – a new knowledge-engine layer for AI agents that reduces token use by up to 90%. It’s built on top of a vector database, but shifts reasoning earlier in the pipeli

built a bird search app to show off pinecone's full text search capabilities 2,079 bird articles, full-text keyword search, Gemini Embedding 2 for cross-modal visual search. the birds did not consent

This repository demonstrates a search application built using Pinecone's vector database, likely showcasing how to implement semantic search or similarity-based retrieval using bird-related data or im

$20/month. Builder: Pinecone's new plan for teams that have outgrown the free tier but aren't running production workloads at scale yet. The prototype-to-production gap has always been an awkward plac

A beginner-friendly guide to building a simple RAG (RETRIEVAL-AUGMENTED GENERATION) AI Agent with Pinecone + n8n 🧵 If you’re learning AI automation and you’re confused about Pinecone, knowledge bases,

Sign up if you're in LA! The last AI Agents Happy Hour was so fun, @jvedi and I are going to do it again. This time, co-hosted by @pinecone! We want to see what you're building and learn from your exp

Our internal AI agent was a brute-force nightmare. 🛑 It burned 40,000 tokens, took 2 minutes, and only hit 68% accuracy just to answer a single question. Why? Traditional databases are built for human

Pinecone has launched its first serverless cloud region in Singapore and rolled out Nexus, KnowQL, a Marketplace and a USD $20 Builder tier. #CloudComputing #Singapore #Serverless #AI https://techday.

Pinecone has launched two new regional endpoints for its vector database service: AWS eu-central-1 in Germany and AWS ap-southeast-1 in Singapore. These new regions enable users in Europe and Southeas