⏰ Reminder: Qdrant Office Hours - in 2 days!
🗓️ 18th December
⏰ 9:30 PM IST | 9:00 AM PST | 5:00 PM CET
Speakers:
- Kumar Shivendu - Qdrant v1.16 update
- Clelia Astra Bertelli - StudyLlama updates
Link to the event: discord.com/events/90756...
#Qdrant #VectorSearch #Discord #AIInfrastructure #LLM
🗓️ 18th December
⏰ 9:30 PM IST | 9:00 AM PST | 5:00 PM CET
Speakers:
- Kumar Shivendu - Qdrant v1.16 update
- Clelia Astra Bertelli - StudyLlama updates
Link to the event: discord.com/events/90756...
#Qdrant #VectorSearch #Discord #AIInfrastructure #LLM
December 15, 2025 at 7:29 PM
⏰ Reminder: Qdrant Office Hours - in 2 days!
🗓️ 18th December
⏰ 9:30 PM IST | 9:00 AM PST | 5:00 PM CET
Speakers:
- Kumar Shivendu - Qdrant v1.16 update
- Clelia Astra Bertelli - StudyLlama updates
Link to the event: discord.com/events/90756...
#Qdrant #VectorSearch #Discord #AIInfrastructure #LLM
🗓️ 18th December
⏰ 9:30 PM IST | 9:00 AM PST | 5:00 PM CET
Speakers:
- Kumar Shivendu - Qdrant v1.16 update
- Clelia Astra Bertelli - StudyLlama updates
Link to the event: discord.com/events/90756...
#Qdrant #VectorSearch #Discord #AIInfrastructure #LLM
Get started on the Qdrant Essentials Course and get your Qdrant Certification here: qdrant.tech/course/essen...
What would do want to see in an Qdrant Course? Let us know in the comments!
What would do want to see in an Qdrant Course? Let us know in the comments!
December 12, 2025 at 5:50 PM
Get started on the Qdrant Essentials Course and get your Qdrant Certification here: qdrant.tech/course/essen...
What would do want to see in an Qdrant Course? Let us know in the comments!
What would do want to see in an Qdrant Course? Let us know in the comments!
Qdrant’s ACORN fixes the “zero results” problem in filtered vector search.
Smarter second-hop exploration = higher recall under strict filters.
Shared by our star NiranjanAkella 🔥
Link: blog.stackademic.com/zero-results...
Smarter second-hop exploration = higher recall under strict filters.
Shared by our star NiranjanAkella 🔥
Link: blog.stackademic.com/zero-results...
December 11, 2025 at 4:42 AM
Qdrant’s ACORN fixes the “zero results” problem in filtered vector search.
Smarter second-hop exploration = higher recall under strict filters.
Shared by our star NiranjanAkella 🔥
Link: blog.stackademic.com/zero-results...
Smarter second-hop exploration = higher recall under strict filters.
Shared by our star NiranjanAkella 🔥
Link: blog.stackademic.com/zero-results...
𝐊𝐲𝐥𝐢𝐞 - 𝐚 𝐦𝐮𝐥𝐭𝐢𝐦𝐨𝐝𝐚𝐥 𝐖𝐡𝐚𝐭𝐬𝐀𝐩𝐩 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭
Spotted this cool project by Jonathan Mukhobe Sr.
Kylie handles text, images, voice, tasks, search, and more - built with LangGraph + Groq.
🧠 Powered by Qdrant + MiniLM for long-term memory.
Check it out: github.com/jonathanmuk/...
Spotted this cool project by Jonathan Mukhobe Sr.
Kylie handles text, images, voice, tasks, search, and more - built with LangGraph + Groq.
🧠 Powered by Qdrant + MiniLM for long-term memory.
Check it out: github.com/jonathanmuk/...
December 7, 2025 at 9:38 AM
𝐊𝐲𝐥𝐢𝐞 - 𝐚 𝐦𝐮𝐥𝐭𝐢𝐦𝐨𝐝𝐚𝐥 𝐖𝐡𝐚𝐭𝐬𝐀𝐩𝐩 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭
Spotted this cool project by Jonathan Mukhobe Sr.
Kylie handles text, images, voice, tasks, search, and more - built with LangGraph + Groq.
🧠 Powered by Qdrant + MiniLM for long-term memory.
Check it out: github.com/jonathanmuk/...
Spotted this cool project by Jonathan Mukhobe Sr.
Kylie handles text, images, voice, tasks, search, and more - built with LangGraph + Groq.
🧠 Powered by Qdrant + MiniLM for long-term memory.
Check it out: github.com/jonathanmuk/...
Multimodal Fashion Search with Qdrant + ScrapeGraphAI 👗⚡️
Francesco Zuppichini and our Head of DevRel Neil Kanungo just shared a slick walkthrough on building a multimodal clothing search engine using ScrapeGraphAI + CLIP + Qdrant.
Full demo + write-up:
🔗 scrapegraphai.com/blog/scrapin...
Francesco Zuppichini and our Head of DevRel Neil Kanungo just shared a slick walkthrough on building a multimodal clothing search engine using ScrapeGraphAI + CLIP + Qdrant.
Full demo + write-up:
🔗 scrapegraphai.com/blog/scrapin...
December 2, 2025 at 7:45 AM
Multimodal Fashion Search with Qdrant + ScrapeGraphAI 👗⚡️
Francesco Zuppichini and our Head of DevRel Neil Kanungo just shared a slick walkthrough on building a multimodal clothing search engine using ScrapeGraphAI + CLIP + Qdrant.
Full demo + write-up:
🔗 scrapegraphai.com/blog/scrapin...
Francesco Zuppichini and our Head of DevRel Neil Kanungo just shared a slick walkthrough on building a multimodal clothing search engine using ScrapeGraphAI + CLIP + Qdrant.
Full demo + write-up:
🔗 scrapegraphai.com/blog/scrapin...
Vector search is booming - and it’s powering accurate RAG and smarter AI apps.
SE Radio’s new episode with Kacper Łukawski breaks down:
⚡ When to use embeddings
⚡ Real-world architectures
⚡ Lessons from scaling search
⚡ Why teams choose Qdrant
🎧 Listen: se-radio.net/2025/10/se-r...
SE Radio’s new episode with Kacper Łukawski breaks down:
⚡ When to use embeddings
⚡ Real-world architectures
⚡ Lessons from scaling search
⚡ Why teams choose Qdrant
🎧 Listen: se-radio.net/2025/10/se-r...
November 27, 2025 at 4:52 PM
Vector search is booming - and it’s powering accurate RAG and smarter AI apps.
SE Radio’s new episode with Kacper Łukawski breaks down:
⚡ When to use embeddings
⚡ Real-world architectures
⚡ Lessons from scaling search
⚡ Why teams choose Qdrant
🎧 Listen: se-radio.net/2025/10/se-r...
SE Radio’s new episode with Kacper Łukawski breaks down:
⚡ When to use embeddings
⚡ Real-world architectures
⚡ Lessons from scaling search
⚡ Why teams choose Qdrant
🎧 Listen: se-radio.net/2025/10/se-r...
Loved this project by M K Pavan Kumar - an AI-driven load-testing agent that runs tests, interprets results, and recalls past runs using Qdrant as its vector memory.
A clean example of how semantic search can level up performance engineering.
Read: 👉 towardsdev.com/designing-a-...
A clean example of how semantic search can level up performance engineering.
Read: 👉 towardsdev.com/designing-a-...
November 23, 2025 at 6:03 AM
Loved this project by M K Pavan Kumar - an AI-driven load-testing agent that runs tests, interprets results, and recalls past runs using Qdrant as its vector memory.
A clean example of how semantic search can level up performance engineering.
Read: 👉 towardsdev.com/designing-a-...
A clean example of how semantic search can level up performance engineering.
Read: 👉 towardsdev.com/designing-a-...
Cosmos built an editorial-grade visual search engine on Qdrant Cloud - blending text, color, and hybrid queries in under 500 ms. Art meets engineering.
🔗 qdrant.tech/blog/case-st...
🔗 qdrant.tech/blog/case-st...
November 21, 2025 at 9:35 AM
Cosmos built an editorial-grade visual search engine on Qdrant Cloud - blending text, color, and hybrid queries in under 500 ms. Art meets engineering.
🔗 qdrant.tech/blog/case-st...
🔗 qdrant.tech/blog/case-st...
Qdrant 1.16 is out! 🎉
It brings tiered multitenancy, smarter filtered search with ACORN, faster disk-based HNSW via inline storage, better full-text search, safer conditional updates, and a refreshed Web UI.
Read the full release overview to dive deeper: github.com/qdrant/qdran...
It brings tiered multitenancy, smarter filtered search with ACORN, faster disk-based HNSW via inline storage, better full-text search, safer conditional updates, and a refreshed Web UI.
Read the full release overview to dive deeper: github.com/qdrant/qdran...
November 19, 2025 at 7:45 AM
Qdrant 1.16 is out! 🎉
It brings tiered multitenancy, smarter filtered search with ACORN, faster disk-based HNSW via inline storage, better full-text search, safer conditional updates, and a refreshed Web UI.
Read the full release overview to dive deeper: github.com/qdrant/qdran...
It brings tiered multitenancy, smarter filtered search with ACORN, faster disk-based HNSW via inline storage, better full-text search, safer conditional updates, and a refreshed Web UI.
Read the full release overview to dive deeper: github.com/qdrant/qdran...
Xaver used a two-tier AI engine on Qdrant to cut latency by 2–3 seconds and deliver sub-second answers - letting their team focus on better advisory experiences, not infra.
Full story: qdrant.tech/blog/case-st...
Full story: qdrant.tech/blog/case-st...
November 14, 2025 at 8:56 AM
Xaver used a two-tier AI engine on Qdrant to cut latency by 2–3 seconds and deliver sub-second answers - letting their team focus on better advisory experiences, not infra.
Full story: qdrant.tech/blog/case-st...
Full story: qdrant.tech/blog/case-st...
An AI HR Assistant that finds the perfect opportunities from “Python dev (FinTech)” to “AI intern.” 🌌
Built by Chetan Kumar using Next.js, FastAPI, LangChain, OpenAI & Qdrant.
🎥 Demo: www.loom.com/share/257ed8...
Built by Chetan Kumar using Next.js, FastAPI, LangChain, OpenAI & Qdrant.
🎥 Demo: www.loom.com/share/257ed8...
November 13, 2025 at 4:40 PM
An AI HR Assistant that finds the perfect opportunities from “Python dev (FinTech)” to “AI intern.” 🌌
Built by Chetan Kumar using Next.js, FastAPI, LangChain, OpenAI & Qdrant.
🎥 Demo: www.loom.com/share/257ed8...
Built by Chetan Kumar using Next.js, FastAPI, LangChain, OpenAI & Qdrant.
🎥 Demo: www.loom.com/share/257ed8...
Quantization isn’t a trade-off anymore, it’s a must for scalable AI.
Niranjan Akella breaks down how Qdrant’s 1.5-bit Quantization kills the Float32 tax with 24× compression, no recall loss, and sub-40 ms latency, all powered by Rust for real-time performance.
Read more: qdrant.tech/documentatio...
Niranjan Akella breaks down how Qdrant’s 1.5-bit Quantization kills the Float32 tax with 24× compression, no recall loss, and sub-40 ms latency, all powered by Rust for real-time performance.
Read more: qdrant.tech/documentatio...
November 12, 2025 at 8:53 AM
Quantization isn’t a trade-off anymore, it’s a must for scalable AI.
Niranjan Akella breaks down how Qdrant’s 1.5-bit Quantization kills the Float32 tax with 24× compression, no recall loss, and sub-40 ms latency, all powered by Rust for real-time performance.
Read more: qdrant.tech/documentatio...
Niranjan Akella breaks down how Qdrant’s 1.5-bit Quantization kills the Float32 tax with 24× compression, no recall loss, and sub-40 ms latency, all powered by Rust for real-time performance.
Read more: qdrant.tech/documentatio...
Powering next-gen e-commerce recommendations with hybrid sparse + dense vectors in Qdrant
Sayanteka Chakraborty shares how combining keyword + semantic search boosted relevance and speed
⚡ 3× faster recs
📈 30–40% higher engagement
Hybrid search = smarter personalization
Read more: t.co/dlVzDhdc1o
Sayanteka Chakraborty shares how combining keyword + semantic search boosted relevance and speed
⚡ 3× faster recs
📈 30–40% higher engagement
Hybrid search = smarter personalization
Read more: t.co/dlVzDhdc1o
November 11, 2025 at 6:22 PM
Powering next-gen e-commerce recommendations with hybrid sparse + dense vectors in Qdrant
Sayanteka Chakraborty shares how combining keyword + semantic search boosted relevance and speed
⚡ 3× faster recs
📈 30–40% higher engagement
Hybrid search = smarter personalization
Read more: t.co/dlVzDhdc1o
Sayanteka Chakraborty shares how combining keyword + semantic search boosted relevance and speed
⚡ 3× faster recs
📈 30–40% higher engagement
Hybrid search = smarter personalization
Read more: t.co/dlVzDhdc1o
🧩 Community highlight: Matthieu Nicolescu built a fully self-hosted, cloud-native RAG stack using Qdrant, KServe, and Envoy AI Gateway - all on Kubernetes, no external APIs.
A great blueprint for scalable, data-sovereign AI pipelines.
Check here: medium.com/h7w/cloud-na...
A great blueprint for scalable, data-sovereign AI pipelines.
Check here: medium.com/h7w/cloud-na...
November 6, 2025 at 7:46 AM
🧩 Community highlight: Matthieu Nicolescu built a fully self-hosted, cloud-native RAG stack using Qdrant, KServe, and Envoy AI Gateway - all on Kubernetes, no external APIs.
A great blueprint for scalable, data-sovereign AI pipelines.
Check here: medium.com/h7w/cloud-na...
A great blueprint for scalable, data-sovereign AI pipelines.
Check here: medium.com/h7w/cloud-na...
🗞️ The October Qdrant Newsletter is live!
🚀 Highlights:
• Launch of Qdrant Academy & “Essentials” course
• New tools, tutorials & integrations
• Community projects & ecosystem growth
👉 Read: try.qdrant.tech/october-news...
📩 Subscribe: qdrant.tech/subscribe
#Qdrant #VectorSearch #AI #OpenSource
🚀 Highlights:
• Launch of Qdrant Academy & “Essentials” course
• New tools, tutorials & integrations
• Community projects & ecosystem growth
👉 Read: try.qdrant.tech/october-news...
📩 Subscribe: qdrant.tech/subscribe
#Qdrant #VectorSearch #AI #OpenSource
November 4, 2025 at 4:56 PM
🗞️ The October Qdrant Newsletter is live!
🚀 Highlights:
• Launch of Qdrant Academy & “Essentials” course
• New tools, tutorials & integrations
• Community projects & ecosystem growth
👉 Read: try.qdrant.tech/october-news...
📩 Subscribe: qdrant.tech/subscribe
#Qdrant #VectorSearch #AI #OpenSource
🚀 Highlights:
• Launch of Qdrant Academy & “Essentials” course
• New tools, tutorials & integrations
• Community projects & ecosystem growth
👉 Read: try.qdrant.tech/october-news...
📩 Subscribe: qdrant.tech/subscribe
#Qdrant #VectorSearch #AI #OpenSource
📅 Nov 12, 6 PM CET - Join Dat Daryl Ngo (Arize AI) to explore how to make Agentic RAG systems observable, accountable & self-improving with open-source tools and real-world insights.
👉 Register here:
#AI #RAG #Observability #ArizeAI
👉 Register here:
#AI #RAG #Observability #ArizeAI
November 4, 2025 at 4:55 PM
📅 Nov 12, 6 PM CET - Join Dat Daryl Ngo (Arize AI) to explore how to make Agentic RAG systems observable, accountable & self-improving with open-source tools and real-world insights.
👉 Register here:
#AI #RAG #Observability #ArizeAI
👉 Register here:
#AI #RAG #Observability #ArizeAI
Exciting news from our partner @confluent.io!
Confluent’s new Streaming Agents and Real-Time Context Engine bring live context to AI agents and enterprise apps.
Together, Qdrant × Confluent enable developers to build real-time, AI powered by streaming data and vector search.
👉 t.co/DurLLwYMXO
Confluent’s new Streaming Agents and Real-Time Context Engine bring live context to AI agents and enterprise apps.
Together, Qdrant × Confluent enable developers to build real-time, AI powered by streaming data and vector search.
👉 t.co/DurLLwYMXO
October 30, 2025 at 7:11 PM
Exciting news from our partner @confluent.io!
Confluent’s new Streaming Agents and Real-Time Context Engine bring live context to AI agents and enterprise apps.
Together, Qdrant × Confluent enable developers to build real-time, AI powered by streaming data and vector search.
👉 t.co/DurLLwYMXO
Confluent’s new Streaming Agents and Real-Time Context Engine bring live context to AI agents and enterprise apps.
Together, Qdrant × Confluent enable developers to build real-time, AI powered by streaming data and vector search.
👉 t.co/DurLLwYMXO
Qdrant joins the AI-Powered Search course as a guest lecturer!
Our @mrscoopers.bsky.social will speak on “Mixing Sparse & Dense Representations” in Week 2 of Modern Retrieval for Humans and Agents by Trey Grainger and Doug Turnbull.
🔗 Details: aipoweredsearch.com/articles/ai-...
Our @mrscoopers.bsky.social will speak on “Mixing Sparse & Dense Representations” in Week 2 of Modern Retrieval for Humans and Agents by Trey Grainger and Doug Turnbull.
🔗 Details: aipoweredsearch.com/articles/ai-...
October 29, 2025 at 12:33 PM
Qdrant joins the AI-Powered Search course as a guest lecturer!
Our @mrscoopers.bsky.social will speak on “Mixing Sparse & Dense Representations” in Week 2 of Modern Retrieval for Humans and Agents by Trey Grainger and Doug Turnbull.
🔗 Details: aipoweredsearch.com/articles/ai-...
Our @mrscoopers.bsky.social will speak on “Mixing Sparse & Dense Representations” in Week 2 of Modern Retrieval for Humans and Agents by Trey Grainger and Doug Turnbull.
🔗 Details: aipoweredsearch.com/articles/ai-...
🫶 Big thanks to everyone who joined Qdrant’s Discord Office Hours!
Loved the energy, ideas, and stories - and special thanks to Brian, Joshua, Clelia, and Tarun for the great insights.
See you next month for more tech, chats, and demos! 💬
Loved the energy, ideas, and stories - and special thanks to Brian, Joshua, Clelia, and Tarun for the great insights.
See you next month for more tech, chats, and demos! 💬
October 17, 2025 at 9:37 AM
🫶 Big thanks to everyone who joined Qdrant’s Discord Office Hours!
Loved the energy, ideas, and stories - and special thanks to Brian, Joshua, Clelia, and Tarun for the great insights.
See you next month for more tech, chats, and demos! 💬
Loved the energy, ideas, and stories - and special thanks to Brian, Joshua, Clelia, and Tarun for the great insights.
See you next month for more tech, chats, and demos! 💬
An open source engineer from @llamaindex.bsky.social shares trial-and-error-learned lessons.
For anyone implementing textual RAG, check the blog by @cle-does-things.bsky.social!
✅ useful tips, from chunking to evals-related;
✅ projects applying each tip in the wild.
👉 qdrant.tech/blog/hitchhi...
For anyone implementing textual RAG, check the blog by @cle-does-things.bsky.social!
✅ useful tips, from chunking to evals-related;
✅ projects applying each tip in the wild.
👉 qdrant.tech/blog/hitchhi...
July 10, 2025 at 2:52 PM
An open source engineer from @llamaindex.bsky.social shares trial-and-error-learned lessons.
For anyone implementing textual RAG, check the blog by @cle-does-things.bsky.social!
✅ useful tips, from chunking to evals-related;
✅ projects applying each tip in the wild.
👉 qdrant.tech/blog/hitchhi...
For anyone implementing textual RAG, check the blog by @cle-does-things.bsky.social!
✅ useful tips, from chunking to evals-related;
✅ projects applying each tip in the wild.
👉 qdrant.tech/blog/hitchhi...
☕ Guess what? We're sponsoring the coffee breaks at @berlinbuzzwords.de 2025!
June 10, 2025 at 8:20 AM
☕ Guess what? We're sponsoring the coffee breaks at @berlinbuzzwords.de 2025!
🥨 Come to the Bavarian Search Meetup!
The 2nd meeting of 𝐁avaria, 𝐀dvancements in 𝐒𝐞arch 𝐃evelopment meetup, co-organized by our @mrscoopers.bsky.social, is happening in #Munich on the 12th of June!
👇
The 2nd meeting of 𝐁avaria, 𝐀dvancements in 𝐒𝐞arch 𝐃evelopment meetup, co-organized by our @mrscoopers.bsky.social, is happening in #Munich on the 12th of June!
👇
June 2, 2025 at 1:20 PM
🥨 Come to the Bavarian Search Meetup!
The 2nd meeting of 𝐁avaria, 𝐀dvancements in 𝐒𝐞arch 𝐃evelopment meetup, co-organized by our @mrscoopers.bsky.social, is happening in #Munich on the 12th of June!
👇
The 2nd meeting of 𝐁avaria, 𝐀dvancements in 𝐒𝐞arch 𝐃evelopment meetup, co-organized by our @mrscoopers.bsky.social, is happening in #Munich on the 12th of June!
👇
Want to see MCP in action? Learn how to orchestrate OpenAI agents using MCP, AugmentCode, and Qdrant.
📅 April 29 @ 11 am ET
🔗 Save your spot: try.qdrant.tech/mcp-agent-in...
📅 April 29 @ 11 am ET
🔗 Save your spot: try.qdrant.tech/mcp-agent-in...
April 14, 2025 at 5:21 PM
Want to see MCP in action? Learn how to orchestrate OpenAI agents using MCP, AugmentCode, and Qdrant.
📅 April 29 @ 11 am ET
🔗 Save your spot: try.qdrant.tech/mcp-agent-in...
📅 April 29 @ 11 am ET
🔗 Save your spot: try.qdrant.tech/mcp-agent-in...
Relevance feedback helps search systems iteratively improve results toward relevance. It’s been studied for 60+ years — yet remains rare in modern neural search.
We explored the field to understand why — and gathered this summary of methods proposed over the years.
⬇️
We explored the field to understand why — and gathered this summary of methods proposed over the years.
⬇️
April 2, 2025 at 3:30 PM
Relevance feedback helps search systems iteratively improve results toward relevance. It’s been studied for 60+ years — yet remains rare in modern neural search.
We explored the field to understand why — and gathered this summary of methods proposed over the years.
⬇️
We explored the field to understand why — and gathered this summary of methods proposed over the years.
⬇️
🚧 We ran vector search over 400M CLIP embeddings from LAION-400M — using Qdrant and just 64GB RAM.
We wanted to see how far we could push Qdrant with minimal hardware and how much we could squeeze out of quantization, indexing, and async I/O.
We wanted to see how far we could push Qdrant with minimal hardware and how much we could squeeze out of quantization, indexing, and async I/O.
March 28, 2025 at 3:06 PM
🚧 We ran vector search over 400M CLIP embeddings from LAION-400M — using Qdrant and just 64GB RAM.
We wanted to see how far we could push Qdrant with minimal hardware and how much we could squeeze out of quantization, indexing, and async I/O.
We wanted to see how far we could push Qdrant with minimal hardware and how much we could squeeze out of quantization, indexing, and async I/O.