zvec-ai @ZvecAI

🎉 Zvec 0.6.0 Release is Live! This release brings major upgrades across retrieval, compute optimization, deployment experience, and the quantization framework. Upgrade and give it a try! ✨What's new: • 🔍Retrieval: New Group-By search with per-group Top-K support, covering Flat, HNSW, and HNSW-RaBitQ indexes • 📝Full-Text Search: Introduces a UAX #29 standard tokenizer, UTF-8 support, ASCII folding, and Snowball stemming for 34+ languages—a major upgrade for multilingual retrieval; Conjunction queries are now 22–38% faster with block-max pruning • ⚡ Compute Optimization: INT8/INT4 quantization now supports random rotation, evening out the distribution to reduce variance and quantization error; INT4 recall improves by up to 50+ percentage points while QPS remains essentially unchanged • 💾 Deployment Experience: DiskANN and libaio are now dynamically decoupled via dlopen, removing the libaio build dependency and plugin .so; libaio is automatically detected at runtime, with a graceful fallback when unavailable • 🧩 Quantization Framework: The internal quantization module has been refactored into a pluggable Turbo framework, decoupling quantization logic from index code; future quantizers such as PQ and RaBitQ can be added independently without modifying index internals 📚 Learn more: • 📄 Release Notes: zvec.org/en/blog/2026-0… • 🧭 Roadmap: github.com/alibaba/zvec/i…

🚀 New blog post: Zvec now has native full-text search With v0.5.0, Zvec can handle keyword recall, BM25 scoring, phrase queries, Boolean queries, and FTS × vector hybrid search inside the same embedded vector database. No separate Elasticsearch sidecar. No dual writes. No extra index sync. We also shared benchmarks against Elasticsearch and SQLite FTS5, plus a deep dive into how FTS fits into Zvec’s Segment architecture. 👉 Read the post: zvec.org/en/blog/2026-0…

📱What if your phone could search its own memory? To explore Zvec Flutter SDK on mobile, we built PocketSearch: an on-device search app that starts with intelligent local photo search on Android and iOS. It shows how Zvec can power fast, local retrieval today, and points toward richer mobile context for users and agents next. If you're interested in on-device retrieval or mobile AI context, follow along. 🔗 Blog: zvec.org/en/blog/2026-0…

🎉 Zvec 0.5.0 Release is Live! This release focuses on retrieval, indexing, ecosystem, and platform & hardware. Give it a try and let us know what you think! ✨ ✨ What's new: • 🔍 Retrieval: Native full-text search works out of the box; a single query fuses full-text search, semantic vectors, and conditional filters, with multi-way result merging handled automatically; the MultiQuery interface is implemented natively in C/C++, so every language SDK can integrate hybrid retrieval with ease • 💾 On-Disk Indexing: New DiskANN on-disk index significantly reduces memory overhead in large-scale scenarios; it complements HNSW/IVF/Flat to cover the full range of retrieval needs, from pure in-memory to on-disk • 🌐 Ecosystem: Brand-new official Go SDK and Rust SDK for smoother multi-language access; plus the new visual tool Zvec Studio for zero-code data browsing and query debugging • 🖥️ Platform & Hardware: Added RISC-V support, further expanding hardware compatibility 📚 Learn more: • 📄 Release Notes: zvec.org/en/blog/2026-0… • 🧭 Roadmap: github.com/alibaba/zvec/i… • 🐛 Report bugs / requests: github.com/alibaba/zvec/i… • 💬 Discuss & share: github.com/alibaba/zvec/d…

A nice write-up on what local-first vector search can actually look like on desktop apps. This post uses Zvec + Obsidian as an example to show: 1. local semantic search 2. image + text retrieval 3. related context surfacing while writing 4. fully on-device retrieval pipelines Feels like we're moving from “vector databases in the cloud” toward “vector search as a native capability inside apps”. Worth a read: zvec.org/en/blog/2026-0…

🎉 Zvec v0.4.0 is Live! This release focuses on mobile coverage, search capabilities, and stability. Give it a try and let us know what you think! ✨ What's new: • 📱 Mobile Coverage: Official Dart/Flutter SDK for Android (arm64-v8a) and iOS (arm64) • 🔍 Retrieval Enhancement: Enlarged topK limit to support large-scale candidate recall for downstream re-ranking pipelines • 🎯 Quantization Accuracy: Fixed SQ8 quantizer recall drop caused by missing int8 rounding in metadata computation • 🖥️ Cross-platform Stability: Fixed Windows drive-root path handling and improved OS error reporting; relaxed collection path validation For more details, please read the release blog: zvec.org/en/blog/2026-0… We also shared a deep dive into the engineering behind our lightweight core: zvec.org/en/blog/2026-0…

Two ways to use Zvec with your AI Coding Agent: 1️⃣ MCP Server — Your agent operates the vector DB directly via natural language. No code needed. zvec.org/en/docs/ai/mcp/ 2️⃣ Agent Skill — Your agent writes Zvec code (Python/Node.js) for you. Just describe your use case (RAG, e-commerce search, etc.) and get working code with schema design. zvec.org/en/docs/ai/ski… More native AI support is on the way! 🚀

🎉 Zvec v0.3.0 is Live! This release brings full multi-platform support for Windows, macOS, and Linux, along with official SDKs for Python, Node.js, and C. We've integrated the RabitQ quantization algorithm and added batch optimization for IP/L2 distance calculations on x86. We have also added MCP and Skill framework support for AI Agents. ⚡Performance and simplicity are always our top priorities. For more details, please read the blog post: zvec.org/en/blog/2026-0…