Alternatives
Products that do what AIONBD does
Deploy vector search on branch sites, IoT devices ...
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The portable vector database for AI agents beyond the cloud
Apr 2026 · actian.com
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Hey HN! I built a proof-of-concept for AI memory using Git instead of vector databases. The insight: Git already solved versioned document management. Why are we building complex vector stores when we could just use markdown files with Git's built-in diff/blame/history? How it works: Memories stored as markdown files in a Git repo Each conversation = one commit git diff shows how understanding evolves over time BM25 for search (no embeddings needed) LLMs generate search queries from conversation context Example: Ask "how has my project evolved?" and it uses git diff to show actual…
2025 · github.com
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This is a vector index I built that supports insertion and k-nearest neighbors (k-NN) querying, optimized for GPUs. It operates entirely in CUDA and can process queries on half a billion vectors in under 200 milliseconds. The codebase is structured as a standalone library with an HTTP API for remote access. It’s intended for high-performance search tasks—think similarity search, AI model retrieval, or reinforcement learning replay buffers. The codebase is located at https://github.com/rodlaf/BinaryGPUIndex.
2025 · rlafuente.com
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Mar 2026 · github.com
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2024 · github.com
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Hey HN, we want to share HelixDB (https://github.com/HelixDB/helix-db/), a project a college friend and I are working on. It’s a new database that natively intertwines graph and vector types, without sacrificing performance. It’s written in Rust and our initial focus is on supporting RAG. Here’s a video runthrough: https://screen.studio/share/szgQu3yq. Why a hybrid? Vector databases are useful for similarity queries, while graph databases are useful for relationship queries. Each stores data in a way that’s best for its main type of query (e.g.…
2025 · github.com
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Hey everyone, ML Blocks is a node-based workflow builder to create multi-modal AI workflows without writing any code. You connect blocks that call various visual models like GPT4v, Segment Anything, Dino etc. along with basic image processing blocks like resize, invert color, blur, crop, and several others. The idea is to make it easier to deploy multi-step image processing workflows, without needing to spin up endless custom OpenCV cloud functions to glue together AI models. Usually, even if you're using cloud inference servers like Replicate, you still need to write your own image…
2024 · mlblocks.com
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Hey HN, I’m Surya and I’m excited to show you WarpBuild! WarpBuild provides fast, secure `x86-64` and `arm64` Github actions runners. This speeds up your workloads by 30%, at half the cost, and takes ~2mins to get started. We’ve been seeing pretty good results since we opened up signups a week ago and I’ve shared some numbers publicly here [1]. Currently, we support linux runners for Github organizations (not personal accounts) and MacOS support is coming soon (~Jan). The way the runners work is deceptively simple: Runners are assigned to hardware that is ideal for build workloads with fast…
2023 · warpbuild.com
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2023 · zeet.co
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Metal-first MoE inference for Apple Silicon with bounded SSD expert streaming and local OpenAI Chat, Responses, and Anthropic Messages endpoints. - hebrus-labs/hebrus
Jul 2026 · github.com
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Sep 2025 · github.com
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I've been exploring the (not so=) amazing potential of AI in coding and have compiled a list of tools. From AI-powered IDEs to code generators, this resource is my contribution to the community. I'm still on the fence about including txt2sql projects, as their functionality seems too basic to me. And I'm personally maintaining this, so your feedback is wellcome.
2025 · aicode.danvoronov.com
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Submit a job via API or dashboard and get results for cheap
Feb 2026 · carmel.so
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