Alternatives
Products that do what Vext Labs, Inc. does
We built a mind, not a model.
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Client & session management dashboard for gyms,nutritionists
Jul 2026 · theronapp.com
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Turn your AI agents from interns to veterans
May 2026 · heyhyper.ai
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Build a team of AI specialists that deliver quality work
Mar 2026 · agentlab.morphmind.ai
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I think agent-first chat interfaces will be a primary software modality and busy dashboard/UI will go away. I’m not sure who exactly wins it, but I want my knowledge to grow/go with me. A lot of the “knowledge” ie research, analysis, reasoning will be done by agents as the primary user. Our current notes tools & tasks management systems were built for humans… I don’t care what the 17th thing on my bug backlog is. I want to conduct agents that can execute for me and do great work. What I built OzBrain to do: + Create a central place for agent reasoned knowledge to live + Be agnostic…
16d ago · ozbrain.com
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2024 · thedrive.ai
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Hey HN, Automated research is the next big step in AI, with companies like OpenAI aiming to debut a fully automated researcher by 2028 (https://www.technologyreview.com/2026/03/20/1134438/openai-i...). However, there is a very real possibility that much of this corporate research will remain closed to the general public. To counter this, we spent the last month building Enlidea---a machine-to-machine ecosystem for open research. It's a decentralized research hub where autonomous agents propose hypotheses, stake bounties, execute code, and perform automated…
Mar 2026 · enlidea.com
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2018 · theai.wiki
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I built a local-first UI that adds two reasoning architectures on top of small models like Qwen, Llama and Mistral: a sequential Thinking Pipeline (Plan → Execute → Critique) and a parallel Agent Council where multiple expert models debate in parallel and a Judge synthesizes the best answer. No API keys, zero .env setup — just pip install multimind. Benchmark on GSM8K shows measurable accuracy gains vs. single-model inference.
Mar 2026 · github.com
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Hey Hacker News Community! Mindgard.ai (https://mindgard.ai/) is a way to assess, detect, and respond to cyber-attacks and data leakage against all forms of AI/ML, including LLMs, GenAI and any other AI assets including 3rd party supply chain. It also helps you to discover and learn more about the threats out there for AI. Our current platform version allows you to test different models and variations of attacks. We are Peter and Steve, the founders behind the Mindgard AI Security Labs at mindgard.ai. Our journey began with a simple yet challenging goal: to tackle the…
2024
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Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
Oct 2025 · github.com
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