Alternatives
Products that do what Van Helsin does
An AI ecosystem that goes beyond chat
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- 17AG
I’ve been building LLM tooling for a small VC fund and found myself explaining the same mental model over and over to non-technical people around me: how a stateless LLM becomes a chatbot, how tool use works, what an agent is mechanically, and why context windows shape all of it. I never found a guide that covered that full chain at the level I wanted, so I wrote one. It’s nine short chapters, each building on the last. Deliberately simplified: the goal is a useful mental model, not a textbook. Feedback, corrections, and contributions welcome: github.com/ymyke/aiaiai
Apr 2026 · aiaiai.guide
- 18HH
I found myself building a bunch of LLM-backed features that needed to use tool calling, and some of those tools involved doing things that were somewhat high stakes - communicating on my behalf or modifying shared / production data. one example - I wanted to replace a marketing website with a chatbot + vector DB loaded with the previous content, docs, and blog posts. Between hallucinations, missing knowledge base info, and the LLM generally writing like an psuedo-intellectual high schooler, I realized I couldn't trust it to communicate unsupervised with my website visitors. I needed a…
2024 · github.com
- 19AP
We’ve been power users of AI tools for the past year, and we kept running into three constant frustrations: 1. Too many subscriptions – Paying separately for OpenAI, Anthropic, Perplexity, and others quickly adds up. 2. Losing memory & context – Switching between models or platforms means you start over each time. 3. Privacy concerns – With most closed-source models, your data may be stored or used for training. That’s not acceptable for sensitive or professional use cases. So we built AgentSea: a private and safer chat interface where you can access the latest models, agents, and tools in…
2025 · agentsea.com
- 20IB
I've built VT Chat, a privacy-first AI chat application that keeps all your conversations local while providing advanced research capabilities and access to 15+ AI models including Claude 4 Sonnet and Claude 4 Opus, O3, Gemini 2.5 Pro and DeepSeek R1. Live: https://vtchat.io.vn | Source: https://github.com/vinhnx/vtchat The core difference is true local-first architecture. All chats are stored in IndexedDB with zero server storage. Your API keys never leave your browser, and I can't see them even as the developer. You can switch between OpenAI, Anthropic, Google…
2025
- 21PS
I didn't want to buy a standalone computer or repurpose a laptop to run constantly so I could maintain a system to sync my LLMs, so I built this. It's a simple overview of my system, laid out in a way easy to unpack and replicate for yourself. The project is meant to be configured individually, and uniquely, since one solution might not be what's best for another. If anything, maybe it gives you some ideas on how to implement things for your own project. Best wishes, Ryan.
27d ago · pacslate.com
- 22GM
Hello Everyone, I'm excited to announce that I'm currently developing a multi-model AI chat system featuring Branches! It's still in beta right now, but the full version will be officially released later this week. Stay tuned for updates! Thank you for your support!
2025 · graphine.ai
- 23LA
Hey HN, I’m building Lenzy AI - probably the first product analytics platform for AI agents. From my research: Companies building AI agents have thousands or even millions of conversations. In these, users express what they need, use, love, or hate. Often long before they reach out to support (or churn). Some teams try to read chats manually, some build in-house pipelines to analyze them, others completely miss out on this data. The idea: Lenzy continuously analyzes conversations users have with your AI agents to: 1. Discover missing features (e.g. "Fetch info from a URL" mentioned 42 times…
Oct 2025 · lenzy.ai
- 24FF
I built Hermes, an open-source Python framework for multi-agent financial research. Most AI “equity research” demos stop at generating text. In practice, real workflows require pulling structured XBRL financials from SEC filings, extracting labeled sections like MD&A and Risk Factors, merging macro and market data, building actual Excel models with formulas, and generating investment memos in Word or PDF. Hermes is designed to handle that full pipeline end to end. It includes 35 financial data tools covering SEC EDGAR (via edgartools), FRED, Yahoo Finance market data, and RSS-based financial…
Feb 2026 · github.com
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