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Avery
Create a deterministic agent that runs on your hardware
Most agentic AI projects will fail, killed by cost, privacy, and no determinism. Gartner expects ~40% to be canceled by 2027. The work most worth automating is exactly what you can’t hand to a metered public cloud. Avery flips that. Describe an agent in one plain sentence; Avery fabricates a deterministic agent that runs on your hardware, private, auditable, owned. No code. No cloud lock-in. No per-token meter. From a sentence to a working agent in under 30 minutes.
Hey Product Hunt 👋
Bhoomika here, on the launch team at Avery.
We started Avery NXR (Native Execution Runtime) because we kept watching teams hit the same wall with AI: you can't put the work that's most worth automating - your code, your data, your customers - into someone else's cloud and a per-token meter.
So we built a local-first agent and app platform. Here's the short of it:
→ Describe what you want in plain English. Avery picks the archetype, decomposes it into entities, locks a plan, and runs the generators - producing a full Next.js + Prisma + Postgres codebase on your laptop. 17 signed generator plugins. You own every line.
→ Build agents three ways - wizard, blank, or template. 59 capabilities across 14 categories. Sub-agents, loops, KB retrieval, shell commands with guardrails. 7 production-ready templates pre-loaded: Anna for daily AI news, Sophia for meeting follow-ups, Marcus for resume screening, Priya for support triage, Carlos for sales pipeline, Yuki for competitor monitoring, Liam for server health.
→ 63 connectors out of the box (15 OAuth + 48 API-key across 13 categories). Sign in once, use everywhere.
→ Deploy to Vercel, Railway, or SSH on-prem.
→ Consult Mode (opt-in) - when a task truly needs a frontier model, we send only anonymized, redacted context via YOUR BYOK keys. Off by default. Per-task consent. Every escalation logged.
Free Desktop is genuinely $0 forever. Pro is flat $29/user/month - no token meter. Enterprise is on-prem capable, air-gap ready.
Be sovereign. Run AI on your hardware. Own the codebase.
Ruban (our founder) and I are in the comments all day. Ask us anything - about the architecture, the Consult Mode model, the deploy paths, or whether this fits a workflow you've got in mind.
- Bhoomika
Ran it locally on an old workstation and had a working agent in about 20 minutes, the setup was way smoother than I expected for something this self-contained.
Excited to see this go live 🚀
I'm on the eng team at Avery. The audit ledger was one of my favorite things to build, it's overkill for most use cases, but for the regulated customers we've been talking to, it's the reason they can say yes to AI at all.
If you're evaluating agent platforms with compliance in mind, ask us about the ledger. It's the boring feature I'm proudest of!
👋 Ruban here, co-founder of Avery.
Every "AI agent builder" today hands you the same thing: a chat box wired to a model that re-thinks your task from scratch every single time it runs. Magical in a demo, terrifying in production: non-deterministic, unauditable, expensive, and leaking your data to a frontier model for work a single line of code could do.
We took the idea from computing's most reliable invention: the compiler. You describe what you want in plain language, and Avery performs Agentic Compilation. The AI does the hard thinking once, at build time (or on feedback from the user), and emits a real, deterministic workflow. What you get is a Compiled Agent: an inspectable, reproducible program you can open, debug step-by-step, and trust to behave the same way tomorrow. The model designs the agent; it doesn't become the agent at runtime. You get frontier-model intelligence with the reliability of software.
And here's what genuinely sets us apart: most platforms let you build an agent, or a web app. Avery builds all of it from one desktop:
🤖 Agents — headless workers that run on a schedule, a trigger, or an inbox. 🖥️ Web apps — real, deployable Next.js products, not mockups. 📱 Mobile apps — genuine Expo apps, previewed on your phone via QR. 🎛️ Agentic apps — a real UI for your agents, so a non-technical teammate can actually use them.
One canvas. One plain-language conversation. Four kinds of software that ship.
A few more things we haven't seen elsewhere:
⚡ Cheapest capable mechanism wins. Every step is biased toward rules → code → an on-device model → the cloud, in that order. Avery won't bill you a frontier call to check if a number is greater than five.
🔒 On-device by default. Local models (in-app WebGPU + Ollama) handle the private, routine work. Your documents don't leave your machine unless a step truly needs the cloud and you approve it.
🩺 Self-healing builds. Avery tests each agent against your real data, finds the exact step where the data went wrong, and repairs it, instead of failing with a shrug.
We're two-time co-founders who've spent years watching "autonomous agents" shatter the moment they meet the real world. Avery is our answer: software you can read, price, trust, own, and ship.
Would genuinely love your feedback. We're in the comments all day. 🙏
About Avery on Product Hunt
“Create a deterministic agent that runs on your hardware”
Avery was submitted on Product Hunt and earned 15 upvotes and 8 comments, placing #52 on the daily leaderboard. Most agentic AI projects will fail, killed by cost, privacy, and no determinism. Gartner expects ~40% to be canceled by 2027. The work most worth automating is exactly what you can’t hand to a metered public cloud. Avery flips that. Describe an agent in one plain sentence; Avery fabricates a deterministic agent that runs on your hardware, private, auditable, owned. No code. No cloud lock-in. No per-token meter. From a sentence to a working agent in under 30 minutes.
Avery was featured in Developer Tools (515.9k followers), Artificial Intelligence (473.8k followers) and No-Code (5.8k followers) on Product Hunt. Together, these topics include over 188.2k products, making this a competitive space to launch in.
Who hunted Avery?
Avery was hunted by Bhoomika R. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Bhoomika R