Tempreon's answer

Tempreon started with a simple observation: AI models keep changing, but the thing that makes them useful to you — your context, your preferences, your judgment — gets rebuilt from scratch inside every tool, and lost every time you move.

We built the layer that fixes that: person-owned memory served over the open Model Context Protocol, so it works across assistants instead of belonging to one. Along the way we open-sourced the pieces that are useful to everyone regardless of whether they use Tempreon — like memhaul, our MIT-licensed CLI for turning ChatGPT and Claude data exports into files you own.

The through-line is custody: the model is temporary, your memory shouldn't be.

HolyCode's answer:

It started as an open-source Docker image for running coding agents with persistent state, which is still free and maintained at github.com/CoderLuii/HolyCode. The most common feedback was that persistence mattered most: sessions, settings and progress surviving a rebuild rather than starting over each time. The hosted version is that same image on a machine someone else maintains.

Tempreon's answer

Most alternatives in this space are memory infrastructure for developers building their own AI apps. If you're the person using several AI tools every day, that's not your problem — your problem is re-explaining yourself to each of them and losing everything when you switch.

• Tempreon solves that one: one memory, every assistant, no re-onboarding.
• The model landscape changes every few months — a memory layer that belongs to you is the thing that shouldn't.
• No lock-in by design: plain-text exports, open-source export tooling, portable formats.

The choice is really about who the memory is for. Ours is for you.

HolyCode's answer:

Three practical differences. First, nothing gets reclaimed for idleness, so long unattended agent runs actually finish. Second, every tier includes the full toolset. Tiers differ only by CPU, RAM and disk, so paying more buys horsepower rather than unlocking features. Third, you bring your own Anthropic, OpenAI or Gemini key and the provider bills you directly, with no markup on tokens.

Where it is not the right choice: if you want a free tier to try, there isn't one, because every account is a real VM that costs money from the first minute. There is a 7-day refund instead.

Tempreon's answer

Tempreon is built for the person, not the app. Most memory products are developer APIs for adding memory to a single product; Tempreon is a memory layer you own that travels with you across every AI tool you use — Claude, ChatGPT, Cursor, anything MCP-capable.

• It learns, it doesn't just store. How you work, what you decide, how you like things done — refined over time, not filed away.
• One memory, every assistant. Captured once in one tool, available in all of them. No re-explaining yourself.
• Custody is structural, not marketing. Your data exports anytime, the formats are portable, and our export tooling (memhaul) is open source. We monetize the service, never the custody.

HolyCode's answer:

The machine does not stop when you do. Most cloud dev environments are containers with an idle timer that reclaims them when nobody has typed for a while, which is exactly what a working unattended agent looks like to a timer. Here the workspace is a real VM with a persistent disk. Hand an agent a four-hour task, close your laptop, and the processes, files and terminal scrollback are still there when you come back. It suspends when idle and resumes in about a second, so always-on does not mean always-billing.

Tempreon's answer

Individuals who live in AI tools all day: operators, consultants, founders, sales professionals, and knowledge workers who use more than one assistant and are tired of being a stranger to each of them.

If you've ever pasted the same context into Claude and ChatGPT in the same week — you're the audience.

HolyCode's answer:

Developers running AI coding agents on real work rather than demos. Typically people who already pay for Claude, Codex or Gemini and have hit the point where the bottleneck is not the model but the machine underneath it. Many have tried tmux on a VPS and got tired of maintaining the VPS.

Tempreon's answer

• Model Context Protocol (MCP) over streamable HTTP — the core of it. This is what makes Tempreon work in any compliant client rather than one walled garden.
• OAuth 2.1 with dynamic client registration and PKCE for authorization.
• TypeScript and Postgres under the hood.

The protocol choice is the product decision: build on the open standard, and your memory works everywhere the standard does.

HolyCode's answer:

Fly.io machines with persistent volumes for the workspaces, Docker and Debian for the image, ttyd for the browser terminal, Node and React for the interface, and Cloudflare for the site and control plane.