Orbator's answer

Orbator measures whether AI assistants actually recommend your product. When buyers ask ChatGPT, Claude, Gemini, Perplexity or Grok for the best tool in a category, most founders have no idea if they are in the answer.

Orbator:

• runs the exact questions your buyers ask, across all five engines
• shows who gets recommended and who gets skipped
• reveals which sources each engine read before answering
• gets you listed on the sources AI actually cites

Most tools track Google rankings. Orbator tracks the AI answers where a growing share of buying research now starts.

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.

Orbator's answer

Three reasons.

• Methodology. Orbator only asks neutral buyer questions, never your product name. A forced mention is not a recommendation, so reports show what a stranger would actually be told.
• Evidence. Full answers are retained and every citation is resolved to its source. Any number in a report can be traced, and the methodology is public.
• Action. Measurement alone moves nothing. Every scan comes with the fix list, the specific AI-cited sources you are missing from, and Orbator does the submissions for you.

The first scan is free, so the honest pitch is simple: run it and see where you stand before spending anything.

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.

Orbator's answer

Founders and small software teams who sell to people that research with AI, plus local businesses (restaurants, med spas, dentists, law firms) whose customers ask for the best option near them in a chat window instead of a search box.

The typical user is a founder who just discovered ChatGPT recommends their competitor and wants to know why, and what to do about it.

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.

Orbator's answer

Orbator is built by a solo founder who runs both a restaurant and several small software products, so he sits on both sides of the problem. The trigger was watching buyers quietly switch from googling to asking AI assistants, and realizing there was no honest instrument for the obvious question: when someone asks AI for what I sell, am I the answer?

Existing SEO tools measure Google. Orbator was built to measure the answers themselves. It is also self-measuring: Orbator uses its own index to track whether AI recommends Orbator.

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.

Orbator's answer

• Backend: Node.js and Express
• Frontend: Next.js and React
• Data: PostgreSQL, including a citation index with full retained answer texts
• Infrastructure: self-hosted with Docker on European cloud servers
• AI engines: official APIs of OpenAI, Anthropic, Google, Perplexity and xAI, with web search enabled
• Submission assistant: Chrome extension (Manifest V3)

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.