GraphPilot VS Tempreon

GraphPilot's answer

GraphPilot is built by Kay Schecker, a solo founder from Düsseldorf, Germany. Caching GraphQL at the edge is easy to start and hard to get right: most setups end up choosing between short TTLs and purging far too much. GraphPilot was built to use the schema itself as the source of truth for what a response contains, so invalidation can be precise. The slogan says it: "We fly the complexity so you don't have to."

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.

GraphPilot's answer

Choose GraphPilot if you want caching that is driven by your schema and invalidation you can verify. Setup is a config file plus your schema, and you are live in minutes. It works with Apollo Server, GraphQL Yoga, PostGraphile and federation routers, and it also caches plain HTTP APIs. It runs on Fastly's global edge network, is built and operated in Germany, and has a free plan (Glider) so you can test it on real traffic before you pay.

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.

GraphPilot's answer

GraphPilot reads your GraphQL schema and turns it into cache keys. It adds the key fields each query needs, removes them from the response again, and tags every cached response with the objects it contains. When a mutation returns a changed object, GraphPilot purges the responses that contain it, without hand-written cache tags or short TTLs as a safety net. You can see each purge, with its reason, in the Cockpit.

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.

GraphPilot's answer

Engineering teams running GraphQL in production with read-heavy traffic: e-commerce, marketplaces, content platforms, SaaS dashboards and mobile app backends. Typically a platform or backend team that wants less origin load and lower latency without building and maintaining its own caching and invalidation layer.

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.

GraphPilot's answer

The edge runtime is written in Rust and compiled to WebAssembly on Fastly Compute. The platform and API run on TypeScript and PostgreSQL, the Cockpit is built with React, and the CLI (gpilot) is a single Rust binary for macOS, Linux and Windows.

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.