Hey Product Hunt 👋 Here's the thing nobody tells you about scaling AI agents: they don't share. One agent researches a vendor on Monday. Another agent researches the same vendor on Wednesday. A third on Friday. Three full frontier-price reasoning runs, three long waits while the model thinks through what's already been figured out. One answer. Your org paid for it — and waited for it — three times. Now multiply that across every agent, every team, every day. We built **Semelbase** — shared execution memory for all the AI agents in your organization. When any agent completes work, that work becomes reusable infrastructure for every other agent. Future requests build on what's already been done instead of paying an expensive model to slowly rediscover it. Agents skip the exploring and go straight to executing. The payoff is double: **less money and less time.** In matched benchmark runs — same agent, same tasks, with and without memory — Semelbase cut spend by 33%, model calls by 49%, and finished up to 67% faster, at an identical pass rate. Same answers. Fraction of the bill. Fraction of the wait. And it compounds: the more your agents work, the cheaper and faster every next task gets. Memory that behaves like an asset, not a cost. **Live today: the Semelbase Audit — free.** Log-only, runs entirely inside your environment, reads the agent traces you already collect, changes nothing in production. In minutes it puts a dollar figure on how much of your AI spend is repeat work. We'd rather show you your number than pitch you software. The layer that recovers that money — and that time — ships next. Audit teams get first access. If you're running more than one agent, ask yourself: do they know what each other did yesterday? Get your number 👇 — the Semelbase team

Semelbase — Shared memory for AI agents

Shared execution memory for every AI agent in your org

Shared execution memory for every AI agent in your org