Scaling Conversations: How Adapta Grew Usage Without Losing Context
Adapta added Supermemory as a persistent memory layer so every conversation keeps its context — letting the team scale usage without losing the thread.
Adapta is an AI workspace for SMBs — a general chatbot, agent-creation tool, and AI toolkit that more than 100,000 companies use every single day. At that scale, memory isn't a nice-to-have: a workspace people actually like has to remember what they've done.
The challenge: memory that holds up at scale
Memory is a genuinely hard problem, and Adapta felt it across a general-purpose product spanning chat, agents, and internal tooling. The team was even building memory systems of its own — but maintaining that, on top of everything else a workspace has to be, pulled focus away from the core product.
Why Adapta chose Supermemory
Rather than judge on landing pages, Adapta tested the major memory tools head-to-head. Supermemory delivered the best results, so the team kept it — and now builds on top of it as a dedicated building block. As Max puts it, even when you're building your own memory system, you should build it on top of Supermemory.
We tested them out, and Supermemory had the best results. Even if you're building your own memory system, you should build it on top of Supermemory.
The result: usage keeps climbing
Adapta watches one lever above all others: usage. Since leaning on Supermemory, usage inside the app has kept increasing — and the founder's own eye-test, the experience of actually using the workspace, has gotten better. For a product where memory makes or breaks the daily experience, that's the metric that matters.