BENCHMARK
State-of-the-art results on real memory benchmarks
Best in the world on real benchmarks — LoCoMo: 90.1% · LongMemEval: 93.4%. Benchmarks focused on long‑horizon, realistic memory tasks—not toy examples.
Production‑grade memory, not a hack around context windows
What is Backboard memory?
Backboard memory lets your apps remember people, projects, and decisions over time—across channels, devices, and models. Instead of stuffing entire histories into every LLM call, you:
MEMORY
Why engineers use Backboard for memory
From benchmark-leading recall to portable, integrated AI infrastructure — everything you need in one stateful API.
Integrated with routing, RAG, and web search
Memory is one feature in a unified stateful API. It works alongside model routing, RAG, adaptive context management, and web search — all configurable per request.
USE CASES
Memory patterns you can implement
Common memory architectures teams build on Backboard — from personalized copilots to org-wide knowledge.
Personalized copilots
Assistants and agents that remember user preferences, history, goals, and constraints across every session — no re-introduction required, ever.
Project‑centric memory
Attach memory to a project entity so the whole team's context — decisions, constraints, progress — is available to any agent or model working in that project.
Org‑wide knowledge
Memory at the organization level: policies, playbooks, customer history, and product knowledge that any agent across your stack can retrieve and use.
Cross‑app continuity
The same memory entity is accessible from your chat product, your IDE plugin, your backend jobs, and your mobile app — all staying in sync through one stateful API.