If you’re building an agent product, one shared model doesn’t work — your customers each combine a different mix of data sources, and their data must never mix.
Your reconciliation agent serves fifty customers, each stitching together a different combination of sales channels — Amazon, Shopify, Walmart — each with its own schema, vocabulary, and rules. Rebuild that context from scratch for every customer and you’re duplicating work fifty times over; collapse it into one shared model and the boundaries between channels blur.
BrainBox provisions an isolated brain per project — one per channel or data source, built once. Your customers map to tenants that simply inherit the specific projects they use: one customer combines Amazon + Shopify, another combines Amazon + Walmart, both reusing the same Amazon brain without any cross-contamination between their setups. Point your agent at the right tenant, and it gets exactly the composed context that customer needs — nothing rebuilt, nothing leaked.
A fintech company building a financial reconciliation agent provisions an isolated brain per sales channel, then composes them into per-customer tenants that reuse shared channel brains without duplication.
Grounded answers, not guesses — from a living model of your business.