


Boost.space v5 is a no-code Agentic Database that provides a persistent context layer for AI agents and automation workflows. It transforms scattered business data into live, structured, and synchronized context so AI systems can act intelligently instead of guessing. By acting as a "Shared Brain," Boost.space ensures every workflow has the full picture—from past interactions to live database states—allowing automations to compound rather than break.
Connect LLMs through the Model Context Protocol so agents can query live data and execute actions across your entire tool stack. This turns AI from a simple chatbot into an active operator that understands your business.
Run automation workflows on top of standardized data using Make, Zapier, n8n, or Boost.space's own engine. Every workflow gets the full business context it needs to make accurate decisions.
Keep all systems continuously aligned with bidirectional synchronization. Context stays always up to date across CRM, billing, ecommerce, and support tools without manual intervention.
Enrich thousands of records automatically with AI Fields for classification, structured attributes, translations, and normalization. This eliminates manual data cleanup and ensures consistent quality.
"When your data becomes a live context, AI stops being a chatbot and becomes an operator."
This one-liner captures Boost.space's core advantage: it bridges the gap between fragmented data and intelligent execution. Most AI agents fail because they lack business context, but Boost.space provides a unified, real-time view that lets automations act on complete information. The result is computed answers instead of hallucinations, and workflows that compound knowledge rather than starting from scratch each time.
You're running AI agents or complex automations that keep breaking because they lack business context. Boost.space is ideal if you need to synchronize data across multiple systems (CRM, ecommerce, support) and want AI to enrich and act on that data automatically. It's also a strong fit for teams scaling operations—one customer reduced manual product updates by 99% while growing from 350 to over 1000 SKUs with zero extra headcount.
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