Boost.space v5 - Shared Context for your AI Agents & Automations
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Most AI agents & complex automations fail because they’re operating in the dark. Boost.space provides the persistent context layer that turns siloed LLMs into an integrated business intelligence system. Give your automations & agents a "Shared Brain." so all workflows has the full context of your business—from past interactions to live database states—allowing workflows to compound instead of breaking.
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Usefull tool, thank you for ability to tested out in my workflows!
@tomas_blatak1 Awesome Tomáš! Thank you! Cant wait for what you can build with Boost.space
I hit this wall with Airtable around the 10th automation. Schema works fine for one workflow, but the moment two agents write to the same table with different assumptions, you get silent data conflicts. Boost.space doing two-way real-time sync with MCP support changes the failure mode... agents can query live state before acting instead of debugging why row 847 got overwritten. The 2000+ integration count matters less than whether the data model survives multi-agent writes without manual deconfliction.
Boost.space
@piroune_balachandran See you soon amd dont forget to grab that 50% OFF🔥📈
The shared context problem is so real. I run multiple AI agents for different tasks and the biggest headache is always them not knowing what the other one just did. You end up with conflicting outputs or redundant work. Question though - how does the context layer handle stale data? Like if agent A updates a record while agent B is mid-execution with the old version, what happens? That race condition stuff has been a nightmare in my setups.
Product looks extremely solid. Are you planning to include n8n or other automation tools later down the line or will it be make.com for a while?
Boost.space
@paula_amador_cardona adding n8n & Zapier later this year as well as vectorization. 📈
Congratulation on the launch. Is there a template library available for me to get started?
Shepherd
Really cool concept, the "shared brain" angle for AI agents makes a bunch of sense. Most automation setups I've worked with eventually hit that wall where nothing remembers what happened two steps ago. Having a persistent data layer that agents can actually build on top of feels like the missing jigsaw. I'm keen to see how it handles conflicts when multiple agents are writing to the same data at once. Congrats on v5 and the consistent PH momentum! 🚀
Nawvel
This could save countless hours of debugging broken automation flows.
I never understood n8n so I am a Make.com customer.
Very excited to give it a try :)
@raghavendra_devadiga4 Awesome I am looking forward for what you can build with Boost.space.
Well done! The MCP-ready architecture is a strong future-proofing move for agent-based systems.
GrowMeOrganic
Love the direction you’re taking here. Any timeline for n8n?
Lancepilot
This feels like infrastructure every serious AI stack will need. Great execution and very strong narrative around the problem.