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.
Replies
Looks powerful!! How easy it is to migrate our existing spreadsheets and fragmented databases into Boostspace? Is it more like an import button?
Boost.space
@zerotox thanks to CSV and AI import you can actually do it two ways: Either export Google Sheet as CSV and import it OR connect Google Sheets via Make scenario, throw bundle of fields to Boost.space and let our AI engine map everything for you.
Nas.com
Could you please share with me how does the tool handle real-time data sync conflicts across multiple agents and workflows? I imagine it would be very messy especially if you have too many nodes exchanging data with each other.
Boost.space
@nuseir_yassin1 Each source has its priority you can set on level of each field. Id recommend hanging out during the launch webinar thats in 2h: https://boost.space/v5
Luigi's Box
Congrats @matous_kralik and the team, well done 🚀
Boost.space
@matejkukucka Děkujeme, Matěji! 👌
Congrats!! The UI looks clean af 👏 Are there pre-made automation templates or do we gotta build everything ourselves?
Boost.space
@mikhail_prasolov Will forward this to our product team and thank you! 🔥
DevQuizzes
Congrats on the release guys!
Boost.space
@madzadev Thank you!
Looks powerful - congrats!
@robbins23 Thank you Robbin!
Netlify
Boost.space
This is a brilliant product idea. How you’re handling data governance and security at scale?
Boost.space
@harsh_jhunjhunuwala neverending pen testing & Sprinto together with secured cloud infrastructure. No magic here, just hard work and expensive hardware 😄🤌
The “marathon in flip-flops” analogy is painfully accurate for a lot of automation stacks. The persistent data layer angle is interesting — especially if it truly acts as a real SSOT instead of just another sync layer. Curious how you handle schema changes and versioning when multiple agents are writing to the same data?
Boost.space
@andrius_aguinaldo API prioritization & conditioning on field-level 🤤
Boost.space
@yashankgoswami we closed our devs in basement for like 4 to 5 months. Not so many UI changes, but especially the AI Mapping & new Make.com API integration with new app took us some time 📈