AI Intime
Sovereign AI for Enterprises
2 followers
Sovereign AI for Enterprises
2 followers
AI Intime is an agentic AI platform for manufacturing teams to build custom, role-specific agents tailored to their operational workflows. Each agent connects via MCP to systems like ERPs and emails, answers natural-language questions, and enforces role-based access so users see only what they should. Deploy sovereign, on-prem to keep sensitive operational data in your own infrastructure. Built for manufacturing and adaptable to any sector where work depends on the right data at the right moment
We come from Vegam Solutions, where we've spent the last two decades building mission-critical enterprise software for 300+ factories across 60 countries, the kind of systems where a bad decision on the plant floor costs real money and AI has to be trusted before it's useful.
Across all of it, we kept watching the same thing happen: companies were creating knowledge faster than they could preserve it. The "why" behind a critical decision, the fix someone figured out months ago, the workaround a team forgot two versions back—all of it slipping through the cracks.
Then GenAI arrived, and a second pattern emerged on top of the first: enterprises everywhere were running pilots, but almost none were making it into production. After our CEO Subbu spent time with dozens of enterprise leaders, one insight crystallized: people weren't struggling to find answers. They were struggling to trust them.
The reason isn't intelligence. Frontier models are extraordinary. The reason is that generic copilots don't understand an enterprise's ontology, its security boundaries, its regulatory constraints, or the actual workflow a plant manager or compliance officer runs every day. And most of them can't be deployed where the data actually lives.
So we built AI Intime, a sovereign, enterprise-owned agentic AI platform.
Instead of another chatbot, AI Intime lets organizations build custom, role-specific agents that operate inside their systems of record SAP, MES, ERP, and data lakes through MCP. Every answer has a receipt: traceable sources, citations, timestamps. Every action is policy-controlled. And it runs on-prem or air-gapped, so regulated industries (BFSI, defense, healthcare, and manufacturing) can finally move AI from pilots into production without the data leaving their walls.
We're not trying to replace system integrators we partner with them. We bring the platform and the agentic intelligence; they bring scale and domain reach.
A few things I'd love your feedback on:
Does the "sovereign + agentic + governed" positioning resonate, or feel too niche?
If you've run enterprise GenAI pilots that stalled, what broke first integration, governance, or trust?
What would make you want to try a sovereign deployment over a cloud-first one?
Would genuinely value your feedback, especially from anyone who's tried to get enterprise AI past the pilot stage.
Thanks for having us :)