Every portco runs on tribal knowledge — the rules, exceptions, and decisions that live in senior employees' heads, in old Slack threads, in scattered Notion pages. It's the bottleneck on every AI deployment we've seen across the portfolio. Hive extracts it, structures it for agents, and gives your operating team a Company Brain you can roll out across the portfolio.
A portco shipped a support agent. It worked for 80% of tickets. Then it confidently quoted the wrong refund window to a customer the founders had been hand-holding for two years, and the deal team found out from the customer — not from QBR.
The right answer existed. It just lived in a Slack DM between the CX lead and a founder, written six months ago when they carved out an exception for annual plans. Notion still said 30 days, no exceptions. The Drive doc said escalate over $10k. Three sources, three answers, and the agent picked the most confidently-worded one.
Every company runs on tribal knowledge — rules and exceptions decided in threads, refined in calls, contradicted in policy docs nobody owns. Across the portcos we've worked with, this is the bottleneck on every AI deployment. The model isn't broken. The company's knowledge was never structured for an agent to use — and no portco's IT team is going to structure it without help.
Slack, Notion, Google Drive. Read-only. We ingest threads, docs, and decisions — not just the documents your team remembered to write.
We surface the rules — with their conditions, exceptions, and escalation paths — and tag every node with source, timestamp, and reliability. When sources disagree, we resolve where we can and surface the rest for human review once, not every time the agent runs.
Each process is a versioned node in a structured graph, with sources and a confidence score. Wire it into Decagon, Sierra, an in-house agent — anything that takes a structured workflow. Roll the same Brain out across the portfolio; every decision and conflict resolved makes it smarter.
Your portcos already have Notion, maybe Glean, maybe Whale or Trainual. Notion AI and Glean answer from what's already written. SOP tools ask humans to write docs that go stale in 60 days. None of them extract the tribal knowledge that was never written down— and that's the layer the agents need to actually work.
The 2022-and-after PE environment requires operational alpha, not financial engineering. Bain's framing — "12 is the new 5" — captures it: today's deals need ~12% EBITDA growth where 5% used to clear the bar. Hold periods have stretched to 6.7 years. $3.8 trillion of unrealized value is sitting in portfolios. Operating groups have more than doubled since 2021, with the largest hires in IT, procurement, and digital/AI.
Every major sponsor is now running a named AI program — Apollo's APPS, Hg's Catalyst, Vista's Agentic AI Factory, KKR's Capstone Digital, Thoma Bravo. The mandate is committed and budgeted. The question your operating partners are quietly asking is who actually delivers it across the portfolio for sponsors that don't have an in-house AI team. That's what Hive is built for.
Agent reliability finally crossed the threshold for this work in 2025–2026. SWE-bench Verified moved past 87%; GAIA past 74%. Agents can now run discrete, dependency-aware workflows reliably — exactly the shape of the work Hive extracts. Earlier than this, the layer wouldn't have mattered. Later, your portcos will have built it themselves. Now is the window.
Five design-partner slots before we ship. Pick a portco; we'll come back within 24 hours with a sample audit of one process from their stack — what we extract, what conflicts we surface, and what their agent could execute against tomorrow. Read-only access; no commitment to start.