Ontora for Private Equity
Work with portfolio management teams to find operational upside, implement AI solutions, and measure the value created.
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Bring operating partners and management teams through the same process: find the value, implement the change, and assess the return.
Hear directly from teams across a portfolio company. Agent-led conversations reveal the day-to-day constraints, local practices and dependencies behind the operating plan.
A conversation that goes deeperWho approves a purchase when it can’t wait?
Connect interviews into a view of processes, handoffs and dependencies within the company. Review different accounts with management before using the findings to shape an initiative.
See where operational friction and AI opportunities meet. Help management teams choose where to focus, with the underlying process evidence ready to inspect.
Simplify approval handoffs. Reduce manual reporting. Clarify process exceptions.
Move from prioritised opportunities to working AI solutions with management teams. Measure results against the operating baseline and use that evidence to guide the next rollout.
Your context. In Claude.Explain our purchase approval process, including the exceptions.
Identify where AI can reduce friction inside a portfolio company. Agree on priorities and the starting baseline with management.
Implement solutions alongside operating teams and process owners, with the context needed to change how work gets done.
Measure the result in each business. Use what worked to inform the next initiative and assess fit across the portfolio.
Both the operating team and the people inside a portfolio company contribute to the picture. Start with a specific operating question and use the findings to support decisions with management.
AI agents hold focused conversations with the people doing the work. They ask follow-up questions, connect different perspectives and use screen sharing to understand the tools and steps being described.
Ontora builds a shared knowledge layer across conversations. When an answer reveals an exception or a gap, that context informs what the agent asks in the next conversation.
Company context is accessible through API, MCP and CLI. Your team can bring it into its own analysis, workflows and AI tools without starting every question from scratch.
We agree on a baseline and success measures with your operating team and management. Assess time saved, cost changes, and capacity gained against implementation costs, using the company’s operational and financial data.