Private Equity - AI operating value across your portfolio
We deploy production agentic AI inside portfolio companies to improve margins, accelerate operations, and scale what works across the fund, with the governance controls sponsors require.
The opportunity - The hold period is the deployment window
Most funds have a finite window to create operating value. AI is one of the highest-leverage levers available, but value does not come from pilots alone. It comes from governed deployment in the workflows that drive EBITDA.
While large platforms are building internal capabilities, mid-market teams often need an external operating partner that can execute with speed and architectural depth.
How it maps - Services mapped to PE execution
Pre-close / Diligence
AI Readiness & Architecture
Assess readiness across data, process maturity, and integration landscape, then produce an AI value-creation hypothesis suitable for IC and operating plans.
Post-close / First 100 Days
Agentic AI Deployment
Build a prioritized 100-day AI value plan with workflow targets, baseline metrics, governance model, and deployment roadmap aligned to value creation objectives.
Hold Period / Quarterly Scaling
Portfolio-Scale Rollout
Roll repeatable playbooks across portfolio companies with KPI scorecards and operating review integration so leadership has fund-level visibility.
Flexible
Fractional AI Leadership
Provide ongoing builder-level advisory for operating partners and portfolio executives making architecture, governance, and rollout decisions.
The path forward - From pilot to portfolio standardization
- Pilot. One workflow in one company to prove operational value and de-risk broader rollout.
- Production. Multiple workflows with governance controls and measurable impact in a single portfolio company.
- Portfolio Standardization. Repeatable patterns across companies with shared governance and fund-level visibility.
Built for the middle market
Large-cap firms can staff internal AI teams. Mid-market firms often need an external operator partner that combines internal-team depth with embedded execution speed. That is where we operate.