Private equity (PE) firms now compete on the AI capability they can engineer into the portfolio. The firms producing the strongest returns are running a consistent strategic playbook across portfolio companies (portcos), one that ties every data and AI investment to measurable value creation, defensibility, and the multiple at exit.
We design the AI strategy with portfolio ops, build it inside the portcos, and scale it across the portfolio.
CHALLENGES
Portco processes are outdated. The systems behind them were not engineered for AI-era automation. Without modernization, the operational improvements that drive multiple expansion cannot be deployed inside the hold period, and fast-payback ROI sits behind months of foundational work.
AI-native entrants are arriving in portco categories with lower cost structures, faster product cycles, and better unit economics. Portfolio companies that fail to adopt AI face structural disruption before exit, which erodes valuation and narrows the firm's strategic options.
AI for the sake of AI does not produce material value at exit. The right initiatives depend on where the portco sits in its hold period. A year-four play looks nothing like a year-one play, and most portcos do not have the strategic lens to prioritize accordingly.
Portco data lives across disconnected systems, business units, and acquired entities. Without centralization, it is not possible to deploy AI at scale, measure value creation consistently, or carry the playbook from one portco to the next.
Capabilities
We design the AI value creation strategy alongside portfolio operations, build production-grade systems inside the portco, and scale the playbook from one portco to the next.
Identify the AI initiatives that produce the most material value at exit and build a portco-specific roadmap aligned to the hold period
Design the data ownership, access control, and AI governance framework portfolio companies need to adopt AI defensibly
Centralize fragmented portfolio company data into a platform engineered for AI at scale and for metrics the firm can trust
Give portfolio operating partners and portco executives visibility into the operational and financial KPIs that drive value creation
Deploy agentic AI, document intelligence, conversational AI, computer vision, and forecasting models built for the operational realities of the portco
Automate data quality monitoring and policy enforcement so AI investments hold up through diligence
A dedicated OneSix team stays embedded across the portfolio for continuous delivery and a repeatable playbook
Use Cases
Use Case
What it does
Use Case
What it does
Digitization and AI automation layered on contract, invoice, and operational document corpora to eliminate manual processing and unlock data trapped in PDFs
Use Case
What it does
Autonomous AI workflows that execute multi-step operational processes across finance, operations, customer success, and back-office functions
Use Case
What it does
Intelligent interfaces that give portco employees and customers fast access to institutional knowledge, support content, and operational data
Use Case
What it does
Visual AI for quality, safety, and operational monitoring across manufacturing, retail, logistics, and consumer services portcos
Use Case
What it does
Predictive models that improve demand planning, financial forecasting, and operational decision-making across the portfolio
FAQs
We work across the industries PE firms invest in: manufacturing, consumer services, technology and SaaS, retail, healthcare, and more. The use cases and operational context differ by sector. The strategic approach stays consistent: identify the AI investments that produce the most material value at exit and engineer them in a way the portco can operate after handoff.
A portco three years from exit needs a different playbook than one in year one of a five-year hold. We start every engagement by understanding where the portco sits in its hold period, then prioritize accordingly. Fast-payback operational engagements for shorter horizons. Foundational transformation and defensibility work for longer ones. Every system we deliver is engineered to produce value visible at exit and to be operated by the portco team after handoff.
Both. Engagements typically start with portfolio operations to align on strategy, governance, and the portfolio-wide playbook. From there, we embed with portco leadership to execute. The result is a consistent strategic approach across the portfolio with implementation calibrated to each company.
Yes. This is the model most of our PE relationships operate in. We work with firms as a trusted partner across the portfolio: running strategy workshops with portco leadership, reusing reference architectures, and applying lessons from one engagement to the next. The goal is a repeatable approach that moves portcos from technology laggard to AI-first business regardless of which company comes next.
Often, no. Data quality matters in every engagement, and if a portco's operational data is fragmented or unreliable, we address that inside the engagement and build the data foundation in parallel with AI development. Many of our PE engagements combine Data Foundations and Artificial Intelligence into a single coordinated effort to compress time to value within the hold period.
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