The new PE edge is the AI you build into the portfolio.
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
What we typically see
Tech debt and legacy systems that delay value creation
Portco processes are outdated.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.
Disintermediation risk from AI-native competitors
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 value creation that is not matched to the exit horizon
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.
Data that is siloed and inaccessible
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
How we help
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.
Data & AI Strategy
Identify the AI initiatives that produce the most material value at exit and build a portco-specific roadmap aligned to the hold period
Governance Blueprint
Design the data ownership, access control, and AI governance framework portfolio companies need to adopt AI defensibly
Data Foundations
Centralize fragmented portfolio company data into a platform engineered for AI at scale and for metrics the firm can trust
Analytics
Give portfolio operating partners and portco executives visibility into the operational and financial KPIs that drive value creation
Artificial Intelligence
Deploy agentic AI, document intelligence, conversational AI, computer vision, and forecasting models built for the operational realities of the portco
Governance Programs
Automate data quality monitoring and policy enforcement so AI investments hold up through diligence
Operating Partnership
A dedicated OneSix team stays embedded across the portfolio for continuous delivery and a repeatable playbook.
Use Cases
Solutions we deliver in this industry
Document Intelligence
Digitization and AI automation layered on contract, invoice, and operational document corpora to eliminate manual processing and unlock data trapped in PDFs. Learn More
Agentic AI
Autonomous AI workflows that execute multi-step operational processes across finance, operations, customer success, and back-office functions. Learn More
Conversational AI
Intelligent interfaces that give portco employees and customers fast access to institutional knowledge, support content, and operational data. Learn More
Computer Vision AI
Visual AI for quality, safety, and operational monitoring across manufacturing, retail, logistics, and consumer services portcos. Learn More
Forecasting & Anomaly Detection
Predictive models that improve demand planning, financial forecasting, and operational decision-making across the portfolio. Learn More
Proof & Perspective
From the field
Private Equity
Automating data review and verification with document AI
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Enhancing sales efficiency with an AI quoting and knowledge platform
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Boosting sales by 15% through marketing optimization for a spa franchise
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Unifying data for enhanced portfolio insights and reduced risk in private equity
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Culture Matters: Building a Data-Driven, AI-Powered Mindset in Private Equity
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AI in Action: Use Cases for Private Equity Firms
FAQs
What types of portcos do you work with?
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.
How do you tailor AI strategy to the exit horizon?
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.
Do you work with portfolio operations or directly with portco leadership?
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.
Can you bring a consistent playbook across multiple portcos?
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.
Do portcos need clean, centralized data before deploying AI?
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.