The PE Playbook for Unlocking Trapped Value in the AI Era
Activating Underutilized Assets, Processes, and Data
By Thomas Thayyil Thomas, Co-Founder & CEO, Teragonia
For decades, private equity has mastered the art of finding and fixing inefficiency. The classic playbook—financial engineering, operational tightening, professionalized management—created enormous enterprise value. But those levers are no longer enough.
Multiples are high. Hold periods are short. The easy gains have been captured. And in the AI era, every portfolio company sits atop oceans of underused data that traditional playbooks simply weren’t built to exploit.
The next frontier of value creation isn’t about squeezing more from capital or cutting more from cost. It’s about activating what’s already there—the trapped value inside underutilized assets, misaligned processes, and disconnected data.
That shift demands a new discipline: Value Orchestration.
The Limits of the Old Playbook
Traditional PE value creation strategies were built for a different era—an era when visibility was the bottleneck. Dashboards, shared services, and KPI frameworks all aimed to give leadership a clearer picture of performance.
But in most portfolio companies today, visibility isn’t the problem. Operators are drowning in information. Every function—finance, sales, operations—has its own metrics, reports, and AI tools. The problem is that none of them move in sync.
Legacy playbooks tend to:
- Analyze more than they act. BI dashboards explain what happened but rarely dictate next steps.
- Optimize in silos. Finance protects cash; sales chase volume; ops chase throughput—without a common language for margin.
- Operate episodically. Quarterly reviews and board decks drive bursts of focus, followed by long gaps of drift.
- Treat AI as a pilot, not a practice. Experimenting with content generation or forecasting, but rarely linking AI output to execution or measurable EBITDA.
The result is familiar: value creation that looks smart on slides but plays out too slowly to hit targets.
“The real opportunity lies in embedding AI into the operating model itself—where it monitors performance signals across the business, learns from outcomes, and continuously aligns people and processes around what matters most.”
Why AI Has Changed the Game
AI has upended the tempo of competition. Market conditions, pricing dynamics, and cost structures now evolve daily. The firms that win aren’t those with the most dashboards—they’re the ones that turn intelligence into action before the window closes.
But most “AI in PE” efforts still sit at the surface level: chatbots, marketing content, summarization tools. Those projects demonstrate technical curiosity, not strategic advantage.
The real opportunity lies in embedding AI into the operating model itself—where it monitors performance signals across the business, learns from outcomes, and continuously aligns people and processes around what matters most.
That’s the leap from Business Intelligence to Value Orchestration.
What Value Orchestration Looks Like
Value Orchestration is a continuous discipline that transforms data into prioritized, coordinated action. It closes the loop between signal, decision, and execution—turning intelligence into measurable value lift.
Instead of waiting for quarterly performance reviews, Value Orchestration systems operate in real time. AI models surface the most urgent levers—margin drift, pricing anomalies, supply risk—and route them to accountable owners. Each action is tracked, measured, and refined, creating a living feedback loop of performance.
Where the old playbook relied on dashboards and discipline, Value Orchestration adds orchestration and speed:
Legacy PE Levers | Value Orchestration Levers |
Financial engineering | Execution intelligence |
KPI dashboards | Real-time signal loops |
Cost reduction | Margin amplification |
Quarterly cadence | Continuous responsiveness |
Function-specific tools | Cross-functional alignment |
Human reporting lag | AI-driven prioritization |
With Value Orchestration, PE firms and their portcos stop managing from behind the data. They act in rhythm with it.
Turning Data Infrastructure into EBITDA Infrastructure
Over the last decade, most PE-backed companies have built out modern data stacks—Snowflake, Fivetran, dbt, Power BI, Tableau. But these investments often stop short of impact. The data is clean, stored, and visualized—but not activated.
That’s the missing layer Value Orchestration provides.
Teragonia’s Astradis™ platform, powered by the FibronAI orchestration core, connects financial and operational data streams into one adaptive layer. It continuously scans for value leakage—pricing erosion, working capital drag, cost-to-serve spikes—and triggers orchestrated responses across teams.
Instead of dashboards that tell you what happened, AstradisAI tells you what to do about it—and coordinates the action across Finance, Revenue, Product, and Service functions.
This is how AI moves from an experiment to a force multiplier—amplifying human judgment instead of replacing it.
The Cost of Standing Still
The biggest risk for private equity today isn’t failed deals—it’s missed timing. Value that should have been captured slips away in the gap between knowing and doing.
Without orchestration, portfolio companies face:
- Margin decay that compounds invisibly between reporting cycles.
- Slow decision cascades where insights die in PowerPoint decks.
- Execution drift as teams chase conflicting KPIs.
- AI fatigue from pilot programs that never translate to results.
Meanwhile, competitors who have embedded AI into their operating fabric are compounding advantage daily—adjusting pricing, reallocating working capital, and tightening cost-to-serve faster than others can react.
In an environment where deal cycles are shorter and competition is smarter, delayed action equals diluted returns.
Continuous Orchestration as the New Standard
The firms that adopt Value Orchestration early are building a different kind of operating muscle—one that never stops learning, aligning, and acting.
They don’t wait for the quarter to close to see where value was lost. They see it as it happens and fix it before it hits the P&L. They don’t rely on isolated data teams to interpret the numbers; the system itself flags priorities and coordinates response.
This isn’t a management fad—it’s the operating system for modern private equity:
- Always-on visibility into margin drivers.
- Real-time accountability across teams.
- Embedded AI that learns from every cycle of execution.
- Direct linkage between data investments and EBITDA outcomes.
When every decision compounds in the same direction, the traditional notion of “value creation plan” gives way to value creation flow.
“The firms that adopt Value Orchestration early are building a different kind of operating muscle—one that never stops learning, aligning, and acting.”
A New Era of Value Creation
The legacy PE playbook built extraordinary businesses. But it was designed for a slower world—one where decisions could wait, and visibility was scarce.
Today, AI has made visibility abundant and time scarce. The firms that thrive will be those that move from analyzing value to orchestrating it—every day, across every lever of performance.
That’s the promise of Value Orchestration: turning the modern data deluge into a coordinated system of action that drives measurable, repeatable growth.
Because in private equity, the clock doesn’t start ticking when the deal closes anymore.
It’s already ticking—and trapped value waits for no one.
A proven business builder, innovator and M&A advisor with significant global experience, and adept in quantitative techniques and technology, Thomas brings forth a unique set of perspectives and capabilities to boost the systemic efficiency of fast-growing enterprises. Thomas has been a trusted advisor throughout his professional services career to several financial sponsors, sovereign wealth funds and Fortune 100 corporations, throughout the M&A life cycle from deal sourcing, deal execution, post-close value creation, to exit.
Foundational Tech Infrastructure
Our core analytics and AI platform drives informed decision-making with enhanced clarity and focus, and rapidly unlocks enterprise value
Core Features:
Connect All Your Data Sources
Integrate data from multiple source systems effortlessly
Critical for breaking down silos and creating a unified view
One Trusted Data Source
A secure, centralized cloud hub for all your data insights
Foundational for reliable decision-making and enterprise-wide alignment
Interactive Dashboards
Visualize complex data through easy-to-understand dashboards
Empowers leaders with actionable insights
Enriched Data Flow, Fully Automated
Reverse ETL capabilities enriches your data and ensures your data flows exactly where it is needed for function teams to act on
Enables real-time, action-oriented data flow
Additional AI capabilities are actively in development
Scott Briggs
BS International Business | American University of Paris
BS Computer Science | American University of Paris
Seasoned DevOps and infrastructure engineer with expertise in AWS, Kubernetes, and Terraform; led cloud migrations and scalable infrastructure projects at Sfara, FanDuel, and Kickstarter.
With over 15 years of experience in small and medium-sized startups, Scott is a seasoned expert in designing, optimizing, and maintaining robust, scalable, and secure infrastructure. He specializes in automation and embedding security from the ground up, consistently delivering reliable systems tailored to meet dynamic business requirements.
Prior to joining Teragonia, Scott made a significant impact at Sfara, where he built the company’s entire infrastructure from scratch. He engineered systems capable of supporting hundreds of thousands of users with seamless scalability, implemented automated development pipelines, and introduced observability tools to monitor and manage resources effectively. Additionally, Scott led the infrastructure team in achieving ISO27001 security certification, ensuring security was integrated into every aspect of the system and transforming it into a critical asset for business-to-business operations.
Beyond his technical expertise, Scott has a proven track record of managing and mentoring high-performing teams. As a Senior DevOps Engineer at FanDuel, he gained invaluable experience in scaling infrastructure and optimizing resources to support millions of daily users, aligning technological capabilities with organizational goals.
Jack Amedio
Master’s in Human Resources | University of Illinois
Bachelor’s in Management | Loyola University
Former Financial and Operations Manager at Houlihan Lokey, Golin Harris, and MSL Group.
Jack is a highly driven, cross functional professional with extensive experience in operations and administration.
Prior to joining Teragonia, Jack held financial and facilities management roles for Houlihan Lokey, MSL Group/Publicis, and Golin Harris in which managed and created processes and trainings for multiple functional areas ensuring operational and administrative procedures were well planned, efficient, cost-effective, and aligned with business objectives while ensuring initiatives, internal events as well as client events propelled employee and client engagement.
Jack holds undergraduate degrees from University of Illinois and Loyola University Chicago and has completed graduate certificates in Business Administration, Strategic Human Resources, and Operations at Cornell, CUNY-Buffalo, and University of Illinois and is in the process of completing a Master’s in Human Resources at Loyola University Chicago’s Quinlan School of Business.
Mason Taylor
MS Analytics | Georgia Institute of Technology
BS Management Information Systems | Oklahoma State University
Former analytics engineer at Cyderes and ConocoPhillips with a Master’s in Analytics from Georgia Institute of Technology and a Bachelor’s in Management Information Systems from Oklahoma State University
Mason is an Analytics Engineer with deep experience in data analytics, business intelligence, machine learning, and cybersecurity. He brings a proven track record of leading analytics engagements spanning architecture, insights, visualizations, and delivery.
Before joining Teragonia, Mason was a Senior Analytics Engineer at Cybersecurity MSSP CYDERES where he built a scalable, standardized, and secure analytics architecture for over 300 clients across many industries and consulted with them to deliver insights through bespoke data driven solutions. In addition, he managed the data delivery of the insight platform leveraged by the Security Operations Center to respond to incidents in a timely and effective manner.
Prior to joining CYDERES, Mason worked in ConocoPhillips’ Analytics and Innovation Center of Excellence holding varied roles within the Data Analytics organization from Data Engineering, to Business Intelligence, and Data Science. He delivered robust data solutions in all operating units for various functions including Engineering and Production, Finance, IT, and more. Including projects to standardize cost and production data across operating units.
Mason started his career at The Williams Companies in cybersecurity and transitioned to cybersecurity at ConocoPhillips where he found his passion for Data Analytics through SIEM management, detection engineering, and threat intelligence.
Grace Sun
Bachelor’s in Finance & Accounting | Georgetown University
Former analytics engineer at Houlihan Lokey and financial analytics at JP Morgan Chase with a Bachelor’s in Finance & Accounting at Georgetown University
Grace is a seasoned analytics engineer with specialized expertise in crafting and implementing analytics solutions that drive agile, informed executive decisions in M&A and value creation for private equity-backed companies.
Before joining Teragonia, Grace was a part of the data science and business analytics team at Houlihan Lokey. She has excelled in harmonizing, enriching, and analyzing data from diverse sources, providing key insights that enabled private equity investors and portfolio company executives to make rapid, data-driven decisions across the investment lifecycle. She has developed novel analytics solutions, including deal sourcing and evaluation tools for platform investments that employ a buy-and-build or de novo growth strategy, as well as post-close value creation and KPI reporting tools for operators and management teams.
Grace has also worked at JPMorgan Chase & Co. in the Global Finance and Business Management rotational program, where she built analytics solutions to evaluate banker attrition and KPI reporting within the Global Private Bank.