We deliver AI value creation for private equity across the fund and its portfolio companies, from deal research and diligence to use cases sized in EBITDA and used inside the business.
At the fund, GPs and deal teams need better sourcing coverage, faster diligence and a clearer view of the companies they own. Inside each portfolio company, the opportunity spans revenue, service, operations, working capital and the people doing the work.
We address these as two distinct tracks. Fund tools improve investment and oversight decisions. Portfolio-company work changes how the business sells, serves customers and operates, with returns measured in the company’s own numbers.
We work on two tracks. At the fund, research agents, diligence and portfolio reporting improve the investment workflow. Inside portfolio companies, the same selection and measurement discipline travels across different operating contexts, reducing repeated discovery and setup where prior work applies.
Size opportunities against earnings, cash and operating constraints. During diligence, separate evidence available today from assumptions requiring validation after close, then translate the findings into priorities management can own.
Build the selected agents and workflows in the fund’s or company’s approved systems. Reuse tested approaches where appropriate, but validate the data, controls and economics in each company instead of assuming the first deployment will fit everywhere.
Work with operating partners and management teams to put use cases into daily work. Finance, commercial and operations leaders own changed processes, while fund teams gain a consistent view of what is running and what remains blocked.
Track outcomes against a common baseline, rolling company results into a portfolio scorecard. Distinguish estimated opportunity, implemented change and measured financial impact so investment committees can see which results are evidenced and which still need validation.
For GPs, deal teams and operating partners: turn your investment criteria, research and company reporting into better investment decisions.
Investment criteria, market data and company research become verified target lists, account briefs and sourcing priorities for the deal team.
Data-room documents, financials and management interviews become source-linked findings, follow-up questions and an assessment of the target’s AI opportunity.
Company reporting, board materials and investment records become comparable performance views, draft investor updates and early flags for operating partners.
For company CEOs and functional leaders: select and build around the business model, not a fixed list of back-office automations. A distributor, services firm and healthcare operator will have different priorities.
CRM, quote, transaction and customer data become account research, faster proposals, pricing recommendations and signals for cross-sell or customer retention.
Calls, tickets, contracts and service records become faster intake, better routing, quality checks and next actions for customer-facing teams.
Demand, inventory, purchasing and production data become replenishment signals, capacity plans and exception alerts for day-to-day operations.
AP, AR, bank and ledger records become reconciled balances, collections priorities, faster close and a clearer view of cash tied up in the business.
Case files, referral records or field-service documents become use cases such as legal intake, patient scheduling and job documentation, with the controls each business needs.
Company knowledge, role-specific work and operating reports become searchable answers, AI-enabled onboarding and current management reporting, supported by team training.
Built parallel research agents for a lower middle-market private equity fund, grounded in the firm’s underwriting standards. Work that previously took one to two weeks of analyst research became a same-day run, with more than 100 verified companies per thesis. Partners could review broader coverage while keeping judgment over which targets deserved attention.
Redesigned a healthcare group’s patient platform with AI in the blueprint, from intake to billing. Patient data access is scoped by role, so clinical copilots and automation can scale without widening access to protected information. The platform supported growth from about 4,000 to 16,000 monthly transactions, with an AI-ready data model underpinning future workflows.
Turned a firm’s phones, email, CRM and documents into one AI layer that works the caseload. Calls and records become case data, risks reach the right person the day they surface, and routine letters draft themselves. The work spans intake to settlement, bringing daily decision support to every case manager.
Let's discuss your ideas and questions about deploying AI for profitability and growth in your organization.
Meet privately with one of our senior team members to discuss your ideas and questions.
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