AI for private equity

AI for private equity portfolio companies.

Deal-side AI covers the fund: sourcing, diligence, monitoring. Codos covers the portfolio company, where AI changes the cost base that drives EBITDA. For operating partners and portco CEOs: a 30-day diagnostic, automations in production, and savings verified weekly against a baseline finance signs.

See the portfolio playbook
Engagement start
30-day diagnostic on one portco. Either side can stop at day 30.
Built for
Operating partners and portco CEOs, 300–5,000 people
Impact accounting
Baseline agreed with finance, verified weekly
Deployment
On-prem: data stays on the portco’s servers
Backed bya16z Speedrun
Builders fromMcKinsey & CompanyMetaTesla
$5M+verified client impact

The two levels

Two levels of AI in private equity.

At the fund, AI is deal-side software: sourcing and screening, due diligence and data rooms, IC memos, portfolio monitoring, LP reporting. A mature market of platforms serves that work. Codos does not compete in it.

Inside a portfolio company, AI is an operating change: agents and automations in the central functions (finance operations, customer support, back office, supply chain), so the same revenue runs on a smaller cost base.

Codos works inside the portfolio company. The buyer is the operating partner or the portco CEO and CFO. The engagement is the same AI transformation consulting system, software plus forward-deployed engineers, pointed at one portco at a time.

Why programs stall

The deployment gap.

PE funds did not skip AI. Most portfolios are full of licenses and pilots. What is missing is deployment: workflows that run differently, and savings a CFO can verify.

01

The pilots clear their business cases.

In FTI Consulting’s May 2026 survey of 200 PE fund and operating leaders, 95% of AI initiatives met or exceeded their business case. The same report calls portfolio-wide penetration low. The pilots work, but the portfolio does not feel them.

02

The portfolio P&L stays flat.

In “The AI-First Private Equity Firm” (January 2026), BCG finds that few firms can show meaningful AI returns across their portfolio companies. Licenses without changed workflows produce little P&L impact. The gap is operational, not technological.

03

Closing it is an operating job.

The gap closes inside the portco: pick the workflows where AI changes the economics, build the automations to production, and verify the savings weekly against a baseline finance signed. That is the playbook below.

How it works across a portfolio

Diagnose. Map. Run. Repeat.

Pilot at one portfolio company, then carry the playbook across the portfolio: the same diagnostic, the same brain, the same weekly review on every portco.

01

Diagnose: 30 days on one portco.

Agentic interviews with leaders and employees, while forward-deployed engineers validate data and systems. You walk away with a workflow map, an ROI-ranked initiative list, and a baseline agreed with the portco’s finance team. The engine is the same 30-day readiness diagnostic, pointed at one portco.

02

Map: a brain per portco.

Approved sources (docs, mail, CRM, meetings) become a living ontology of the business: people, workflows, metrics, commitments, events. Agents and leadership work from it, deployed as a company brain for each portfolio company.

03

Run: cost base to weekly verified savings.

Engineers ship the highest-ROI automations with process owners, and the AI Office reviews impact with the C-suite every week: annualized impact, capacity unlocked in FTE, an owner and next action per initiative.

04

Repeat: the playbook crosses the portfolio.

Wins on the first portco become the playbook the next one starts from: same diagnostic, same brain pattern, same impact-accounting standard. The operator model behind it: one AI operator across the portfolio.

05

On-prem: data stays in the portco.

Codos deploys on the portco’s own infrastructure. Portfolio financials and customer data never enter public AI tools that train on their content.

Questions operating partners ask

Before the first portco.

Two layers. The GP runs deal-side platforms for sourcing, due diligence, and portfolio monitoring, a mature software market. The portfolio companies run AI inside their operations: agents and automations that change the cost base. Codos works on the second layer: a 30-day diagnostic, a company brain, and an AI Office that reviews verified savings weekly.

Due diligence, data rooms, and deal sourcing are the GP layer, served by specialized deal-side platforms. Codos does not compete there. We start post-close, on the operating side of the portfolio company, where the value plan has to become real workflows.

The baseline is agreed with the portfolio company’s finance team before anything is built. From there the AI Office runs a weekly C-level review: annualized impact, capacity unlocked in FTE terms, and every initiative with an owner, a blocker, and a next action. Freed capacity is not called savings until the financial mechanism is visible.

Yes. Codos deploys on-prem, and all data stays on the client’s servers. Portfolio financials, customer records, and board material never enter public AI tools that train on their content.

The diagnostic takes 30 days on one portfolio company. After it, one core workflow is rebuilt end to end every two months, with the company brain and an AI Office review behind it. Wins on the first portco become the playbook the next one starts from.

The first portco

Start with one portfolio company.

The 30-day diagnostic gives an operating partner a decision-ready picture of one portco: the workflow map, the cost base, and a ranked initiative list. You keep all of it, and either side can stop at day 30.

founders@codos.ai