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Private equity and portfolios
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100-day AI plan for a newly acquired portfolio company
A 100-day AI plan for a newly acquired portfolio company: a day 0-30-60-100 template with owners, starting with a records inventory taken as metadata only.
A 100-day data plan for a newly acquired 3PL or distributor
A 100-day data plan for an acquired 3PL or distributor: secure access, inventory WMS, TMS, ERP and EDI records, settle rights, then decide what to keep.
A portfolio company got an inbound data request: what the sponsor should do
An AI company asked a portfolio company for its records. A five-step sponsor response, what to say in the first reply, and the mistakes to avoid.
Acquired SaaS customers asking about AI use of their data: how to respond
When a customer asks if you use their data for AI, answer per product and per data type. A response template for software holdcos with acquired products.
Acquiring a company that already licenses its data: what to check
Acquiring a company with data licenses? Check scope, exclusivity, revenue quality, deletion duties, change-of-control rights and limits on future buyers.
Add-on integration checklist: the records section most plans miss
An add-on integration checklist with the records section plans skip: pause deletions, export full histories before tools are cancelled, capture contracts.
Agentic AI in portfolio companies: which workflow records agents need
Agentic AI in portfolio companies runs on workflow history. A map of agent tasks, from dispatch to AP exceptions, to the records that train and test them.
AI diligence questions acquirers ask in 2026
AI due diligence questions for M&A, grouped by data rights, third-party restrictions, AI use and licensing history, with what a weak answer looks like.
AI disruption risk in a software portfolio: how to assess each company
Assess AI disruption risk across a software portfolio with a 1-5 rubric on workflow depth, system of record, data ownership and switching costs.
AI due diligence checklist for private equity deal teams
An AI due diligence checklist for private equity in four groups: exposure, AI in use, data rights for training and governance, plus 12 questions to send.
AI features in acquired products vs licensing records out: a holdco rule
Can SaaS use customer data to train AI? Only where contracts allow. Licensing a vendor's own code, tickets and releases follows a separate rights path.
AI-native roll-ups: how they differ from classic buy-and-build
An AI roll-up strategy moves acquisitions onto shared systems and one data model early. How it differs from buy-and-build on tech, data and deal cadence.
AI readiness assessment for portfolio companies: what to score
An AI readiness assessment for portfolio companies: ten criteria scored 0 to 3, from connected systems to rights and exports, with a next action per band.
AI readiness in PE-backed companies: what operating partners check in 2026
AI readiness for private equity portfolios in 2026: what operating partners check in data foundations, rights, governance and quick wins, company by company.
AI value creation in 3PL and freight roll-ups
3PL roll-up private equity AI starts with records: orders, exceptions, routing and claims in WMS, TMS and telematics. See what to map and preserve first.
AI value creation in home services roll-ups: where the records are
Where AI-ready records sit in a home services roll-up: calls, estimates, dispatch, invoices and callbacks, mapped by system and AI use before integration.
AI value creation in portfolio companies: start with operating records
A record-first AI value creation framework for private equity: screen portfolio operating records, then pick internal AI projects and licensing side by side.
AI value creation in private equity: a playbook for operating partners
Three AI value creation levers for private equity operating partners, where licensing operational records fits in each, and a decision rule per lever.
AI value creation in private equity portfolios: where data fits
AI value creation in private equity has three levers: cost savings, AI revenue and data as an asset. See where operating records fit and how to sequence them.
AI vendor contracts at portfolio companies: data terms to check
AI vendor contract data terms decide whether portfolio records train a vendor's models for free. Check these eight clauses before rollout or renewal.
Asset deal vs stock deal: who owns an acquired firm's drawings?
Asset purchase vs stock purchase records ownership for AEC add-ons: who holds copyright in drawings and project files, and which client clauses override it.
Assignment and change-of-control terms in a data license: plan for the exit
How a change of control clause in a license agreement plays out in a stock sale, asset sale or merger, and which drafting options keep your exit clean.
Auditing customer data terms across acquired vertical SaaS products
A SaaS customer data terms audit shows which records each acquired product may license. Use the six-clause worksheet before any AI data conversation.
Build an AI product on portfolio data or license the records out?
Building an AI product on portfolio data or licensing the records out? Compare cost, time to cash, rights, team and risk, and see when licensing comes first.
Buying a co-packer: diligence on customer contracts, specs and records
Co-packer acquisition due diligence: assignment clauses, who owns recipes and specs, audit history, changeover data and customer concentration.
Buying a company for its records: when the data is the thesis
Thinking of acquiring a company for its data? Apply four tests (rights transfer, depth, linkage, refresh) and see when licensing beats paying for records.
Buying a machine shop: diligence on programs, setups and maintenance logs
Machine shop acquisition due diligence beyond the equipment list: test the program library, setup sheets, tool data, maintenance logs and actual hours.
Can a private equity firm license portfolio company data to AI developers?
Yes, with conditions: the portfolio company, not the fund, is the licensor. Five prerequisites decide whether a sponsor-backed data license can proceed.
Can a sponsor use portfolio company data for its own AI tools?
Sponsor access to portfolio company data usually covers monitoring, not reuse. See which sponsor AI uses need a separate agreement with each company.
Can software holding companies license data across their portfolio products?
Software holding company data licensing, answered: which records each product owns, where customer terms stop you, and which product to license from first.
Can you license data that is collateral under a loan?
Can you license data pledged as loan collateral? Often yes for non-exclusive licenses, but check the lien, negative pledge and IP covenants first.
Cancelling an acquired company's SaaS subscriptions: export first
Before you cancel SaaS subscriptions after an acquisition, export each tool's full history. A checklist by tool type, with history-depth checks.
Centralized vs federated data governance for software holding companies
Centralized vs federated data governance for software holding companies: a side-by-side comparison and the data decisions that should stay central.
Change-of-control and assignment clauses: what they mean for acquired data
How anti-assignment and change-of-control clauses affect customer data after an acquisition: a decision path from deal structure to consent to data-use scope.
Client-owned drawings vs firm records in A&E roll-ups: what can be licensed
Who owns architectural drawings in an A&E roll-up depends on each project contract. See which firm records can be licensed and which designs stay out.
Closing one subsidiary in a group: separating its records
A closing a subsidiary checklist for group CFOs: what the entity owns, what sits in shared systems, who keeps custody, and what to export before cancelling.
Commercial HVAC platforms: consolidating service agreements and BAS data
Commercial HVAC platform integration after tuck-ins: consolidate service agreements first, then BAS access, with a data rights check for every building.
Consolidated legacy archives after add-on acquisitions: what to keep
Before you shut off an acquired company's legacy systems, keep full exports, record links, terms and privacy notices. A checklist for consolidating archives.
Consolidating field service software across home services add-ons
ServiceTitan migration after an acquisition: what moves to the platform, what add-ons usually leave behind, and what to export before you cancel.
Consolidating legacy archives after a buy-and-build: a playbook
Consolidate legacy data after acquisitions with one register: a row per acquired system, its terms, export status and owner. Template and phases inside.
Consulting firm roll-ups: proposals, playbooks and project reviews as assets
Consulting firm roll-ups in private equity: which proposals, playbooks and project reviews count as firm assets, and which client deliverables stay excluded.
CRM and helpdesk consolidation after add-ons: keep the full history
CRM consolidation after an acquisition often drops internal notes, attachments and status history. Use this pre-cutover export checklist to keep it all.
Customer data rights after a home services acquisition
Customer data rights after an acquisition hinge on asset vs stock structure, the seller's privacy notice and customer contracts. What to check first.
Customer-funded development: who owns the code?
Customer-funded development IP ownership turns on the SOW and MSA. How to read the clauses, trace funded code and keep customer-owned work out of a license.
Data as a value creation lever in manufacturing portfolios
A four-factor screen grid for operating partners: rate manufacturing companies on data depth, linkage, rights clarity and effort before adding a data lever.
Data assets in a sell-side data room: what to include
A sell-side data room checklist for data assets: the folders buyers expect, from record inventory and rights evidence to signed licenses and delivery logs.
Data clean rooms vs data licensing for portfolio companies
Data clean room vs data licensing: what leaves the company, who computes, and which portfolio records suit each route, with decision rules for CIOs.
Data governance in PE portfolio companies
Data governance in portfolio companies, made practical: five baseline policies, who owns each, and the evidence an operating partner should ask to see.