← case studies
Published
June 2026

How a PE IT-Services Portfolio Cut SOW Time 50–60%

Service directors across a PE IT-services portfolio spent days writing SOWs from scratch. AI generation from guided inputs and templates now cuts SOW creation time 50–60%.

50–60%

Cut SOW creation time

Not disclosed

Implementation Time

Not disclosed

Project Cost
the challenge
Across a PE-backed IT-services portfolio, companies used manual, inconsistent workflows for proposals, onboarding checklists and internal research. Service directors spent days creating statements of work from scratch out of fragmented systems.
what they built
Casper built AI-powered SOW generation that drafts statements of work from guided inputs and standardized templates, plus company-search automation to retrieve data across portfolio companies and workflow standardization so the approach scales across the portfolio.
Casper targeted the most expensive recurring task: writing SOWs. They built an AI generator that drafts a statement of work from a service director's guided inputs against standardized templates, so a document that used to take days comes together in a fraction of the time. Company-search automation pulls data across the portfolio's fragmented systems, and the workflows were standardized so the same approach could roll out to multiple portfolio companies rather than one-off. SOW creation time dropped 50–60%, with portfolio-wide savings as the pattern scaled.
best fit for
PE platforms and multi-entity services businesses where proposal/SOW creation is manual, slow and inconsistent across companies — and a standardized AI generator can scale across the portfolio.
Ai ROLE
AI drafts the most expensive recurring document. A generator turns guided inputs into a statement of work against standardized templates, while company-search automation pulls the needed data across the portfolio's fragmented systems.
impact

50–60% Faster SOWs

SOW creation time cut by half or more.

Portfolio-Wide Rollout

Standardized across multiple portfolio companies.

Cross-Company Search

Automated retrieval across fragmented systems.

Jay Singh

CEO & Founder
Casper Studios
CEO and co-founder of Casper Studios, a product studio helping companies design, build, and integrate AI-powered products.
Get an intro
Talk to this team
industry
Professional Services
business organization
Sales & Revenue
Operations
AI TYpe
Generative Design & Content
Process Automation (RPA + AI)
value type
Time Savings
Cost Reduction
frequently asked questions
How did a PE-backed professional services portfolio cut SOW creation time 50–60% with generative AI?

The experts targeted the most expensive recurring task, writing statements of work, and built an AI generator that drafts an SOW from a service director's guided inputs against standardized templates. Company-search automation pulls data across the portfolio's fragmented systems, and the workflows were standardized so the same pattern could roll out across multiple portfolio companies. SOW creation time dropped 50–60%.

What AI approach was used for the professional services portfolio?

The work combined generative design and content with process automation (RPA + AI): an AI SOW generator working from guided inputs and standardized templates, plus automated company search across fragmented systems and standardized workflows built to scale across the portfolio.

What results did the professional services portfolio achieve?

SOW creation time fell 50–60%, cross-company search automated retrieval across fragmented systems, and the standardized approach rolled out portfolio-wide across multiple companies rather than as a one-off.

How long did it take to see results?

Results showed up at the task level once the generator was in place, with SOWs that previously took days coming together in a fraction of the time, then compounding as the pattern scaled across portfolio companies.

Who is this AI SOW-automation approach best for?

PE platforms and multi-entity services businesses where proposal and SOW creation is manual, slow, and inconsistent across companies, and where a standardized AI generator can scale across the portfolio.

Have a similar challenge?

Ask whether this would work for you, or describe what you're trying to solve.
TELL US WHAT YOU'RE EXPLORING