Ontra

Thank you to everyone who stopped by for Sugar Rush Hour 🍬 . Midtown got a little sweeter for a few hours. We loved meeting so many of you in person!

Headcount hasn't grown. The workload has. PE legal and compliance teams are absorbing more portfolio complexity, more regulatory exposure, and more cross-jurisdictional obligations without meaningful headcount growth. The firms getting ahead aren't doing more with less by chance. They've made deliberate choices about where AI fits in the work. On May 20, Ontra is bringing together practitioners who have already done this. Christopher Vilhelmsen from Holland Mountain, Derek Shanahan from Juniper Square, and Gui Smolarek de Barros from Ontra will cover AI use cases delivering real results across contracting, diligence, and document preparation, and how leading teams are managing expanding fund obligations and regulatory requirements at scale. The session will also address AI governance directly: why firms are formalizing policies now, what state-level AI legislation means for PE, and how to assess AI risk across your portfolio. If you're deciding where your firm's AI efforts should go now, this is the conversation to join. Register via link in the comments👇

A DDQ lands. Someone digs through old submissions. Legal gets pulled in. The whole thing moves through email, and another DDQ arrives before the last ships. The manual workflow has real costs. IR teams spend hours on coordination. Outdated answers slip through the cracks. There's limited visibility into cross-functional progress. And as volume grows, the process doesn't scale. Generic AI and RFP tools don't fix it. They rewrite answers your legal team already approved. They surface responses without context. They fail to account for the specific way private markets investors ask questions. Ontra's DDQ changes that. See how it works: https://lnkd.in/gKXFMq24

We've started calling it the "upload and prompt illusion." A managing director uploads a handful of fund documents, asks a question, gets a surprisingly good answer. A compliance team drops ten side letters into an LLM, extracts investor obligations, walks away impressed. The experiment lands. The firm labels it a success. That's where it gets complicated. A few good outputs from a few documents doesn't tell you how the model holds up across 400 agreements the team hasn't read closely, or what happens when the context window degrades mid-workflow, or how IR collaborates with compliance when neither can reliably build on the other's LLM thread. Most private markets firms that have pushed past the experiment are finding the same thing: reliable operationalization across hundreds of documents, multiple teams, and the traceability LPs, lenders, and regulators expect requires more than a prompt. We wrote about where horizontal LLMs actually break down for PE firms, and what a hybrid tech stack looks like instead. Link in the comments.

Introducing Ontra's AI-powered DDQ solution. Purpose-built for the demands of investor diligence, it helps fund managers complete DDQs with the accuracy and speed institutional LPs expect. Here's how it works: ✅ AI digitizes a trusted answer bank using completed industry templates, DDQs, policy documents, and PPMs. ✅ AI identifies approved answers from precedent or generates a custom response — both traceable to source — for team review. ✅ Assign questions, approve answers, and export completed questionnaires in the LP’s original format. ✅ Find, verify, and reuse the strongest answers to one-off investor questions by searching a precedent library. The solution was co-developed with nine leading private markets firms. More than 65 private markets firms across PE, credit, and real estate enrolled in early access ahead of today's launch. As Ontra CEO and Founder Troy Pospisil puts it: "In this market, your DDQ process is either a competitive advantage or a liability." We built our DDQ solution to make it an advantage. It’s live today. See it in action: https://lnkd.in/gKXFMq24

It was a Hack Day for the books! Hack Day is one of the ways we invest in innovation and cross-functional experimentation at Ontra. The team presented 20+ projects this year. When you give people room to experiment and collaborate across the company, they don't waste it. Tools that had been on the backlog. Ideas that always had a reason to wait. They built them anyway. The problems a team chooses to solve on their own time say a lot about who they are. Ours builds things that genuinely matter to our customers. Thank you to everyone who pitched, built, and showed up.

47% of LPs say they're monitoring how their GPs adopt AI. While a third view AI positively, 46% report mixed views due to risk concerns. Every firm is being pitched something. Each vendor has rehearsed answers for data security, privacy, and accountability. The harder question tends to get skipped: was this AI actually built to do your specific work, end to end, without your team constantly filling the gaps? That one tends to surface on a Friday night. The stakes are rising. LPs are increasingly scrutinizing AI adoption, and general-purpose platforms weren't built to meet that standard. They were built to scale broadly. Private markets legal and compliance work demands depth. Purpose-built in private markets means something specific: designed from the ground up for how teams actually operate, co-developed alongside the very customers who use the tools, with human professionals in the loop. 9 of the top 10 PEI-ranked firms use Ontra. That's not a coincidence. What's the first question your firm asks before committing to an AI vendor?

One way we measure a successful implementation? The weight our customers feel lifted off their shoulders. As an Implementation Manager at Ontra, Stacy Hauser and her team are the ones who get customers up and running on the product, so they can stop spending hours going through documents and start getting instant answers through purpose-built, AI-powered solutions. "For me, it's really about the people," she says. That shows up in what Stacy wants her customers to experience: no more late-night document digs, no more paperwork searches for the one provision someone needs by morning. Just the right answers, verified and in one place.

#DealMAX 2026 delivered. We came to connect with investment banking and deal teams about what's happening in private markets right now. What we heard was consistent: for high stakes workflows, AI that can actually do the work is more critical than ever. When technology can take a manual, tedious process off a team's plate, it's a no-brainer. That's the house edge Ontra is built on. Purpose-built AI for the workflows that keep deals moving, so the people closing them can focus on what actually moves the needle. Thanks to everyone who stopped by and connected with Troy Pospisil, Alan Alaraj, Eman Cheema, Juliet Oskowsky, Sarah Amselem, Tyler Rozas, Tyler Sandifer, Walker Praznik, Hadley Coulter, and Ahisha Stewart in person. The conversations have us excited for what's ahead.

The signing of a credit agreement is just the beginning of the finance team's involvement. Tracking what's in them often lives in scattered spreadsheets, someone's inbox, or a colleague's memory. That's as much a CFO problem as a legal one. Finance teams at PE firms are the ones who have to monitor covenant compliance, prepare reporting packages, and manage cash flow waterfall mechanics. As portfolios scale, the complexity compounds. And yet, many finance teams are still managing this reality with spreadsheets, shared drives, and manual review processes that were designed for a simpler time. The result? A growing gap between the operational demands of modern private credit and the infrastructure most firms have in place to manage it. Insight for Credit closes that gap. Structured, searchable credit data. Upcoming deliverables tracked in one place. The visibility to understand and compare credit agreements, and satisfy commitments to lenders without the late-night document chase. Ready to prepare your finance team for the next stage of growth? Check out the demo: https://lnkd.in/gZKXXnBe