Juniper Square Acquires Sightglass to Bolster AI Capabilities for Private Markets Investor Relations

WHY THIS MATTERS
Juniper Square’s acquisition of Sightglass targets one of the most time-consuming and underestimated bottlenecks in private markets: due diligence questionnaires. As institutional capital flows increase, LPs are demanding deeper, more detailed disclosures, turning DDQs into complex, multi-team efforts that can take dozens of hours to complete.

By embedding AI directly into this workflow, Juniper Square is addressing a clear pain point for investor relations and operations teams. Automating ingestion, drafting, and verification of responses not only saves time but improves consistency and auditability. In a market where trust and accuracy are critical, having source-linked, verifiable answers can materially improve how firms present themselves to investors.

This also reflects a broader shift in private markets toward data centralisation. By connecting DDQ automation to existing investor and fund data, firms can move away from fragmented workflows and toward a unified system where information is reused, validated, and continuously improved.

Juniper Square, the operations partner to more than 2,000 GPs, today announced the acquisition of Sightglass, an AI-native due diligence questionnaire (DDQ) automation company. The acquisition reinforces Juniper Square’s position as the all-in-one provider capable of helping finance and investor relations teams unify their data across workflows and adopt purpose-built AI.

The Sightglass technology addresses the single most requested technology need from investor relations teams today.

“IR teams are currently drowning in a growing volume of complex diligence requests, and generic tools simply cannot parse the terminology and nuance of institutional private markets,” said Jay Farber, General Manager, GPX. “This is not just a product addition; it is a strategic expansion of our AI platform. By connecting DDQ automation to the investor and fund data already inside Juniper Square, we are helping firms deliver accurate, audit-trailed responses in a fraction of the time.”

As institutional fundraising becomes more competitive, the burden of due diligence has reached a breaking point. Standard frameworks have nearly tripled in complexity, often requiring 40 to 60 hours of manual work across IR, finance, compliance, legal, and other operations teams to respond to a single request. By integrating Sightglass’s agentic AI directly into the Juniper Square platform, GPs can now automate these high-stakes workflows, reducing response times by up to 90 percent while ensuring 100 percent source-verified accuracy.

Unlike horizontal AI tools, the Sightglass technology was built specifically for the private markets. Key capabilities include:

• Automatic ingestion: The app ingests questionnaires in any format and automatically populates the questions inside the platform.
• First-draft completion: AI generates a first draft from the firm’s proprietary knowledge base, enabling teams to start with a nearly complete response.
• Dynamic source modeling: Every answer includes precise page-level citations for instant verification.
• Cross-functional collaboration: The app supports real-time collaboration, allowing users to see teammates’ activity and eliminating the need for version control.
• Human-in-the-loop workflow: Designed for accountability, the system tracks every edit and approval through a full audit trail.

The acquisition marks another milestone in Juniper Square’s ongoing mission to modernize the private markets ecosystem.

“Joining Juniper Square is the natural next step to automate the most tedious parts of fund operations,” said Thomas Buley, Sightglass Founder and CEO, now Director of Product Management at Juniper Square. “The firms that win the next decade of fundraising will be those that leverage their own relationship history and data narrative to respond to LPs with unprecedented speed and accuracy.”

FF NEWS TAKE
This is a smart, targeted acquisition. Rather than building generic AI tools, Juniper Square is doubling down on vertical-specific use cases where the value is immediate and measurable. DDQs may not be glamorous, but they sit at the heart of fundraising, and improving this process directly impacts a firm’s ability to raise capital.

The emphasis on audit trails and source verification is key. In regulated, high-stakes environments like private markets, AI adoption depends on trust as much as efficiency. Tools that can show where answers come from, and how they were approved, are far more likely to gain traction.

Looking ahead, this signals where AI is heading in finance: deeply embedded in workflows, trained on proprietary data, and designed to augment domain expertise rather than replace it. Firms that can operationalise their data in this way will have a clear advantage in increasingly competitive fundraising environments.