# Keye – AI-Powered Due Diligence Platform for Private Equity > Source: > Published: 2026-06-25 17:31:55+00:00 [Agentic Finance Startups](https://www.narracomm.com/category/companies-startups/ai-startups/ai-fintech-startups/agentic-finance-startups/)| [Agentic Infrastructure Startups](https://www.narracomm.com/category/companies-startups/agentic-infrastructure-startups/)| [AI Fintech Startups](https://www.narracomm.com/category/companies-startups/ai-startups/ai-fintech-startups/)| [AI Startups](https://www.narracomm.com/category/companies-startups/ai-startups/)| [Companies/Startups](https://www.narracomm.com/category/companies-startups/)| [FinTech Startups](https://www.narracomm.com/category/companies-startups/fintech-startups/)| [New York City AI Startups](https://www.narracomm.com/category/companies-startups/new-york-city-ai-startups/)| [New York State Startups](https://www.narracomm.com/category/companies-startups/new-york-state-startups/) # Keye – AI-Powered Due Diligence Platform for Private Equity Keye develops an AI platform that transforms raw deal files from virtual data rooms and CIMs into structured, calculation-backed analyses, cohort models, trend detection, and audit-ready outputs for private equity investors. Founded in 2024 and based in New York, the company targets workflow bottlenecks in buy-side due diligence. **Founded**: 2024 (YC F24)** HQ**: New York, NY** Stage**: Seed-stage with early commercial traction** Core Focus**: Deterministic AI automation for private markets diligence **Core Data Grid** | Funding Round | Lead Investors / Notable Backers | Total Raised (approx.) | HQ Location | Industry Sector | Estimated Team Size | Key Partners / Validation | |---|---|---|---|---|---|---| | Seed (2025) | Sorenson Capital (lead); General Catalyst, Y Combinator, ERA, Tiferes Ventures, Dunamu & Partners, Palm Drive Capital; angels incl. Kaz Nejatian (Shopify COO), Philip Rathle (Neo4j CTO), Clark Valberg (ex-InVision CEO), PE practitioners | $5M+ (Seed rounds, 2024–2025) | New York, NY | AI Software / Private Markets Technology / Fintech | 11–50 (expanding post-seed) | SOC II Type 2 certified; zero data retention, no training on customer files; end-to-end encryption; deployed with PE funds representing $1.4T+ AUM; testimonials from $5B–$45B+ AUM funds | ## Keye Leadership & Structural Breakdown **Key Leadership**: [Rohan Parikh, CFA](https://www.linkedin.com/in/parikhrohan)– Co-Founder & CEO. 6+ years front-office investment banking (IB/Global Markets); promoted to Director with 7x deal flow/revenue growth. Prior Accenture consulting and S&P credit roles. Wharton MBA + Master’s in Financial Engineering. [Conor Brown](https://www.linkedin.com/in/conor-brown-9a02849b/)– Co-Founder & COO. Previously co-founded SecureFlow (M&A funds flow and deal insights platform). Wharton MBA. Combined founder experience spans due diligence and transactions exceeding $20B at Vista Equity Partners (PE), Goldman Sachs, and Natixis. [Lalit Lal](https://www.linkedin.com/in/lalitlal/)– Co-Founder & CTO. 7+ years leading engineering teams at AI companies (ads, robotics, pharma); multiple prior ventures achieved PE exits. Focus on production-grade SaaS AI systems. **Primary Competitors**: [AlphaSense](/directory/alpha-sense) (AI market intelligence and research platform for investors), [Hebbia](/directory/hebbia) (AI workspace for complex document analysis and financial workflows), [Luminance](/directory/luminance) (AI for legal/contract review and diligence documentation). **Core Use Cases & Market Problem**: - PE teams conducting financial and operational due diligence on acquisition targets. - Automating data extraction, cleaning, cohort/retention analysis, margin/compression identification, anomaly flagging, and custom modeling from messy, unstructured files. - Producing traceable, Excel-exportable, IC-ready outputs that reduce manual effort while maintaining audit-grade transparency. **Plain English Explanation** Keye applies specialized AI to private equity deal data, automatically performing the quantitative heavy lifting—building retention cohorts, running calculations, detecting trends and anomalies, and synthesizing insights—that analysts traditionally complete manually in spreadsheets, while preserving full source traceability and eliminating calculation errors or hallucinations. **Target Customers & Adoption Context** Primary buyers and users are due diligence teams (associates to partners) at private equity funds. It removes the central friction of capacity-constrained, inconsistent manual synthesis from high-volume, disorganized data rooms, allowing teams to rigorously evaluate more deals without proportional increases in headcount or quality degradation. Early adoption includes mid-market to large funds. **Capital & Traction Signals** Closed $5M Seed in 2025 led by Sorenson Capital with participation from General Catalyst, Y Combinator, and strategic angels (tech operators + PE users). Platform shows commercial traction through adoption by funds with $1.4T+ aggregate AUM, generation of 1M+ analyses monthly, and reported multi-day time savings per deal. Post-raise activity centers on engineering expansion and BD/sales hiring. Enterprise-grade security posture (SOC II Type 2, zero-retention architecture) functions as a key validator for institutional PE buyers. **Investor Lens** In the current 2026 private markets environment of selective deployment, elevated entry scrutiny, and LP demands for operational efficiency and alpha, tools that compress diligence timelines while delivering consistent, auditable outputs represent practical infrastructure for higher-velocity capital deployment. Validation signals are material: backing from General Catalyst and Sorenson Capital, YC pedigree, and direct usage/investment by PE practitioners among angels confirm domain authenticity and product-market fit. The team’s combination of front-line IB/PE operational experience (Vista, Goldman) and AI engineering execution from exited companies de-risks delivery in an accuracy-critical vertical. Momentum factors include quantified user outcomes (deal throughput gains) and visible post-seed hiring velocity, aligned with financial services AI productivity tailwinds. Watchpoints include execution risk in long-cycle, relationship-driven PE enterprise sales and the need for sustained differentiation versus general AI research platforms expanding into workflow layers. Public signals indicate focused defensibility through workflow-specific deterministic automation and a security model tailored to sensitive institutional data. **Last Updated**: June 2026 **Sources**: - https://www.keye.co/ - https://www.ycombinator.com/companies/keye - https://fintech.global/2025/07/29/private-equity-ai-platform-keye-emerges-with-5m-seed-round/ - https://www.linkedin.com/company/keye - https://www.crunchbase.com/organization/keye - Public funding aggregates and customer metrics reported on company channels