The startup betting AI can unlock a new era of ‘found money’ for enterprises

OnProfit, founded in 2024 by Tony Capasso and colleagues, is emerging from stealth with enterprise-focused AI tools aimed at recovering “found money” by automating sales interactions and addressing coverage gaps; the seed-backed startup counts HomeStory, OEConnection and Commerce as customers and raised a seed round from investors including Lerer Hippeau, SignalFire and Mark VC (amount undisclosed). HomeStory reports a 10% improvement in early-stage connection rates using the platform, which the company says translates to roughly a 20% increase in revenue, positioning OnProfit as a niche revenue-ops SaaS play rather than a market-moving event.

Analysis

Winners are enterprise SaaS vendors, CRM incumbents and specialized AI-revops startups that remove human coverage constraints — they capture incremental revenue (OnProfit claims +10% conversion → +20% revenue) and marginalize labor-heavy sales models. Losers include high-cost sales outsourcing and legacy systems vendors that can't rapidly integrate generative-AI flows; expect pricing pressure on services and headcount budgets as automation substitutes for repeatable outreach tasks.

Competitive dynamics favor platform integrators (Salesforce, Microsoft, HubSpot ecosystems) and vertical AI players that embed into existing workflows because switching costs remain high; market share will shift gradually over 6–24 months as pilots scale. Supply/demand: demand for AI-revops tools will spike (venture rounds cited: JeevaAI $9m, Nevis $35m) but supply of high-quality labeled revenue datasets and domain-specific workflows is constrained, lifting valuations for differentiated data/moats.

Risk: regulatory (data/privacy, EU AI Act) and model-misbehavior are tail risks that can slow deployments within 3–12 months; operational risk includes overfitting to current seller behaviors leading to churn. Catalysts that can accelerate adoption: 1) measurable ROI case studies (≥15% revenue lift within 6 months), 2) major CRM vendors bundling similar features — either will compress startup exit timelines or force M&A.

Contrarian angle: market assumes tech alone wins; real moat is business process integration and change management — startups without GTM depth will fail. Historical parallel: sales automation waves (SFA in 2000s) favored incumbents that acquired point players; expect consolidation (M&A) within 12–36 months and a temporary premium on small AI-revops vendors that can demonstrate repeatable unit economics.

Key Decisions for Investors

• Establish a 2–3% long position in Salesforce (CRM) over the next 30 days to play platform-led capture of AI-revops demand; target 12–18% upside in 6–12 months if management signals product bundling or material pilot wins (>15% revenue lift).
• Add 1–2% long position in Goldman Sachs (GS) within 60 days — buy thesis: fee income tailwinds from asset-management/ETF distribution (Innovator Capital deal) and M&A advisory in consolidation; target 6–10% upside in 9–12 months and trim if ROE falls below 8%.
• Implement a pair trade: long CRM (1.5%) / short ManpowerGroup (MAN) (1.0%) to be beta-neutral; rationale: automation reduces marginal need for staffing in sales functions over 6–18 months. Rebalance if MAN outperforms by >5% in 30 days.
• Buy a 6–9 month 20% OTM call spread on CRM sized at 0.5% of portfolio to leverage adoption inflection; cap max loss to premium paid and take profits if spread value doubles or CRM rallies 15%.
• Reduce direct exposure to labor-intensive sales vendors by 1–2% and monitor EU AI Act and FTC enforcement for 30–90 days — if restrictive rules (e.g., strict data-use limits) are announced, cut net long AI-revops exposure by 50% within 7 trading days.