Fastly (FSLY) investor relations material

Strategic Direction and Platform Evolution

• Transitioned to a unified, global edge cloud platform with six product suites, focusing on performance, security, compute, and AI-driven outcomes, and a $22B TAM.

• Shifted from selling individual products to outcome-driven, multi-suite platform adoption, doubling large customers using four or more suites from 7% to 30% in two years.

• Enhanced usability and accessibility, democratizing the platform for broader enterprise and AI agent use, with simplified UI/UX and business intelligence dashboards.

• Expanded into under-penetrated verticals (industrials, financial services, pharmaceuticals) and geographies (India, LATAM, Middle East, Malaysia, Thailand), leveraging partnerships and local infrastructure.

• Leveraged AI-driven innovation, with AI traffic growing 6.5x faster than human traffic, and introduced new controls for AI bot management and API security.

Financial Performance and Guidance

• Achieved three consecutive quarters of 20%+ YoY revenue growth, five quarters of improving NRR (117% last quarter), and first year of profitability with 15% operating margin.

• 2029 targets: $1.1B–$1.3B revenue (14–21% CAGR from 2026), 67–71% gross margin, 20–22% operating margin, and 12–15% free cash flow margin, with CapEx at 10–12% of revenue.

• Maintained robust free cash flow generation, with $34M LTM FCF and FY2026 guidance of $40–50M.

• Capital-efficient network and disciplined OPEX leverage expected to drive 700–1,000 bps of operating margin expansion by 2029.

• New financial reporting will consolidate revenue lines and introduce multi-product adoption metrics, reflecting the unified platform approach, starting in 2027.

Product Innovation and AI Opportunity

• Security portfolio expanded from one to five products, now present in over half of new business deals; security and Bot Management growing at triple digits.

• Launched Fastly for AI with AI Runtime Control, AI Firewall, and API Enforcement, targeting governance and resilience for enterprise AI adoption.

• Edge Compute strategy focuses on cascade inference—pairing efficient logic at the edge with large models centrally—to make AI adoption economically viable at scale.

• Positioned edge as the control point for AI, inspecting 130,000+ apps and APIs through its security layer.

• Ongoing co-innovation with customers drives product development, scaling outcome-driven solutions and expanding platform on-ramps.