
Endava executives told JPMorgan investors Q1 revenue and EPS came in slightly below expectations after an unexpected, one‑off credit concession to a large client and softer-than-anticipated non‑big‑deal pipeline; the company has nonetheless secured three large multiyear engagements — including a disclosed Paysafe deal worth $100m over five years, an insurance client and Toyota Racing Development — that management expects to drive H2 revenue and produce a flat near‑term EPS profile with pickup in Q4. Management framed its go‑forward strategy around Dava Flow — a proprietary AI‑native delivery methodology (human-plus-agent orchestration with governance and pilot-led adoption, not a single platform) — and a newly launched Dava.Rise initiative to fast‑track scale‑up integrations, positioning Endava to capture share in core modernization and AI enablement, particularly in financial services and payments. Payments modernization, real‑time rails and data‑sovereignty work remain key vertical drivers for growth and share‑of‑wallet expansion, while tokenization/stablecoin and agentic commerce are being explored as evolving opportunities.
Endava reported a Q1 revenue and EPS miss driven principally by an unexpected, one‑off credit concession to a significant client that management said was requested to secure future pipeline; the revenue reduction flowed directly to EPS and, absent that credit, EPS would have been in the mid‑range of guidance. Management also flagged slightly weaker conversion in its non‑big‑deal run rate, but disclosed three material multiyear wins — a named Paysafe engagement ($100m over five years), an insurance client and Toyota Racing Development — that it expects to drive H2 revenue and produce a Q4 pickup after a flat near‑term EPS profile. Management positioned Dava Flow as a proprietary AI‑native delivery methodology (human-plus-agent orchestration with governance and pilots rather than a single product) and launched Dava.Rise to accelerate scale‑up integrations; they described agentic efficiencies (example: a scrum reshaped from eight humans to four humans plus four agents) and emphasized core modernization, cloud and payments work as share‑of‑wallet opportunities, with the payments practice referenced at roughly 15% of revenue. Management stressed pilots and governance as preconditions for enterprise AI adoption and said most large deals start service delivery at the next calendar year, implying timing risk between contract signing and revenue recognition. Key risks are repeat client concessions (management calls the event unusual but not impossible to repeat), slower pipeline conversion and delayed deal start dates; primary catalysts to re‑rate are visible billings from the disclosed large deals, demonstrable Dava Flow pilot‑to‑production conversions, and improvement in non‑big‑deal run‑rate metrics.
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