Chirag Ved

Chirag Ved, on behalf of Kirk Materne from Evercore ISI, asked about AvePoint's plans to develop a hybrid pricing strategy balancing seat and usage-based models, inquiring about specific platform opportunities and any early feedback from partners or customers. He further questioned how early AvePoint is in terms of customers meaningfully monetizing agent governance in 2026, and what leading indicators signal that AI-driven use cases are becoming a more material ARR driver rather than just AI readiness spending.

Answer

TJ Jiang, Chief Executive Officer, explained that capacity-based licensing already exists for migration and IaaS/PaaS data protection, and it's natural for consumption-based licensing in compute infrastructure (Azure, GCP, AWS). He noted agentic AI deployments might resemble virtual employees with seat counts, but the focus is on maximizing customer value, with IaaS/PaaS expansion leaning towards consumption. He highlighted AgentPulse for multi-cloud agent governance, focusing on risk, access control, and cost monitoring, citing customer concerns about agents racking up large bills. He confirmed the beginning of revenue generation from this need, noting active experimentation with agentic AI and top-of-mind risk, control, and cost for customers.

Chirag Ved from Evercore ISI asked about AvePoint's evolving hybrid pricing strategy, specifically where capacity-based licensing opportunities exist and initial customer feedback, and how early customers are in monetizing agent governance, seeking leading indicators for AI-driven ARR.

Answer

CEO TJ Jiang explained that capacity-based licensing is already used for migration and IaaS/PaaS data protection, and is natural for compute infrastructure. He noted that agentic AI deployments also introduce a 'virtual employee' seat count, but the focus remains on maximizing customer value without major seat count reductions. He confirmed early revenue generation from agentic AI governance, driven by risk, control, and cost monitoring.

Chirag Ved of Evercore ISI inquired about AvePoint's multi-cloud governance strategy for platforms like Salesforce and Google, its market maturity, and the key growth opportunities for the second half of the year related to AI adoption.

Answer

CEO Tianyi Jiang stated that while they have meaningful revenue from backup-as-a-service for Google and Salesforce, the new governance capabilities for these platforms are in early stages. He identified agentic AI governance as the largest growth opportunity for the second half of the year, noting it's a major theme in discussions with large global customers and will be a key focus for the coming quarters.

Chirag Ved, on for Kirk Materne, asked for an update on the progress of companies moving from planning to implementation of data modernization strategies and questioned how long AvePoint expects these modernization tailwinds to persist.

Answer

CEO Tianyi Jiang responded that the market is still in the very early innings of data modernization and AI deployment. He explained that proper implementation requires fundamental business process reengineering, data cleansing, and cultural change, which are difficult and time-consuming tasks, especially for large companies. He concluded that because of this complexity, the trend will take a while to play out.

Chirag Ved inquired about Snowflake's strategic rationale for acquiring Observe and bringing observability capabilities in-house, considering the significant size and complexity of the observability market.

Answer

Sridhar Ramaswamy, CEO, explained that observability, particularly AI observability with agents, is a critical data problem and a natural extension of Snowflake's data platform. He noted that Observe was built on Snowflake, ensuring seamless integration and offering significantly greater efficiency and cost savings compared to traditional observability solutions. This creates a strong value proposition for a large segment of existing Snowflake customers.

Chirag Ved inquired about the strategic rationale behind Snowflake's acquisition of Observe, given the large and diverse observability market, and what market or company trends made this in-house integration sensible.

Answer

CEO Sridhar Ramaswamy explained that observability, particularly AI observability with agents, is a significant and growing market, representing a critical data problem and a natural extension of Snowflake's data platform role. He noted that Observe was built on Snowflake, inheriting its strong data and compute foundation, and offers a value proposition that is significantly more efficient than traditional observability, especially for customers with large data volumes. He highlighted the substantial overlap between Observe's potential customers and existing Snowflake customers as a key driver for the acquisition.

Chirag Ved asked about the typical conversion paths from over 150 AI and Agentic engagements into revenue and the timeline from initial pilot to material ARR contribution.

Answer

Steve McMillan, President and CEO of Teradata, explained that AI workloads are driving significant growth and capacity usage on the Teradata platform, capturing a shift in customer spend towards advanced solutions. He emphasized that operationalizing these workloads is a daily activity, with examples across various industries and deployment models, and AI workloads are a key element for capturing growth in 2026.

Chirag Ved inquired about the typical conversion paths from the over 150 AI and agentic engagements into revenue and the expected timeline from initial pilot projects to material ARR contribution.

Answer

President and CEO Steve McMillan confirmed significant growth in AI workloads on the Teradata platform, capturing a shift in customer spend towards advanced solutions. He explained that operationalizing these workloads is a daily activity, citing examples like on-premise customer sentiment analysis for a bank and cloud-based AI solutions for a European customer. He emphasized that AI solutions are driving platform capacity and usage, with the sales team now fully focused on growth, making AI workloads a key element for capturing growth in 2026.

Chirag Ved asked how enterprise perspectives on on-prem versus cloud deployments are evolving in the age of AI, particularly for data estate modernization. He also questioned whether future cloud growth would be driven more by new customers or by expansion, given the sequential drop in cloud net retention rates.

Answer

President and CEO Steve McMillan noted that customers are increasingly focused on hybrid deployments to leverage data across environments for AI, leading to renewed interest in Teradata's on-prem platform, especially where data sovereignty is key. CFO John Ederer clarified that cloud ARR growth is expected to remain balanced, with roughly 50% from new migrations and 50% from expansions, consistent with previous trends.

Chirag Ved of Evercore ISI asked for the key factors providing confidence in maintaining the full-year ARR guidance, especially given cautious commentary from software peers.

Answer

CEO Stephen McMillan explained that confidence stems from unchanged internal expectations for linearity and having factored uncertainty into the initial pragmatic guidance. He added that the company has line of sight to its execution targets and has de-risked its outlook by removing large 'mega deals' from its forecast.

Chirag Ved inquired about customer sentiment regarding cloud migrations, particularly in light of slower growth from hyperscalers, and asked for factors supporting confidence in the ARR guidance despite a decelerating cloud net expansion rate.

Answer

CEO Stephen McMillan acknowledged deal cycle elongation and more staged migrations, viewing it as an opportunity for Teradata's hybrid platform, evidenced by 30 active GenAI proof-of-concepts. CFO Claire Bramley explained that the 2025 guidance incorporates lessons from 2024, with less reliance on large deals and confidence driven by improved retention rates and better pipeline visibility from go-to-market changes.

Chirag Ved inquired if the shift in cloud migration approach changes Teradata's strategic focus on cloud versus on-premise innovation and contracting. He also asked for clarification on the Q3 recurring revenue beat and the outlook for Q4.

Answer

CEO Stephen McMillan reiterated Teradata's commitment to its 'cloud-first, but not cloud-only' strategy, emphasizing that cloud innovations often benefit on-premise capabilities and that the overall cloud pipeline remains strong. CFO Claire Bramley attributed the Q3 recurring revenue outperformance to timing and a slight benefit from upfront revenue, confirming the full-year guide remains unchanged.

Chirag Ved asked which verticals are adopting UiPath's pre-built Agentic solutions fastest and if the company is moving more aggressively into industry-specific packaged automation. He also inquired about the balance between deterministic and Agentic/LLM-based automation and if this balance is expected to shift materially.

Answer

Daniel Dines, Founder and Chief Executive Officer, confirmed a strong focus on verticalized solutions, particularly in healthcare (revenue cycle management, claims) and financial services (financial crimes, KYC). He views deterministic and LLM-based automation as complementary, with deterministic for well-defined tasks and LLMs for complex, unstructured processes, emphasizing orchestration as key for secure, governed enterprise solutions.

Chirag Ved asked which verticals are adopting pre-built agentic solutions fastest and if UiPath is aggressively moving into industry-specific packaged automation. He also inquired about management's view on the balance between deterministic and agentic/LLM-based automation and if this balance is expected to shift materially.

Answer

CEO Daniel Dines confirmed a strong focus on verticalized solutions, with product and engineering teams reworked to address this, primarily targeting healthcare (revenue cycle management) and financial services (financial crimes, KYC, AML). He emphasized that deterministic and LLM-based automation are complementary, with deterministic used for well-defined tasks and LLMs for complex, document-heavy, or conversational processes, all orchestrated by Maestro for secure and governed enterprise solutions.

Chirag Ved, on for Kirk Materne, asked for a high-level overview of UiPath's competitive advantage and its right to win in the Agentic AI category over the next one to two years.

Answer

CEO Daniel Dines detailed a three-part strategy: 1) Leveraging their existing robot deployments by adding agents with Agent Builder, 2) Adopting an open platform approach by integrating with open-source agent frameworks to avoid vendor lock-in, and 3) Building verticalized solutions, starting with the Peak AI acquisition, for industries like finance and healthcare.

Chirag Ved from Evercore ISI inquired about recurring themes in customer renewals and expansions, particularly which products are driving a greater portion of net new ARR. He also asked about the drivers of the Q3 margin beat and the potential for Q4 upside.

Answer

CFO & COO Ashim Gupta highlighted continued adoption of growth products like IDP and Autopilot, noting the quarter's largest deal had an Agentic component. He also cited Test Suite's momentum in expansions. Regarding margins, he attributed the beat to disciplined execution and efficiency efforts, which support the forecast for reaccelerating free cash flow growth next year.

Chirag Ved, on for Kirk Materne, inquired about how UiPath balances selling its comprehensive automation platform versus core RPA, especially when landing new customers who may only be looking for the core product initially.

Answer

CEO Daniel Dines explained that RPA is a powerful technology and the core principle of the platform, which emulates human users. He positioned the evolution to a broader business automation platform as a natural extension, noting that Generative AI fits naturally into this paradigm, making it a seamless progression from RPA to an AI-powered platform.