Motive IPO: S1 Breakdown

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S1 Deep Dive

Motive in one minute

Motive is rebuilding the physical economy's operational infrastructure from the ground up using AI and unified data—transforming how organizations manage workers, vehicles, equipment, and spend across trucking, construction, logistics, and industrial operations. In a world where fleet operators still navigate fragmented point solutions and disconnected systems built for the office economy, Motive delivers an Integrated Operations Platform that combines dashcams, GPS, fuel cards, and workflow automation into a single system, reducing collisions by 80% and delivering over $175 million in annual savings to customers.

Since its founding in 2013, Motive has pioneered the real-world application of the Physical Operations Graph—proving that connecting atomic-level data across vehicles, drivers, and assets can deliver measurable safety and productivity gains beyond traditional fleet management software. By growing from zero to $501 million in ARR and serving nearly 100,000 customers, Motive has emerged as the dominant data layer connecting the $50 trillion physical economy. With over one million connected vehicles feeding continuous model improvements and 400 full-time data annotators generating tens of millions of labeled events annually, Motive holds the leading AI advantage in mission-critical physical operations.

At the core of Motive's model is recursive AI improvement: a data flywheel that locks in customers with 109-126% net dollar retention, then systematically expands across safety, fleet, equipment, spend, and workforce products. This is achieved through the Physical Operations Graph—eliminating data silos, enabling cross-domain automation, and delivering industry-leading AI precision with minimal false positives. The result is safer operations preventing 170,000 accidents and saving 1,500 lives since 2023, driving 28% ARR growth with durable expansion into larger enterprise accounts generating 37% of total revenue.

Introduction

Motive operates as a physical economy infrastructure company. The company proved that unified data and AI could solve real-world problems in fleet operations—not through point solutions alone, but through recursive operational intelligence. Starting with fleet management software in 2013, Motive has built an integrated platform spanning driver safety, vehicle telematics, equipment monitoring, spend management, workforce automation, and AI vision—all supported by over one million connected vehicles and 400 full-time data annotators. By replacing fragmented legacy systems, disconnected workflows, and manual compliance processes with its Physical Operations Graph and AI-powered automation, Motive aligns with how physical operations should work: safe, productive, and profitable from driver dispatch to asset utilization to fuel card transaction.

This infrastructure powers safety and expansion. Motive's incentives are fundamentally aligned with its customers': the company delivers value only when fleets achieve measurable outcomes through collision reduction, fuel savings, and insurance premium decreases. With proprietary dashcam hardware and purpose-built AI models delivering industry-leading precision with minimal false positives, Motive operates at accuracy levels that allow automated decision-making while maintaining trust. The result is a data-led flywheel: customers adopt Driver Safety for collision prevention, purchase Fleet Management for visibility, add Equipment Monitoring for asset utilization, and expand into Spend Management for cost control. In typical enterprise relationships, product adoption starts with one module but expands across the platform over time—demonstrating steadily accelerating cross-sell and deepening customer lock-in reinforced by 110-126% net dollar retention rates.

The market shift is foundational. The physical economy Motive serves represents $50 trillion in annual output—approximately 50% of global GDP—yet organizations remain underserved by legacy technology and face ongoing safety risks, labor shortages, and rising input costs requiring operational transformation. Motive is positioned for this inflection point: the company has grown ARR from zero to $501 million since 2013, prevented over 170,000 accidents and saved 1,500 lives since 2023, and serves nearly 100,000 customers across construction, trucking, logistics, oil and gas, and manufacturing—using recursive AI improvement and a unified data layer purpose-built to become the infrastructure connecting workers, vehicles, equipment, and spend across the entire physical economy.

History

Motive began with a direct challenge to fleet management orthodoxy: physical operations could run on unified data and AI, not just disconnected point solutions. For decades before Motive's founding, fleet safety and management operated on fragmented legacy systems built for the analog era—paper logbooks, standalone GPS trackers, manual incident reviews, and siloed expense tracking. Fleet managers waited days to investigate accidents. Operators paid thousands per vehicle in insurance premiums and compliance overhead. Safety teams struggled to prevent collisions at scale. The infrastructure was expensive, reactive, and opaque by design.

Shoaib Makani, founder and CEO, saw an opening. After working on autonomous vehicle technology at Google and Quanergy, he recognized that AI-powered dashcams could do more than record video—they could become the foundational data layer for the entire physical economy. In 2013, Motive launched (originally as KeepTruckin) with a thesis that connected hardware and purpose-built AI could automate fleet operations end-to-end, cutting collisions by 80% while recording every driver event, vehicle movement, and transaction transparently in a unified graph. The model was intentionally contrarian: build proprietary hardware rather than license commodity sensors, replace manual safety reviews with algorithmic event detection, and create an integrated platform where insights compound with every connected asset.

What started as an electronic logging device for Hours of Service compliance evolved into vertically integrated physical operations infrastructure. Motive launched its AI Dashcam in 2018, detecting safety events with industry-leading precision while competitors struggled with false positive rates that made their systems unusable. By 2022, the company had proven the technology worked at scale and expanded beyond safety—launching Spend Management with the Motive Card, then Equipment Monitoring, then Workforce Management. Product adoption accelerated: from one module focused on compliance to six products spanning the entire operational stack, with Large Customers (over $100,000 ARR) growing from 234 at year-end 2023 to 494 by September 2025.

In 2024, Motive's Physical Operations Graph reached an inflection point as a unified data layer connecting workers, vehicles, equipment, and spend across mission-critical workflows. This completed the vertical integration—from dashcam footage to GPS tracking to fuel card transactions to payroll—all flowing through recursive AI models trained on over one million connected assets. More vehicles generated more labeled training data, which improved model accuracy, which enabled more automation, which attracted more customers deploying additional products. The infrastructure compounded: customers adopted for collision prevention, expanded for fleet visibility, and scaled across equipment monitoring and spend management as the platform demonstrated measurable ROI.

Risk factors

Motive operates in a rapidly evolving physical operations platform market, where execution risk, AI reliability, and competitive intensity can materially impact growth trajectory and profitability. Below are the primary risks associated with Motive's business model.

History of Losses and Uncertain Path to Sustained Profitability

Motive has incurred net losses in every fiscal year since inception: $109 million in 2023, $153 million in 2024, and $139 million in the nine months ended September 2025, with an accumulated deficit of $978 million. Substantial investments in AI development, product expansion across six modules, and public-company compliance continue to pressure margins. While ARR grew 28% year-over-year to $501 million as of September 2025, sustained profitability remains uncertain.

Customer Concentration and Non-Guaranteed Renewals

Large Customers (over $100,000 ARR) generated 37% of total ARR as of September 2025, indicating accelerating revenue concentration in enterprise accounts. While standard agreements automatically renew, customers can prevent renewal with notice, and certain large contracts require affirmative renewals or permit mid-term termination. Loss of a major customer—due to competitive displacement, budget constraints, or union resistance to driver monitoring—could cause sudden revenue declines.

Scaling AI Infrastructure and Managing Technical Complexity

Managing growth from 1,009 employees in 2018 to 4,508 by September 2025 strains Motive's technology stack and recursive AI improvement cycle. The system requires 400 full-time data annotators processing tens of millions of events annually—annotation errors can amplify biases or degrade model accuracy. If Motive cannot manage technical debt or maintain AI precision, false positive rates could increase and competitive differentiation could erode.

Intense Competition and New Product Execution Risk

Motive competes against well-capitalized players like Samsara across fleet safety, management, equipment monitoring, and spend management. The company's growth depends on customers adopting multiple products over time. If cross-sell rates disappoint or products fail to deliver measurable ROI, returns on R&D investment will be diluted and Physical Operations Graph network effects will weaken.

Market Sensitivity to Physical Economy Cyclicality

Motive's customer base spans construction, trucking, logistics, oil and gas, and manufacturing—industries exposed to fuel price volatility, interest rate swings, and recession risk. Economic downturns reduce capital expenditures on fleet technology, compressing software subscription budgets despite demonstrated ROI from collision reduction and fuel savings.

Market Opportunity

The physical operations landscape is experiencing a structural inflection point. Motive addresses a $187 billion global revenue opportunity by delivering AI-powered safety, fleet management, equipment monitoring, spend control, workforce automation, and computer vision through a vertically integrated platform spanning workers, vehicles, equipment, and spend.

Displacing Legacy Fleet and Safety Infrastructure

Motive's primary opportunity lies in replacing fragmented point solutions across Driver Safety and Fleet Management—a $60 billion market including $25 billion controlled by legacy telematics providers. Traditional systems burden fleet operators with siloed GPS tracking, standalone dashcams generating false positives, manual incident reviews, and disconnected compliance workflows.

Motive collapses these silos into a unified platform delivering 80% collision reduction and industry-leading AI precision. Despite serving nearly 100,000 customers and $501 million ARR as of September 2025, Motive penetrates less than 1% of the addressable market—leaving substantial expansion room as customers adopt AI Dashcams, migrate from legacy telematics, and consolidate multiple vendors into the Physical Operations Graph.

Structural tailwinds persist: organizations in the physical economy face growing safety risks (43% surge in fatal truck crashes from 2014-2023), declining labor force participation (51% annual turnover in transportation and warehousing), and continuously rising insurance premiums (40% increase over the past decade). These dynamics reward platforms delivering measurable ROI through accident prevention, insurance savings, and workforce productivity.

Expanding Across Equipment, Spend, and Workforce

Motive's second opportunity is cross-sell expansion into Equipment Monitoring ($28 billion), Spend Management ($30 billion including $4 billion from legacy providers), and Workforce Management ($23 billion). Customers adopt for collision prevention, then systematically expand across trailers, fuel cards, and payroll as the Physical Operations Graph demonstrates value.

Equipment Monitoring addresses underutilized assets and reactive maintenance. Spend Management eliminates fuel fraud (contributing to $175 million in customer savings during 2024). Workforce Management automates scheduling, timekeeping, and compliance across field workers. AI Vision ($46 billion opportunity) extends computer vision beyond dashcams into warehouses, construction sites, and industrial facilities.

Building the Infrastructure Layer

Motive's long-term vision: becoming the central data layer for the $50 trillion physical economy as recursive AI improvement and unified operations reach critical mass. Every connected vehicle, labeled safety event, and cross-domain workflow strengthens Motive's moat and expands addressable markets into industries beyond trucking—construction, oil and gas, manufacturing, agriculture, public sector—spanning organizations requiring integrated management of workers, vehicles, equipment, and spend.

Product

Motive's Integrated Operations Platform delivers six products unified by the Physical Operations Graph—a foundational data layer connecting workers, vehicles, equipment, and spend. This architecture eliminates the fragmented point solutions that burden fleet operators with siloed systems, manual workflows, and limited automation.

Driver Safety: AI-Powered Collision Prevention

Launched in 2018, Driver Safety deploys proprietary AI Dashcams engineered for mission-critical accuracy with minimal false positives. The system monitors driver behavior in real-time, detects safety events with industry-leading precision, and enables proactive coaching before incidents occur. Customers using AI Dashcams reduced collisions by 80% on average, with top quartile customers reporting 63% reductions in accident-related costs and 25% insurance premium savings. Multi-layer validation—model benchmarking, human review by 400 full-time annotators, and quality assurance sampling—ensures erroneous detections are corrected before reaching customers.

Fleet Management: Operational Visibility and Automation

Launched in 2013 as Motive's founding product, Fleet Management provides location tracking, asset utilization, maintenance automation, and dispatch workflows. Top quartile customers reported saving 25 hours per week on vehicle tracking and 20% annual costs through efficient maintenance management—transforming reactive repairs into predictive scheduling powered by telematics data flowing through the Physical Operations Graph.

Equipment Monitoring, Spend Management, and Workforce Management

Equipment Monitoring (launched 2019) extends visibility beyond vehicles to trailers, heavy machinery, and field assets. Spend Management (launched 2022) integrates the Motive Card with vehicle telematics, enabling fraud detection, spend policy enforcement, and partner network discounts—delivering over $175 million in fuel and fraud savings during 2024. Workforce Management automates scheduling, timekeeping, and compliance for field operations.

AI Vision: Computer Vision Beyond Dashcams

AI Vision extends Motive's recursive improvement architecture into warehouses, construction sites, and industrial facilities—enabling safety monitoring, workflow automation, and operational analytics across the $46 billion computer vision opportunity.

Recursive Improvement Flywheel

More than one million connected vehicles generate continuous training data. Four hundred full-time annotators process tens of millions of events annually, feeding purpose-built AI models that improve with every deployment cycle. This compounding advantage—proprietary hardware, high-quality labeled data, domain-expert engineers, and low-latency validation—creates barriers competitors cannot replicate through software alone. The Physical Operations Graph becomes more valuable with each connected asset, each labeled event, and each cross-product workflow, driving 110-126% net dollar retention as customers expand from single products to integrated platform adoption.

Business Model

Motive's model is data-native, AI-powered, and expansion-compounding—built as recurring subscription infrastructure that delivers measurable safety and productivity outcomes while reinforcing customer lock-in through multi-product adoption and the Physical Operations Graph flywheel.

Subscription-Dominant, High-Retention Architecture

1) Platform Subscriptions

Economics: 95-97% of revenue from per-asset, per-product pricing with typical three-year contracts. Customers pay monthly, quarterly, or annually with net 30-day terms. Subscription bundles include platform access plus integrated hardware (AI Dashcams, GPS trackers, fuel cards).

Mix: Driver Safety, Fleet Management, Equipment Monitoring, Workforce Management, and AI Vision across nearly 100,000 customers and over one million connected assets.

Why it matters: Recurring revenue engine funding recursive AI improvement through 400 full-time data annotators processing tens of millions of events annually. Multi-product adoption is the core value creation mechanism—89% of Core Customers adopted two or more products as of September 2025, with 40% adopting three or more products. Net dollar retention of 110% for Core Customers and 126% for Large Customers demonstrates steadily accelerating expansion.

2) Spend Management

Economics: 2-4% of revenue from interchange fees and Motive partner network rebates tied to fuel card transaction volume. Usage-based model scales with customer activity rather than fixed subscriptions.

Why it matters: Strategic land-and-expand mechanism providing transaction-level visibility into fleet spend patterns. Delivered over $175 million in fuel and fraud savings during 2024, creating measurable ROI that drives platform stickiness while generating incremental revenue as customers consolidate spend onto Motive Card.

Recursive AI and Data Flywheel

Connected assets replace fragmentation: Over one million vehicles and equipment generating continuous training data across dashcam footage, GPS telemetry, fuel transactions, and maintenance records unified in the Physical Operations Graph. More connected assets per customer improves cross-domain insights—collision patterns correlated with fuel efficiency, maintenance scheduling optimized by utilization data.

Proprietary AI eliminates false positives: Full-stack architecture combining custom dashcam hardware, purpose-built computer vision models, multi-layer validation (benchmarking, human review, quality assurance), and low-latency corrections. Result: 80% average collision reduction and industry-leading precision enabling automated workflows while competitors struggle with unusable false positive rates.

Multi-Product Adoption Flywheel Compounds Customer Value

Land with collision prevention (demonstrate 80% reduction) → expand into fleet visibility and equipment monitoring → cross-sell Spend Management (fraud detection creates immediate ROI) → capture expansion revenue while delivering insurance savings and productivity gains → reinvest in AI model improvements and new product development → deepen lock-in through Physical Operations Graph dependencies and measurable outcomes.

Management Team: 

Shoaib Makani – Chief Executive Officer and Co-Founder

Shoaib Makani has served as CEO and board member since co-founding Motive in 2013. He previously led investments in consumer and enterprise technology at Khosla Ventures (2011–2013) and drove international growth at AdMob, a mobile advertising platform acquired by Google in 2009, from 2008 to 2011. His vision to apply AI and connected hardware to the physical economy established Motive's foundational strategy: building proprietary dashcam technology and the Physical Operations Graph as infrastructure for fleet safety and automation. Makani's technical background and venture capital experience position him to execute recursive AI improvement and multi-product expansion. Shoaib holds a B.Sc. in Government and Economics from The London School of Economics.

Amish Babu – Chief Technology Officer

Amish Babu has served as CTO since May 2025, previously leading Connected Devices (2022–2025) and Hardware (2020–2022). Before joining Motive, Babu served as Head of Electrical Engineering at Oculus VR, Meta's virtual reality subsidiary (2017–2020), and Director of Hardware Engineering at Logitech (2015–2017). His consumer electronics expertise underpins Motive's full-stack AI architecture combining proprietary dashcams, purpose-built computer vision models, and low-latency validation systems. Amish holds a B.S. in Computer Systems Engineering and M.S. in Materials Science and Engineering from Stanford University.

Chirag Shah – Chief Financial Officer

Chirag Shah has served as CFO since October 2024. He previously held CFO roles at Kong Inc., an API management software company (2022–2024), and Cornerstone OnDemand, a cloud-based talent management platform (2021–2022). Earlier, Shah served in positions of increasing responsibility at Cornerstone, including General Manager of Growth Markets (2017–2020) and VP of Finance and Strategy (2009–2016). His SaaS finance leadership and public company experience support Motive's path to profitability following rapid ARR growth from $338 million (2023) to $501 million (September 2025). Chirag holds a B.S. in Finance from Georgetown University and an M.B.A. from Northwestern University's Kellogg School of Management.

Investment

Motive's financing trajectory signaled methodical validation—from fleet management thesis to AI-powered physical operations platform. Founded in 2013 as KeepTruckin, the company raised early-stage capital to build electronic logging devices for Hours of Service compliance, establishing product-market fit in the fragmented trucking software market.

Momentum accelerated through product expansion. Series funding rounds financed AI Dashcam development (launched 2018), proprietary hardware manufacturing, and the Physical Operations Graph infrastructure connecting workers, vehicles, equipment, and spend. As ARR scaled from zero to $338 million by December 2023, investor confidence grew around recursive AI improvement and multi-product adoption economics.

The inflection arrived as Motive demonstrated enterprise traction with Large Customers growing from 234 (December 2023) to 494 (September 2025)—a 58% increase in 21 months. Net dollar retention rates of 110% for Core Customers and 126% for Large Customers validated land-and-expand unit economics, while 89% multi-product adoption among Core Customers proved platform stickiness. This capital fueled expansion beyond trucking into construction, oil and gas, manufacturing, agriculture, and public sector verticals, plus international operations in Mexico (2024) and United Kingdom (2025).

With institutional backing spanning growth equity and strategic investors, Motive financed a vertically integrated, AI-first stack powering safety, fleet management, equipment monitoring, spend control, workforce automation, and computer vision. The result is a capital-intensive but scalable operating model aligned to network effects, reaching $501 million ARR as of September 2025 while investing toward long-term infrastructure dominance across the $187 billion addressable market.

Competition

The physical operations software landscape is dominated by point solution providers, legacy telematics vendors, and fuel card issuers—organizations built on single-product offerings, siloed data systems, and fragmented workflows. Motive takes a different approach: an AI-powered integrated platform unifying Driver Safety, Fleet Management, Equipment Monitoring, Spend Management, Workforce Management, and AI Vision under the Physical Operations Graph.

The Obvious Competition:

Fleet Management Vendors — Geotab, Verizon Connect, Trimble, and ORBCOMM provide GPS tracking and compliance tools with established customer bases, but lack AI dashcams, spend management, or workforce automation versus Motive's six-product stack.

Dashcam-Only Providers — Lytx, Netradyne, SmartDrive offer video safety systems, but single-product economics, higher false positive rates (2-4x fewer accurate alerts than Motive per Virginia Tech study), and no unified data layer versus Motive's recursive AI improvement across one million connected assets.

Integrated Platforms — Samsara emerged as the primary competitor with fleet management, video telematics, and equipment monitoring backed by $800+ million pre-IPO capital. Broad product suite and enterprise sales motion, but Motive maintains AI accuracy advantages (15 unsafe behaviors monitored including fatigue detection unavailable from competitors) and 20-30% faster enterprise implementation.

Fuel Card Issuers — WEX, Corpay, Comdata provide standalone spend management with interchange economics, but no telematics integration or cross-domain insights versus Motive's unified platform.

How Motive Competes

Motive's moat is built around recursive AI and multi-product adoption:

• Full-stack AI architecture: Proprietary dashcam hardware → 400 annotators processing tens of millions of events → purpose-built models → low-latency validation

• Physical Operations Graph: Connects workers, vehicles, equipment, spend—enabling cross-domain automation impossible with point solutions

• Expansion economics: 110-126% net dollar retention; 89% multi-product adoption among Core Customers; 20-30% faster implementation delivering six-month ROI

Competition remains intense from established vendors and well-capitalized platforms like Samsara, but Motive's AI-native, recursively improving, multi-product platform converts operational fragmentation into sustainable competitive advantage.

Financials

Motive's financial profile reflects AI-powered platform scaling toward profitability: accelerating ARR growth, expanding Large Customer penetration, and improving operating leverage powered by multi-product adoption. Ongoing investments in recursive AI infrastructure influenced recent loss levels, but the business added enterprise accounts, deepened relationships, and demonstrated path to sustainable unit economics.

Growth at Scale

• ARR: $501M (September 2025), +28% YoY from $393M; +23% to $417M (December 2024) from $338M (December 2023).

• Revenue: $370M in 2024 (+19% YoY); $327M in 9M 2025 (+22% YoY from $269M).

• Mix: Subscription revenue 95-97% of total; Spend Management 2-4% (growing from interchange fees and partner network rebates).

• Profitability: Net loss $153M in 2024 versus $109M (2023); $139M in 9M 2025. Non-GAAP operating loss improved to $55M (9M 2025) from $65M (9M 2024), demonstrating leverage as revenue scales faster than adjusted expenses.

Ecosystem Momentum

• Customer Expansion: Large Customers (>$100K ARR) grew 58% to 494 (September 2025) from 312, representing 37% of total ARR versus 28%—indicating upmarket penetration.

• Multi-Product Adoption: 89% of Core Customers adopted two or more products (September 2025) versus 87%; 40% adopted three or more versus 34%—driving land-and-expand flywheel.

• Net Dollar Retention: Core Customers 110% (September 2025); Large Customers 126%—demonstrating expansion economics and platform stickiness.

Conversion Economics

Subscription revenue grew $57M in 9M 2025, driven by: $19M from new customers acquired during period; $38M from existing customer expansion (multi-product cross-sell, fleet size growth); +$3.5M Spend Management from higher adoption and transaction volume.

Operating Discipline

• Gross Margin: 70% (2024, 9M 2025); hardware amortization scales with subscription growth.

• Sales & Marketing: $155M in 9M 2025 (+16% YoY); expanding sales teams while improving efficiency (47% of revenue versus 50% prior year).

• R&D: $81M in 9M 2025 (+11% YoY); investments in AI models and recursive improvement (25% of revenue versus 27% prior year).

Closing thoughts

Motive's financial performance and strategic positioning underscore its potential to redefine how the physical economy operates in an era of rising safety risks, labor shortages, and input cost pressures. With an AI-powered, recursively improving platform, Motive has differentiated from point solution providers and legacy telematics vendors while building infrastructure spanning proprietary dashcam hardware, purpose-built computer vision models, and cross-domain workflow automation. Its end-to-end offering—over one million connected assets, 400 data annotators, Physical Operations Graph, six-product suite, and systematic multi-product adoption—creates a flywheel that strengthens as customers consolidate fragmented systems, AI models improve through continuous training, and platform economics reach critical mass.

Bull Case: Motive's AI-native model provides foundation for sustained growth. The company serves nearly 100,000 customers generating $501M ARR (September 2025), prevents over 170,000 accidents since 2023, and demonstrates improving unit economics with non-GAAP operating loss declining to $55M (9M 2025) from $65M prior year. Large Customer expansion—growing 58% to 494 with 126% net dollar retention—demonstrates embedded growth. Multi-product adoption reaching 89% (two or more products) among Core Customers validates land-and-expand momentum. Addressable market spans $187B globally with less than 1% penetration.

Bear Case: Intense competition from established vendors (Geotab, Verizon Connect) and well-capitalized platforms (Samsara with $800M+ pre-IPO funding). History of losses—$153M (2024), $978M accumulated deficit—creates uncertainty around profitability. Large Customer concentration (37% of ARR) amplifies revenue risk. AI reliability risks—annotation errors, model drift, regulatory compliance—threaten differentiation if false positive rates increase.

Success hinges on maintaining net dollar retention as competition intensifies, executing systematic product expansion (two to six products over customer lifecycles), scaling internationally (1% of revenue versus global opportunity), and achieving profitability while sustaining AI model quality. If executed, Motive is positioned to capture infrastructure economics as physical economy organizations consolidate operations and AI-powered unified platforms become essential across workers, vehicles, equipment, and spend.

Ankur Patel is the founder and CEO of Multimodal, where he’s automating the most complex workflows in finance and insurance. He has 15+ years of work experience across companies like J.P. Morgan and Bridgewater.

In this conversation, Ankur and I discuss:

• What’s the biggest objection from compliance teams in finance, and how do you overcome it?

• How do you price agentic AI—seats, tasks automated, outcomes. Which model truly aligns incentives?

• Usage-based pricing creates cost uncertainty. How do you balance consumption economics with the enterprise need for budget predictability?

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