Bot Services Market by Bot Type (Conversational Chatbots, Voice Bots, Transactional Bots), Channel Type (Text Based, Voice Based), Organization Size, Deployment Model, Application, End User - Global Forecast 2025-2032
Description
The Bot Services Market was valued at USD 1.46 billion in 2024 and is projected to grow to USD 1.90 billion in 2025, with a CAGR of 30.79%, reaching USD 12.58 billion by 2032.
A strategic primer on how modern conversational agents and automation technologies are redefining customer engagement and operational transformation across enterprises
The bot services landscape has evolved from nascent rule-driven scripts to sophisticated conversational platforms that integrate across enterprise systems. This introduction outlines the strategic context for leaders assessing how bot-enabled automation reshapes customer engagement, service delivery, and operational efficiency across industries. As organizations prioritize digital transformation, bots have become pivotal for bridging human and machine interactions, reducing friction, and enabling 24/7 responsiveness.
This summary frames the core drivers motivating adoption, including the push for seamless customer experiences, cost optimization pressures, and the need to scale support functions without proportional headcount increases. It also highlights the maturation of underlying technologies such as cloud-native deployment paradigms, advanced natural language processing, and increasingly capable machine learning models. Together, these trends are establishing new norms for how enterprises design conversational journeys, delegate routine tasks to automated agents, and measure success through experience metrics and operational KPIs.
How converging technology advances, governance expectations, and evolving customer demands are reshaping the architecture and adoption of conversational bot services
The current landscape is undergoing transformative shifts as underlying technologies, regulatory pressures, and customer expectations converge to redefine the role of bot services. On the technology front, the move from isolated, on-premise solutions to cloud-first architectures is enabling rapid iteration, seamless integration with enterprise systems, and continuous model improvements. Simultaneously, advances in natural language understanding and contextual dialogue management are elevating the capability of bots to handle complex, multi-turn interactions that previously required human intervention.
Regulatory and ethical considerations are also influencing design choices, encouraging transparency, data minimization, and robust governance frameworks. Customer expectations have shifted toward instant, personalized, and omnichannel experiences, prompting organizations to integrate conversational agents into broader experience ecosystems. As a result, vendors and buyers are recalibrating roadmaps to emphasize interoperability, explainability, and measurable business outcomes, thereby accelerating enterprise adoption and raising the bar for solution differentiation.
Assessing the cascading effects of updated United States tariff policies on procurement, deployment choices, and resilience strategies for bot service implementations
The policy environment in 2025 introduced new tariff measures in the United States that ripple across global supply chains and procurement strategies, affecting software-enabled services and hardware provisioning essential for bot deployments. Organizations that rely on imported hardware for on-premise deployments, or on third-party hosting services provisioned through international data centers, face higher total cost of ownership and altered procurement timelines. In response, many firms are revisiting deployment strategies and contractual terms to mitigate exposure to tariff-induced cost volatility.
Consequently, there is an observable recalibration toward cloud-hosted and hybrid models that reduce dependency on cross-border hardware movement while enabling service providers to abstract tariff impacts. Procurement teams are negotiating more flexible commercial terms and longer-term service agreements to stabilize budget forecasts. At the same time, regionalization of vendor partnerships and supply chains is gaining traction as firms seek resilience by diversifying sourcing and hosting options. This policy-driven environment compels organizations to balance cost considerations with performance, data residency, and regulatory compliance needs when planning bot service rollouts.
Deep segmentation-driven insights revealing how deployment choices, channel modalities, bot intelligence levels, end-use cases, organization scale, and industry verticals determine adoption and value capture
Segment-level insights reveal divergent adoption pathways based on deployment, channel, bot intelligence, end-use, organization size, and industry vertical. Deployment choices are pivotal: Cloud and On Premise remain the primary models, with Cloud gaining preference due to elasticity and continuous update capabilities; within Cloud, Hybrid Cloud, Private Cloud, and Public Cloud present trade-offs between control, scalability, and compliance obligations. Channel selection influences user experience and technical integration priorities; Text Based implementations emphasize asynchronous, scalable interactions, whereas Voice Based solutions, including Interactive Voice Response and Voice Assistant, demand tighter latency control and advanced speech interfaces.
Bot Type delineates capability tiers where AI Based solutions, driven by Machine Learning Driven approaches and Natural Language Processing, offer nuanced understanding and adaptive responses, in contrast to Rule Based bots that excel in deterministic, low-complexity workflows. End Use patterns show customer-facing deployments concentrated in Customer Support, which spans Post Sales Support and Pre Sales Support, while IT Helpdesk and Virtual Assistant implementations address internal workflows; Virtual Assistants further bifurcate into Personal Assistant and Scheduling Assistant roles that streamline day-to-day productivity tasks. Organization Size influences adoption velocity and customization needs: Large Enterprise environments prioritize integration with legacy systems and governance, whereas Small And Medium Enterprise segments, including Medium Enterprise and Small Enterprise, seek cost-effective, off-the-shelf solutions. Industry Vertical dynamics vary markedly across Banking Financial Services Insurance, Government, Healthcare, Retail, and Telecom; within BFSI, Banking, Insurance, and Investment Services each demand specialized compliance and domain models, while Retail differentiates between Brick And Mortar and Ecommerce experiences, shaping conversational design and channel mix.
Comprehensive regional analysis that highlights how the Americas, Europe Middle East & Africa, and Asia-Pacific each require distinct deployment strategies, compliance approaches, and localization priorities
Regional dynamics shape strategic priorities and vendor selection as enterprises navigate regulatory requirements, talent availability, and customer behavior variations across geographies. In the Americas, market actors emphasize rapid digital channels, strong cloud adoption, and an appetite for integrating generative and conversational AI into customer-facing workflows; commercial models there tend to favor outcome-based contracts and robust analytics. Europe, Middle East & Africa exhibits a heterogeneous landscape where stringent data protection regimes, localization requirements, and a mix of mature and emerging markets drive tailored deployment strategies and a cautious approach to cross-border data flows.
Asia-Pacific demonstrates accelerated uptake driven by high mobile penetration, broad consumer familiarity with conversational interfaces, and significant investment in localized language models and voice technologies. Regional vendors and system integrators in Asia-Pacific often deliver solutions optimized for multilingual, high-concurrency environments. Across regions, enterprises are balancing global standardization with local customization to ensure regulatory compliance, cultural resonance, and operational efficiency. These geographic patterns inform vendor go-to-market approaches, partnership formations, and prioritization of language and channel support in product roadmaps.
Competitive landscape insights showing how platform innovation, vertical specialization, and ecosystem partnerships determine vendor differentiation and enterprise adoption success
Competitive dynamics among companies offering bot services are characterized by a blend of platform innovation, solution depth, and partnership ecosystems. Leading providers are investing in modular architectures, low-code orchestration layers, and pre-trained domain models to accelerate time to value for enterprise clients. Strategic differentiation increasingly hinges on the ability to demonstrate integration capabilities with CRM, contact center platforms, and core back-office systems while delivering measurable improvements in customer satisfaction and operational efficiency.
Smaller and niche vendors focus on vertical specialization, building rich industry ontologies and compliance-ready templates that reduce deployment friction for regulated sectors. Partnerships with telecom carriers, cloud hyperscalers, and systems integrators expand reach and enable bundled offerings that address complex enterprise requirements. Across the competitive set, there is a clear movement toward transparent performance metrics, explainability for AI-driven decisions, and ecosystem playbooks that combine professional services with managed operations to support clients throughout the adoption lifecycle.
Actionable recommendations for enterprise leaders to align bot deployments with measurable outcomes, governance frameworks, and resilient vendor partnership strategies
Industry leaders should adopt a pragmatic roadmap that aligns technology selection with measurable business outcomes and governance guardrails. Begin by articulating outcome-focused use cases that map directly to customer experience improvements or cost-to-serve reductions, and prioritize those with clear integration touchpoints to CRM and enterprise service platforms. Concurrently, establish robust governance practices covering data privacy, model monitoring, and change control so that innovation does not outpace operational risk management.
Adopt a hybrid deployment posture that leverages Public Cloud for scalability, Private Cloud where data residency or control is paramount, and On Premise for latency-sensitive or highly regulated workloads. Invest in reusable conversational components and a centralized intent taxonomy to accelerate rollout across channels, including both Text Based and Voice Based interactions. Form strategic partnerships with specialized vendors and systems integrators to complement internal capabilities, and design procurement vehicles that permit pilot-to-production scaling while insulating budgets from geopolitical or tariff-induced volatility. Finally, cultivate internal upskilling and cross-functional governance teams to sustain continuous improvement and to measure impact against agreed KPIs.
Transparent research methodology detailing primary interviews, secondary synthesis, and analytical frameworks used to derive robust and actionable insights on bot service adoption
The research approach combined qualitative and quantitative methods to generate balanced insights on adoption patterns, technology capabilities, and operational implications. Primary interviews with enterprise practitioners, technology leaders, and solution providers surfaced firsthand perspectives on implementation challenges, governance needs, and integration priorities. Secondary research synthesized vendor documentation, regulatory guidance, and technical literature to corroborate trends and to map capabilities across deployment models and vertical contexts.
Analytical frameworks included capability mapping, use-case prioritization, and comparative evaluation of deployment trade-offs between Cloud, On Premise, and hybrid modalities. Emphasis was placed on triangulating findings to ensure consistency and to highlight areas of divergence where organizational context materially affects strategic choices. Throughout the methodology, care was taken to anonymize sensitive interview data and to validate conclusions through cross-sector corroboration, thereby providing decision-makers with reliable, actionable intelligence grounded in both practitioner experience and technical assessment.
A strategic conclusion emphasizing how integration of conversational intelligence, governance practices, and modular deployment models will define long-term success for enterprises
In conclusion, bot services are transitioning from tactical automation tools to strategic components of enterprise digital ecosystems, enabling both external customer engagement and internal workforce productivity. The convergence of improved natural language capabilities, flexible deployment architectures, and heightened governance expectations is shaping a landscape where interoperability, explainability, and outcome measurability determine long-term success. Organizations that explicitly link conversational initiatives to business objectives, while embedding risk controls and cross-functional governance, will capture disproportionate value.
Looking ahead, the interplay between regulatory shifts, supply chain considerations, and regional market dynamics will continue to influence procurement and deployment strategies. Firms that adopt a deliberate, phased approach-prioritizing modularity, cross-channel consistency, and partnerships-will be best positioned to scale conversational capabilities while maintaining compliance and cost discipline. This conclusion underscores the imperative for leaders to act decisively, balancing innovation with prudent risk management to realize the full potential of bot-enabled transformation.
Note: PDF & Excel + Online Access - 1 Year
A strategic primer on how modern conversational agents and automation technologies are redefining customer engagement and operational transformation across enterprises
The bot services landscape has evolved from nascent rule-driven scripts to sophisticated conversational platforms that integrate across enterprise systems. This introduction outlines the strategic context for leaders assessing how bot-enabled automation reshapes customer engagement, service delivery, and operational efficiency across industries. As organizations prioritize digital transformation, bots have become pivotal for bridging human and machine interactions, reducing friction, and enabling 24/7 responsiveness.
This summary frames the core drivers motivating adoption, including the push for seamless customer experiences, cost optimization pressures, and the need to scale support functions without proportional headcount increases. It also highlights the maturation of underlying technologies such as cloud-native deployment paradigms, advanced natural language processing, and increasingly capable machine learning models. Together, these trends are establishing new norms for how enterprises design conversational journeys, delegate routine tasks to automated agents, and measure success through experience metrics and operational KPIs.
How converging technology advances, governance expectations, and evolving customer demands are reshaping the architecture and adoption of conversational bot services
The current landscape is undergoing transformative shifts as underlying technologies, regulatory pressures, and customer expectations converge to redefine the role of bot services. On the technology front, the move from isolated, on-premise solutions to cloud-first architectures is enabling rapid iteration, seamless integration with enterprise systems, and continuous model improvements. Simultaneously, advances in natural language understanding and contextual dialogue management are elevating the capability of bots to handle complex, multi-turn interactions that previously required human intervention.
Regulatory and ethical considerations are also influencing design choices, encouraging transparency, data minimization, and robust governance frameworks. Customer expectations have shifted toward instant, personalized, and omnichannel experiences, prompting organizations to integrate conversational agents into broader experience ecosystems. As a result, vendors and buyers are recalibrating roadmaps to emphasize interoperability, explainability, and measurable business outcomes, thereby accelerating enterprise adoption and raising the bar for solution differentiation.
Assessing the cascading effects of updated United States tariff policies on procurement, deployment choices, and resilience strategies for bot service implementations
The policy environment in 2025 introduced new tariff measures in the United States that ripple across global supply chains and procurement strategies, affecting software-enabled services and hardware provisioning essential for bot deployments. Organizations that rely on imported hardware for on-premise deployments, or on third-party hosting services provisioned through international data centers, face higher total cost of ownership and altered procurement timelines. In response, many firms are revisiting deployment strategies and contractual terms to mitigate exposure to tariff-induced cost volatility.
Consequently, there is an observable recalibration toward cloud-hosted and hybrid models that reduce dependency on cross-border hardware movement while enabling service providers to abstract tariff impacts. Procurement teams are negotiating more flexible commercial terms and longer-term service agreements to stabilize budget forecasts. At the same time, regionalization of vendor partnerships and supply chains is gaining traction as firms seek resilience by diversifying sourcing and hosting options. This policy-driven environment compels organizations to balance cost considerations with performance, data residency, and regulatory compliance needs when planning bot service rollouts.
Deep segmentation-driven insights revealing how deployment choices, channel modalities, bot intelligence levels, end-use cases, organization scale, and industry verticals determine adoption and value capture
Segment-level insights reveal divergent adoption pathways based on deployment, channel, bot intelligence, end-use, organization size, and industry vertical. Deployment choices are pivotal: Cloud and On Premise remain the primary models, with Cloud gaining preference due to elasticity and continuous update capabilities; within Cloud, Hybrid Cloud, Private Cloud, and Public Cloud present trade-offs between control, scalability, and compliance obligations. Channel selection influences user experience and technical integration priorities; Text Based implementations emphasize asynchronous, scalable interactions, whereas Voice Based solutions, including Interactive Voice Response and Voice Assistant, demand tighter latency control and advanced speech interfaces.
Bot Type delineates capability tiers where AI Based solutions, driven by Machine Learning Driven approaches and Natural Language Processing, offer nuanced understanding and adaptive responses, in contrast to Rule Based bots that excel in deterministic, low-complexity workflows. End Use patterns show customer-facing deployments concentrated in Customer Support, which spans Post Sales Support and Pre Sales Support, while IT Helpdesk and Virtual Assistant implementations address internal workflows; Virtual Assistants further bifurcate into Personal Assistant and Scheduling Assistant roles that streamline day-to-day productivity tasks. Organization Size influences adoption velocity and customization needs: Large Enterprise environments prioritize integration with legacy systems and governance, whereas Small And Medium Enterprise segments, including Medium Enterprise and Small Enterprise, seek cost-effective, off-the-shelf solutions. Industry Vertical dynamics vary markedly across Banking Financial Services Insurance, Government, Healthcare, Retail, and Telecom; within BFSI, Banking, Insurance, and Investment Services each demand specialized compliance and domain models, while Retail differentiates between Brick And Mortar and Ecommerce experiences, shaping conversational design and channel mix.
Comprehensive regional analysis that highlights how the Americas, Europe Middle East & Africa, and Asia-Pacific each require distinct deployment strategies, compliance approaches, and localization priorities
Regional dynamics shape strategic priorities and vendor selection as enterprises navigate regulatory requirements, talent availability, and customer behavior variations across geographies. In the Americas, market actors emphasize rapid digital channels, strong cloud adoption, and an appetite for integrating generative and conversational AI into customer-facing workflows; commercial models there tend to favor outcome-based contracts and robust analytics. Europe, Middle East & Africa exhibits a heterogeneous landscape where stringent data protection regimes, localization requirements, and a mix of mature and emerging markets drive tailored deployment strategies and a cautious approach to cross-border data flows.
Asia-Pacific demonstrates accelerated uptake driven by high mobile penetration, broad consumer familiarity with conversational interfaces, and significant investment in localized language models and voice technologies. Regional vendors and system integrators in Asia-Pacific often deliver solutions optimized for multilingual, high-concurrency environments. Across regions, enterprises are balancing global standardization with local customization to ensure regulatory compliance, cultural resonance, and operational efficiency. These geographic patterns inform vendor go-to-market approaches, partnership formations, and prioritization of language and channel support in product roadmaps.
Competitive landscape insights showing how platform innovation, vertical specialization, and ecosystem partnerships determine vendor differentiation and enterprise adoption success
Competitive dynamics among companies offering bot services are characterized by a blend of platform innovation, solution depth, and partnership ecosystems. Leading providers are investing in modular architectures, low-code orchestration layers, and pre-trained domain models to accelerate time to value for enterprise clients. Strategic differentiation increasingly hinges on the ability to demonstrate integration capabilities with CRM, contact center platforms, and core back-office systems while delivering measurable improvements in customer satisfaction and operational efficiency.
Smaller and niche vendors focus on vertical specialization, building rich industry ontologies and compliance-ready templates that reduce deployment friction for regulated sectors. Partnerships with telecom carriers, cloud hyperscalers, and systems integrators expand reach and enable bundled offerings that address complex enterprise requirements. Across the competitive set, there is a clear movement toward transparent performance metrics, explainability for AI-driven decisions, and ecosystem playbooks that combine professional services with managed operations to support clients throughout the adoption lifecycle.
Actionable recommendations for enterprise leaders to align bot deployments with measurable outcomes, governance frameworks, and resilient vendor partnership strategies
Industry leaders should adopt a pragmatic roadmap that aligns technology selection with measurable business outcomes and governance guardrails. Begin by articulating outcome-focused use cases that map directly to customer experience improvements or cost-to-serve reductions, and prioritize those with clear integration touchpoints to CRM and enterprise service platforms. Concurrently, establish robust governance practices covering data privacy, model monitoring, and change control so that innovation does not outpace operational risk management.
Adopt a hybrid deployment posture that leverages Public Cloud for scalability, Private Cloud where data residency or control is paramount, and On Premise for latency-sensitive or highly regulated workloads. Invest in reusable conversational components and a centralized intent taxonomy to accelerate rollout across channels, including both Text Based and Voice Based interactions. Form strategic partnerships with specialized vendors and systems integrators to complement internal capabilities, and design procurement vehicles that permit pilot-to-production scaling while insulating budgets from geopolitical or tariff-induced volatility. Finally, cultivate internal upskilling and cross-functional governance teams to sustain continuous improvement and to measure impact against agreed KPIs.
Transparent research methodology detailing primary interviews, secondary synthesis, and analytical frameworks used to derive robust and actionable insights on bot service adoption
The research approach combined qualitative and quantitative methods to generate balanced insights on adoption patterns, technology capabilities, and operational implications. Primary interviews with enterprise practitioners, technology leaders, and solution providers surfaced firsthand perspectives on implementation challenges, governance needs, and integration priorities. Secondary research synthesized vendor documentation, regulatory guidance, and technical literature to corroborate trends and to map capabilities across deployment models and vertical contexts.
Analytical frameworks included capability mapping, use-case prioritization, and comparative evaluation of deployment trade-offs between Cloud, On Premise, and hybrid modalities. Emphasis was placed on triangulating findings to ensure consistency and to highlight areas of divergence where organizational context materially affects strategic choices. Throughout the methodology, care was taken to anonymize sensitive interview data and to validate conclusions through cross-sector corroboration, thereby providing decision-makers with reliable, actionable intelligence grounded in both practitioner experience and technical assessment.
A strategic conclusion emphasizing how integration of conversational intelligence, governance practices, and modular deployment models will define long-term success for enterprises
In conclusion, bot services are transitioning from tactical automation tools to strategic components of enterprise digital ecosystems, enabling both external customer engagement and internal workforce productivity. The convergence of improved natural language capabilities, flexible deployment architectures, and heightened governance expectations is shaping a landscape where interoperability, explainability, and outcome measurability determine long-term success. Organizations that explicitly link conversational initiatives to business objectives, while embedding risk controls and cross-functional governance, will capture disproportionate value.
Looking ahead, the interplay between regulatory shifts, supply chain considerations, and regional market dynamics will continue to influence procurement and deployment strategies. Firms that adopt a deliberate, phased approach-prioritizing modularity, cross-channel consistency, and partnerships-will be best positioned to scale conversational capabilities while maintaining compliance and cost discipline. This conclusion underscores the imperative for leaders to act decisively, balancing innovation with prudent risk management to realize the full potential of bot-enabled transformation.
Note: PDF & Excel + Online Access - 1 Year
Table of Contents
192 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Growing adoption of multilingual conversational AI bots for global customer engagement
- 5.2. Integration of AI-driven sentiment analysis in chatbots to personalize user experiences
- 5.3. Deployment of voice-enabled virtual assistants with natural language understanding for seamless support
- 5.4. Emergence of low-code bot development platforms accelerating enterprise automation initiatives
- 5.5. Use of proactive customer outreach bots leveraging predictive analytics to improve retention rates
- 5.6. Rising investment in security protocols for conversational AI to safeguard sensitive user data from breaches
- 5.7. Adoption of hybrid bots combining rule-based and AI capabilities to handle complex customer queries
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Bot Services Market, by Bot Type
- 8.1. Conversational Chatbots
- 8.1.1. Rule Driven Chatbots
- 8.1.2. AI Driven Chatbots
- 8.1.3. Hybrid Chatbots
- 8.2. Voice Bots
- 8.2.1. Call Center Voice Bots
- 8.2.2. Smart Device Voice Bots
- 8.3. Transactional Bots
- 8.4. Process Automation Bots
- 8.5. Informational Bots
- 9. Bot Services Market, by Channel Type
- 9.1. Text Based
- 9.2. Voice Based
- 9.2.1. Interactive Voice Response
- 9.2.2. Voice Assistant
- 10. Bot Services Market, by Organization Size
- 10.1. Large Enterprise
- 10.2. Small And Medium Enterprise
- 10.2.1. Medium Enterprise
- 10.2.2. Small Enterprise
- 11. Bot Services Market, by Deployment Model
- 11.1. Cloud
- 11.1.1. Hybrid Cloud
- 11.1.2. Private Cloud
- 11.1.3. Public Cloud
- 11.2. On Premise
- 12. Bot Services Market, by Application
- 12.1. Customer Support
- 12.1.1. Post Sales Support
- 12.1.2. Pre Sales Support
- 12.2. IT Helpdesk
- 12.3. Virtual Assistant
- 12.3.1. Personal Assistant
- 12.3.2. Scheduling Assistant
- 13. Bot Services Market, by End User
- 13.1. Banking Financial Services Insurance
- 13.1.1. Banking
- 13.1.2. Insurance
- 13.1.3. Investment Services
- 13.2. Government
- 13.3. Healthcare
- 13.4. Retail
- 13.4.1. Brick And Mortar
- 13.4.2. Ecommerce
- 13.5. Telecom
- 14. Bot Services Market, by Region
- 14.1. Americas
- 14.1.1. North America
- 14.1.2. Latin America
- 14.2. Europe, Middle East & Africa
- 14.2.1. Europe
- 14.2.2. Middle East
- 14.2.3. Africa
- 14.3. Asia-Pacific
- 15. Bot Services Market, by Group
- 15.1. ASEAN
- 15.2. GCC
- 15.3. European Union
- 15.4. BRICS
- 15.5. G7
- 15.6. NATO
- 16. Bot Services Market, by Country
- 16.1. United States
- 16.2. Canada
- 16.3. Mexico
- 16.4. Brazil
- 16.5. United Kingdom
- 16.6. Germany
- 16.7. France
- 16.8. Russia
- 16.9. Italy
- 16.10. Spain
- 16.11. China
- 16.12. India
- 16.13. Japan
- 16.14. Australia
- 16.15. South Korea
- 17. Competitive Landscape
- 17.1. Market Share Analysis, 2024
- 17.2. FPNV Positioning Matrix, 2024
- 17.3. Competitive Analysis
- 17.3.1. Alvaria, Inc.
- 17.3.2. Amazon Web Services
- 17.3.3. Avaamo.ai
- 17.3.4. Chatfuel
- 17.3.5. CM.com
- 17.3.6. Creative Virtual Private Limited
- 17.3.7. eGain Corporation
- 17.3.8. Enterprise Bot
- 17.3.9. Google LLC by Alphabet Inc.
- 17.3.10. Gupshup
- 17.3.11. Inbenta Technologies Inc.
- 17.3.12. International Business Machines Corporation
- 17.3.13. Jio Haptik Technologies Limited
- 17.3.14. Kore.ai Inc.
- 17.3.15. Meta Platforms, Inc.
- 17.3.16. Microsoft Corporation
- 17.3.17. Oracle Corporation
- 17.3.18. Pandorabots
- 17.3.19. Pypestream
- 17.3.20. Rasa Technologies Inc.
- 17.3.21. SAP SE
- 17.3.22. ServisBOT Ltd.
- 17.3.23. Webio
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