Top 7 Moveworks Alternatives in 2026 | Tested & Reviewed 

If you’re evaluating AI agent platforms for your organization, chances are Moveworks has appeared on your radar. It’s an enterprise AI platform that has been in the headlines following its acquisition by ServiceNow. 

While Moveworks is a promising option, selecting an AI agent platform is a long-term strategic decision that goes far beyond headlines. Enterprises should carefully evaluate the depth of each platform – the use cases it truly supports, its reliability at scale, integration maturity, governance and security controls, total cost of ownership, and its track record in real-world deployments similar to their own.

Always ask yourselves:

• Can the platform support all use cases across the enterprise?
• Does it offer the features that will bring your organization to speed? 
• Will it integrate deeply with the data and systems you currently use?
• How mature are the platform’s governance, security, and audit framework?
• Is the platform’s long-term product roadmap aligned with your AI strategy?

Given these considerations, it’s natural and smart to compare Moveworks with other providers and choose a platform that truly fits your organization's current and evolving needs and delivers long-term value. 

In this guide, we break down the top Moveworks alternatives to help you evaluate your options and choose the platform that best aligns with your organizational goals.

Key takeaways (TL;DR)

• Moveworks is strong for service desk operations, but if you need agents that operate across customer service or complex operational workflows, you’ll quickly run into its limitations.
• Choosing the right alternative requires looking for scalability across departments, enterprise-grade governance, and a long-term product roadmap. 
• Top platforms like Kore.ai provide broader enterprise depth, with a wide range of use case support, flexibility to extend across the organization, stronger governance, multi-agent orchestration, and proven large-scale deployments. 
• Avoid platforms that lock you into narrow use cases or rigid architecture, and opt for solutions that evolve as your organization’s needs grow.

What is Moveworks?

Moveworks is an enterprise AI platform designed to automate employee support and handle common work requests across functions such as IT, HR, finance, and workplace operations. It uses advanced natural language understanding and reasoning capabilities to understand what employees are asking in plain language and determine the right actions to take. 

The platform is primarily positioned as a way to reduce support tickets, speed up issue resolution, and improve employee productivity by handling repetitive, high-volume requests automatically.

What are the key features of Moveworks?

Moveworks positions itself as a platform for building and running business-ready AI agents. The key features of the platform include:

• Agentic AI assistant - Moveworks’ AI can break down complex requests, plan actions, and execute them across different connected systems. 
• Service desk automation - Designed to reduce support volume by automating repetitive high-frequency requests.
• Enterprise integrations - Moveworks offers out-of-the-box integrations with systems such as ServiceNow, Salesforce, Microsoft Teams, HRIS, and more.
• Enterprise search - It can search across various data sources and knowledge bases to deliver accurate answers with context.
• Custom AI agent building - Moveworks offers no-code and low-code tools to create custom AI agents and workflows.
• Security and Governance - Moveworks includes enterprise-grade security features such as controls for data access, auditing, and permissions.

Why look for Moveworks alternatives and competitors?

Moveworks is a strong option for certain employee support scenarios, but it may not be the best fit for every enterprise, especially if your roadmap involves scaling agentic AI across more functions, deeper workflows, or broader channels. Here are common reasons enterprises evaluate alternatives:

1 - Limited use cases

Moveworks is primarily optimized for internal service desk scenarios, with a strong focus on IT and HR request resolution. For employee experience (EX) teams, this can be a good starting point. But the platform is less well-suited for broader enterprise-wide automation, such as customer service use cases, revenue operations, industry-specific workflows, or complex, multi-step business processes that span multiple departments and systems. 

If your organization is looking for an agentic AI platform that can grow beyond internal support, supporting cross-functional workflows today and more advanced use cases in the future, Moveworks may feel constrained in both scope and extensibility.

2 - Unclear long-term product roadmap post acquisition

Following its acquisition, Moveworks’ long-term product direction has become an important consideration for enterprise buyers. Large organizations should prefer strategic partners with clear, independently articulated roadmaps, particularly when AI platforms are expected to become core infrastructure. 

Forrester, in its The Forrester Wave™: Cognitive Search Platforms Q4 2025 report, notes that some customers have expressed uncertainty around Moveworks’ post-acquisition future, especially how its roadmap will evolve within a larger platform ecosystem. 

For enterprises making multi-year investments, it’s essential to carefully assess how innovation, feature prioritization, and platform openness may change over time.

3 - Limited flexibility in model choice

Moveworks typically uses a set of fixed, vendor-managed AI model options rather than supporting a fully bring-your-own-model approach. This means organizations cannot bring their own large language models or easily switch between providers. 

But enterprises increasingly want model-agnostic flexibility to optimize for data residency, compliance, cost, performance, or internal model strategies. This lack of model choice can introduce vendor lock-in and reduce long-term flexibility.

4- Gaps in enterprise-grade capabilities 

While Moveworks offers solid foundational features, it lacks several capabilities that enterprises need to scale AI agents. For instance, while Moveworks provides dashboards for agent performance, they are very basic and lack several critical capabilities that help scale agentic AI in complex environments, including: 

• Advanced agent debugging and observability 
• Bias detection and model behavior analysis 
• No-code or low-code AI testing and validation frameworks 

These features are especially important for enterprises that want to deploy, govern, and scale multiple AI agents quickly while maintaining trust, reliability, and compliance.

Additionally, Forrester notes that although Moveworks has strong data connectors for ingestion, it must expand its multimodal capabilities, particularly its ability to deeply understand and reason over indexed images, charts, and graphs. This becomes increasingly important as enterprises work with more unstructured and visual data.

5 - High operating costs and budgeting unpredictability 

For many enterprises, Moveworks’ biggest downside might be its cost and predictability at scale. Pricing is typically custom and contract-based, which can make it harder to benchmark value, forecast total spend, or compare options on an apples-to-apples basis.

In addition, deployments are often tied to multi-year agreements, which can reduce flexibility if your priorities shift or you decide to change platforms. And despite “ready-to-use” positioning, onboarding and rollout can still take months in complex environments once integrations, governance requirements, and workflow tailoring are factored in. 

All of this results in higher operational overhead and less budgeting clarity, particularly for organizations planning to expand agent coverage across teams and use cases over time.

‍Watch this webinar to learn how Agentic AI is reshaping enterprise workflows.

Top Moveworks alternatives in 2026 & beyond

Below are the top 7 Moveworks alternatives that stand out in 2026 and beyond, along with a breakdown of where they excel, the problems they solve, and the use cases they’re best suited for. 

1 - Kore.ai: Ideal for enterprises operationalizing AI agents at scale across CX, EX, and business processes

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Kore.ai is an enterprise‑grade agentic AI platform that helps enterprises quickly design, deploy, manage, and scale AI agents across the business. Unlike other platforms that cater to narrow use cases, Kore.ai offers the full range of agentic solutions for workplace productivity, customer service, or process orchestration, giving enterprises the freedom to build agents for virtually any scenario.

At the center of Kore.ai’s agent platform is its multi-agent orchestration engine. Acting as a control layer across the enterprise tech stack, it enables multiple AI agents to collaborate, hand off context, and execute tasks with differing levels of autonomy, from simple assistive copilots to fully autonomous task-executing agents.

Kore.ai’s agent platform is built with accessibility in mind. With no‑code and pro‑code agent development options, both business teams and IT teams can get agents up and running in no time. To accelerate that further, Kore.ai offers an Agent Marketplace with 300+ pre-built AI agents and templates, so organizations can start from proven building blocks instead of reinventing common workflows.

Under the hood, the platform stays intentionally flexible. Its model-agnostic, cloud-agnostic, and data-agnostic architecture lets enterprises choose any LLM they prefer, including bringing their own in-house models, running them in any environment, and connecting to virtually any data source. Simply put, this flexibility ensures businesses are never locked into a single ecosystem.

Kore.ai’s pricing is equally flexible and scalable. It provides options for session-based, usage-based, and per-seat-based models. For larger deployments, Kore.ai offers tiered volume pricing, plus the flexibility to move up or down tiers as usage changes. For teams that want to start smaller and scale later, pay-as-you-go plans are also available without requiring bulk commitments.

Where Kore.ai truly comes into its own, though, is in its AI governance-first approach. The platform includes a comprehensive AI governance dashboard that provides full visibility into every agent’s decisions, actions, and performance. Enterprises can trace interactions, monitor agent reasoning, manage security guardrails, enforce role-based access controls (RBAC), and review detailed audit logs to ensure compliance and responsible AI behavior at every step.

Kore.ai’s leadership in the agentic AI landscape is widely recognized across the industry. The platform has been named a Leader in the  Gartner® Magic Quadrant™ for Conversational AI Platforms, 2025, for the third consecutive year. According to Gartner, “Kore.ai delivers a feature-rich platform that stands out for its comprehensive and well-balanced capabilities.” 

Similarly, Kore.ai has been named a Leader in The Forrester Wave™: Cognitive Search Platforms, Q4 2025. According to Forrester, “Kore has been able to capitalize on the rush to deploy 'ChatGPT for the enterprise' over the past few years.”

Kore.ai has also been named a Leader in the Everest Group’s Conversational AI & AI Agents in CXM Products PEAK Matrix® Assessment 2025. According to Everest Group, “Kore.ai supports advanced multi-agent orchestration through features such as agent collaboration, short- and long-term agent memory, agent tool access, and intelligent delegation.”

Kore.ai is trusted by over 400 Fortune 2000 companies, delivering more than $1Bn in cost savings. They have proven across industries like finance, healthcare, technology, manufacturing, telecom, and retail, with deep expertise in complex workflows. 

Key features of Kore.ai:

Some of the notable features of Kore.ai’s agent platform are:

• Multi-agent orchestration enables enterprises to design AI agents that collaborate seamlessly, share context, and execute complex workflows across customer, employee, and operations use cases.
• Enterprise-grade context, tools, and memory support both enterprise and agentic RAG, letting agents securely retrieve, reason, and act on real-time knowledge via APIs. Agents can chain retrieval with tools to complete multi-step tasks, while retaining context across interactions.
• 250+ enterprise-grade, plug-and-play integrations give agents direct access to systems like CRM, ITSM, HRIS, ERP, and data lakes. Teams can also add custom integrations or bring in any system they need, without heavy engineering.
• No-code + pro-code development framework lets business teams build visual workflows and agent logic without writing code, while developers extend functionality with APIs, custom skills, and deeper integrations. 
• Comprehensive AI governance and observability provide full lifecycle oversight with end-to-end tracing, audit logs, and real-time monitoring so enterprises can deploy AI safely, transparently, and at scale. 
• Configurable guardrails and RBAC enforce organizational policies, restrict unsafe behaviors, and manage permissions through structured role-based access control to uphold security and compliance. 
• Agent marketplace with 300+ pre-built AI agents allows enterprises to build and deploy agents up to 10 times faster and start generating ROI from the get-go.

Pros of Kore.ai: 

• Enterprise-scale multi-agent orchestration 
• Best-in-class governance and observability
• Highly flexible, model- and cloud-agnostic architecture
• Enterprise + Agentic RAG with tool-use memory
• Flexible pricing. (Request-based, session-based, per-seat, or pay-as-you-go pricing structures)
• Deep integration ecosystem with 250+ plug-and-play enterprise connectors 
• Agent marketplace with 300+ pre-built AI agents
• Proven scalability, trusted by 400+ Fortune 2000 enterprises
• Recognized as a leader by third-party analysts

Cons of Kore.ai: 

• Not suited for small and medium businesses
• Given the number of integrations, some documentation, especially for newer connectors, is still catching up.
• With a broad template library, finding the right template can take a few extra clicks.
• The wide product suite may overwhelm teams without a clear onboarding plan and defined starting points.

Overall verdict:

Enterprises looking to start small yet rapidly scale agentic AI across diverse use cases will find Kore.ai as a trusted partner of choice. With advanced multi-agent orchestration, cloud and model-agnostic architecture, and a strong focus on AI governance, Kore.ai empowers organizations to deploy AI safely and responsibly at scale. Proven in large enterprise environments worldwide, it delivers the flexibility and full control leaders demand, while driving significantly lower total cost of ownership (TCO). 

Learn how Kore.ai can help you build and scale enterprise-grade AI agents.

2 - Glean: Ideal for knowledge discovery and search 

Glean is an “AI for work” platform built to improve enterprise knowledge discovery by unifying information scattered across emails, documents, chats, applications, and knowledge bases. By integrating with a wide range of business tools, it creates a single search experience that helps employees find relevant information quickly and work more efficiently. 

The platform offers contextual search, role-aware recommendations, natural-language question answering, and an assistant that can surface insights across the entire organization. What sets Glean apart is its intent understanding and permission-aware retrieval, which helps employees access the right information without compromising security.

That said, Glean remains more focused on knowledge discovery than on full end-to-end enterprise automation. In The Forrester Wave™: Cognitive Search Platforms, Q4 2025, Forrester noted that there are a few areas where Glean is still expanding. Specifically, the report points out that Glean’s connector ecosystem is narrower than some competitors, and that its tools for enriching indexed content with added context are comparatively lighter today. 

Forrester also reports that Glean has a smaller catalog of pre-built apps and packaged solutions, which may matter for organizations that want more out-of-the-box automation. Finally, the report notes that Glean needs to strengthen its scaling efficiency for broader and more specialized use cases.

Glean follows a user-based subscription pricing model, with plans that scale based on the number of users and required features. Enterprise tiers are available for organizations needing custom integrations, enhanced administration, or advanced security and compliance controls.

Key features of Glean:

• Unified enterprise search across documents, messages, tickets, and tools.
• A knowledge graph that maps people, content, activity, and permissions to deliver personalized, context-aware search results. 
• AI Assistant that answers questions in natural language and triggers workflow actions based on retrieved insights. 
• Multimodal ingestion, allowing the platform to index structured and unstructured data, from files and emails to databases and legacy systems. 
• Permissions-aware search and governance, so users only see information they are authorized to access.

Pros of Glean: 

• Strong enterprise search capabilities 
• AI assistance for summarization and Q&A
• Enterprise-grade security with compliance controls

Cons of Glean:

• Best for knowledge discovery, not full workflow automation or complex multi-step orchestration 
• The connector set is narrower than many of its competitors
• Fewer capabilities for enriching indexed data with further context
• Limited set of pre-built apps and off-the-shelf solutions
• Scaling efficiency for broader, specialized use cases is still improving

Overall verdict:

Though Glean is still developing agentic features, its core strength lies in search and information access, not in scaling AI agents across end-to-end enterprise use cases. If you’re looking for a platform that centralizes enterprise knowledge and makes information discovery easier, but not expected to have strong agentic capabilities to run complex workflows, Glean is a competent and well-designed solution.

3 - Aisera: Ideal for service desk operations 

Aisera is an enterprise AI platform designed to automate service interactions and operational workflows across IT, HR, customer support, and other internal service functions. 

Aisera’s value centers on its ability to streamline high-volume service environments. Its pre-built workflows (“Hyperflows”) and domain-specific templates allow organizations to automate ticket resolution, handle employee queries, and improve customer support without relying solely on human agents. 

Though Aisera delivers strong out-of-the-box value for service desk automation, organizations should plan for a more time-intensive implementation. This is because configuration, tuning, and integrations often require sustained effort, and deeper tailoring may also depend on Aisera’s managed services team rather than being fully self-serve, which can extend onboarding timelines.

Also, Aisera tends to be most effective in service desk automation, particularly within IT and HR. While it does extend into CX and operational scenarios, those broader use cases are still developing compared to its core service workflows. 

Key features of Aisera:

• AI Agent System provides purpose-built agents that can coordinate decisions, orchestrate processes, and execute tasks across IT, HR, and customer support. 
• Strong security and governance ensure data protection and compliance with industry regulations.
• Agent Studio enables teams to create AI agents using low-code, no-code, and pro-code tools, supported by pre-built templates for faster setup. 
• AI Workflow Builder offers a library of pre-built actions, making it easy to construct and customize workflows.

Pros of Aisera: 

• Strong capabilities for IT and HR service desk operations 
• An extensive library of pre-built workflows 
• Deep integration ecosystem with major ITSM, HRIS, CRM, and collaboration tools

Cons of Aisera:

• Best suited for IT and HR service desk automation and not broader enterprise use cases. 
• Onboarding and customization can be time-intensive, especially for complex environments. 
• Deeper tailoring may rely on vendor-managed services rather than being fully self-serve.

Overall verdict:

Like Moveworks, Aisera is best understood as a service desk automation platform, with its strongest fit in high-volume IT and HR support environments. It’s worth shortlisting Aisera if you’re confident your agentic AI strategy will remain centred on service desk operations long term and you don’t anticipate expanding into broader CX or cross-functional business workflows.

4- Lucidworks: Ideal for commerce-focused search experiences 

Lucidworks is a search platform designed to manage, search, and analyze data from diverse digital sources. It gives organizations the tools to build search applications that help users access information efficiently. The platform supports a broad range of use cases and is now mainly focusing on commerce-oriented search experiences. 

Forrester notes that Lucidworks has strong relevance, accuracy, and tunability. The report also highlights rich usage analytics and an approach designed for resilient global search, which can be valuable for organizations running distributed search experiences across regions. 

However, Forrester, in its The Forrester Wave™: Cognitive Search Platforms, Q4 2025, notes that Lucidworks must strengthen native governance and orchestration to better meet emerging agentic needs. This matters for enterprises that want search to serve as a governed foundation for multi-step, action-taking workflows, not just information retrieval. Forrester also flags that Lucidworks’ agentic positioning is still taking shape and lacks clarity of vision on how it will differentiate in the agentic space, especially as it doubles down on commerce-related agentic capabilities.

Key features of Lucidworks:  

• Relevance tuning and hybrid search controls (keyword + vector weighting). 
• Usage analytics and behavioural signal capture to support ongoing optimization.
• Search patterns aimed at global deployments. 
• Configurable processing/query pipelines for building tailored retrieval experiences.
• Security-oriented capabilities such as authentication and security trimming patterns.

Pros of Lucidworks:

• Commerce-focused search experiences
• Provides control over relevance tuning
• Designed for global deployments 

Cons of Lucidworks:

• Needs stronger native governance and orchestration 
• Agentic differentiation and roadmap clarity remain a work in progress
• Extending beyond native capabilities can be difficult, per the Forrester report 
• Increasing commerce focus may be less aligned for teams prioritizing broader enterprise workflows

Overall verdict:

Lucidworks is a good fit for enterprises prioritizing commerce search agents, especially when search quality and global deployments are central requirements. However, organizations aiming to use enterprise search as a broader agentic foundation with strong native governance and orchestration should closely evaluate how Lucidworks’ evolving roadmap aligns with those longer-term needs.

5 - n8n: Ideal for open-source developer-led automation

n8n is an open-source workflow automation platform designed for technical teams that prioritize flexibility and customization. The platform has gained rapid adoption among developers and startups, with a growing community of more than 200,000 users, largely driven by its open architecture, self-hosting capabilities, and access to source code. 

The platform takes a hybrid approach to automation, offering both low-code visual workflows and pro-code extensibility. Developers can combine custom logic with a library of pre-built nodes and connectors to automate integrations across APIs, SaaS tools, and internal systems. This makes n8n particularly effective for building quick proofs of concept, internal tools, and lightweight automation pipelines without heavy upfront investment. 

However, n8n is fundamentally a workflow automation tool rather than an enterprise AI platform. While it supports basic AI integrations, it lacks native capabilities for AI reasoning, contextual decision-making, adaptive learning, or long-running agent supervision. There is no built-in support for multi-agent orchestration, enterprise-grade planning, knowledge graphs, or shared contextual memory across workflows. As automation complexity grows, workflows can become brittle and harder to manage at scale. 

From an enterprise perspective, governance and operational maturity are also key considerations. n8n does not provide the same level of centralized governance, observability, security controls, or lifecycle management expected in regulated or large-scale environments. Support is primarily community-driven through forums and open-source channels, where response times and depth of assistance can vary. For enterprises running mission-critical workflows, this creates risk around reliability, accountability, and long-term maintainability. 

Finally, n8n is best suited for technical workflow automation, not broader enterprise use cases such as employee experience (EX) or customer experience (CX) platforms. It does not offer native conversational AI, copilot experiences, or end-to-end orchestration across CX or EX journeys. 

Key features of n8n:

• Open-source workflow automation with self-hosting options 
• Hybrid low-code and pro-code development model 
• Library of pre-built nodes and connectors for APIs and SaaS tools 
• High flexibility for custom logic and integrations 

Pros of n8n: 

Open-source with full source code access 

Highly flexible and developer-friendly 

Suitable for rapid prototyping and automation pilots 

Self-hosting supports custom infrastructure requirements 

Cons of n8n: 

• Fundamentally, a workflow automation tool, not a native enterprise AI or agentic platform.
• Lacks built-in AI reasoning, long-term memory, or multi-agent coordination 
• Limited enterprise-grade governance, observability, and compliance tooling for regulated environments.
• Support relies largely on community forums, increasing the risk for enterprises 

Overall verdict: 

n8n is a strong choice for developer-led workflow automation, especially for teams that value open-source flexibility, rapid experimentation, and custom integrations. However, it is not designed as a comprehensive enterprise AI platform. Organizations looking to deploy AI across customer experience, employee experience, or complex, multi-domain workflows will likely find n8n insufficient in areas such as governance, AI intelligence, orchestration, and operational maturity for large-scale enterprise adoption.

6 - UiPath: Ideal for RPA-led workflow automation

UiPath is a robotic process automation (RPA) platform that has been consistently recognized by Gartner as a market leader in this category. The platform is used by enterprises to automate structured, rules-based processes across legacy systems, modern SaaS applications, and custom APIs. 

The platform offers a large ecosystem of tools, 300+ integrations, and strong support for legacy systems that many newer AI platforms struggle to access. UiPath also brings enterprise-grade security, governance, and compliance features, including role-based access control (RBAC), auditability, and centralized management. A large global partner ecosystem and developer community further reinforce its enterprise footprint. 

That said, UiPath remains fundamentally an RPA-first platform that is extending into agentic use cases, rather than being built natively for AI-driven, reasoning-led automation. RPA workflows are inherently rigid, relying on deterministic logic and UI-level interactions. As a result, automating complex, dynamic workflows can be challenging, especially when exceptions arise or when application interfaces change, often requiring manual intervention and ongoing maintenance. 

UiPath’s agentic automation capabilities are still relatively new and less mature compared to platforms designed specifically for native agentic AI. Enabling more advanced, end-to-end automation scenarios frequently requires stitching together multiple UiPath products. In practice, customers often need four to six different UiPath modules to deliver a single enterprise use case, which increases architectural complexity, implementation effort, and time to value.

Additionally, many organizations report that UiPath deployments can demand significant technical expertise, making it less intuitive for business users or citizen developers without strong technical support. 

Key features of UiPath: 

• Market-leading RPA capabilities for structured, rules-based automation 
• Broad ecosystem coverage across legacy systems, SaaS applications, and custom APIs 
• 300+ integrations and a large automation marketplace 
• Enterprise-grade security, governance, and compliance with RBAC 
• Extensive global partner ecosystem and developer community 

Pros of UiPath: 

• Proven leader in RPA with strong enterprise adoption 
• Excellent support for legacy and UI-driven systems 
• Large integration library and partner ecosystem 
• Mature governance, security, and compliance controls 

Cons of UiPath: 

• Best suited for workflow automation, not broader employee or customer-facing use cases
• Inability to automate everything with an RPA-first architecture, limiting flexibility 
• Agentic automation capabilities are still evolving and less mature 
• Multiple products are often required to enable a single end-to-end use case 
• Architectural complexity increases time to value 
• Steeper learning curve for business users and citizen developers

Overall verdict: 

UiPath is a strong fit for enterprises focused on workflow automation, especially when they need to automate structured processes across legacy systems and existing enterprise applications. However, it is less suited as a broader enterprise AI platform for end-to-end employee experience (EX) or customer experience (CX) use cases. Organizations looking to scale AI agents across CX, EX, and multi-domain workflows may find UiPath’s RPA-first foundation more complex to operationalize, and its newer agentic capabilities less mature for enterprise-wide adoption.

7 - NiCE Cognigy: Ideal for enhancing contact-center operations 

NiCE Cognigy is a contact-center-focused platform that has evolved its offering to support agentic AI for enterprise customer experience. It enables organizations to build AI agents that can manage a wide range of customer inquiries, collaborate with human agents, and operate effectively across voice, messaging, social channels, and established contact-center platforms. 

For teams running multichannel customer service, Cognigy provides an intuitive interface and a strong set of action capabilities that make it straightforward to design and deploy customer-facing agents. 

However, Cognigy’s emphasis on simplicity means that certain advanced configuration options may be less extensive than those of some other no-code and pro-code platforms. Its flow-based architecture, which evolved from traditional conversational design patterns, can also feel less flexible when teams are building very specialized or highly dynamic agent behaviors.

More broadly, now that Cognigy is part of NiCE, the roadmap may be uncertain, and some organizations may want to watch how the product settles over time. Gartner also, in its 2025 Gartner® Magic Quadrant™ report, notes that Cognigy’s strategy tends to prioritize near-term commercial execution over a longer-range product vision, which is worth keeping in mind for teams planning multi-year agentic CX programs.

Key features of NiCE Cognigy:

• Multilingual AI agents supporting more than 100 languages, allowing organizations to deliver consistent customer experiences across global markets. 
• Visual conversation flow builder with a node-based interface, making it easier for teams to design and refine conversational journeys without heavy coding. 
• Role-based access and governance controls that help enterprises manage permissions, workflows, and compliance requirements. 
• Flexible deployment options, including on-premises or private cloud, to meet varying security and infrastructure needs.
• Prebuilt omnichannel connectors for platforms such as Slack, WhatsApp, and web chat.

Pros of Cognigy: 

• Suitable for CX operations
• Robust enterprise compliance 
• Broad omnichannel support 
• Accessible visual builder 
• Extensive integration ecosystem

Cons of Cognigy:

• Flow-based architecture can feel rigid for highly dynamic use cases 
• Higher learning curve for very deep customizations 
• Roadmap may be uncertain post-acquisition
• Limited long-range product vision

Overall verdict:

NiCE Cognigy is a solid choice for organizations aiming to enhance their contact-center operations with agentic AI, offering strong omnichannel capabilities. While some advanced configurations may take time to master, NiCE Cognigy provides a capable and mature platform for teams looking to modernize customer interactions with AI-driven workflows.

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How to choose the best Moveworks alternatives and competitors?

Choosing the best Moveworks alternative is more than comparing a laundry list of features and looking for a platform that can scale with your organization. Carefully evaluate each vendor against the following criteria: 👇

1 - Scalability across use cases

Make sure the platform can scale beyond a single team or department. Many AI tools lock you into narrowly defined agents that work well for one function, say customer support, but can’t extend to sales, operations, compliance, HR, or back-office workflows. This creates pockets of automation that sit in silos, each requiring separate maintenance, separate data flows, and separate investment. 

A scalable platform should: 

• Support multiple use cases without forcing you onto different product lines or architectures 
• Allow agents to share context, data, and capabilities across departments 
• Handle more complex workflows as your automation ambitions grow 
• Expand from simple tasks to reasoning-led, multi-step operations

2 - Proven, enterprise-grade track record

When choosing a Moveworks alternative, prioritize vendors with a demonstrable history of delivering at enterprise scale. Recognition from independent analysts, such as Gartner, Everest Group, and Forrester, provides an external benchmark of maturity, stability, and product depth. 

Equally important is real-world adoption. Look for customer stories and evidence that the platform is used by a substantial number of large organizations and has been deployed successfully across complex, high-stakes environments. Partnerships, multi-year customer relationships, and references from regulated industries are all indicators of a platform that can sustain long-term value.

3 - Deep enterprise integrations 

It’s not the sheer number of integrations that matters, but whether the platform connects seamlessly with the systems you already rely on. A long integration list means little if it doesn’t cover your core stack. 

Look for platforms that offer secure, well-documented API connections, along with smooth authentication flows and robust access controls. The integration experience should feel stable and designed for enterprise environments. 

Ultimately, the right platform should slot naturally into your existing ecosystem, enabling automation across your current tools rather than forcing you to rebuild your tech stack around it.

4 - Transparent and fair pricing model 

When evaluating Moveworks alternatives, make sure the pricing model is transparent and genuinely supportive of long-term enterprise growth. You should always know exactly what you’re paying for, without hidden add-ons, unexpected usage fees, or confusing tiers that require endless back-and-forth with account managers. 

A good platform makes budgeting straightforward: the cost structure is easy to calculate, simple to explain internally, and predictable as you scale automation across departments. This becomes especially important when AI use cases grow rapidly. The last thing you want is a pricing model that becomes unexpectedly expensive the moment you expand into new workflows.

5 - Strong governance, security, and compliance  

Achieving robust security, compliance, and governance takes time, investment, and long-term discipline, so it should be a major deciding factor when choosing a Moveworks alternative. When AI agents access multiple systems, handle sensitive data, and operate across departments, you simply cannot risk weak controls or unclear ownership. 

Look for platforms that set governance and compliance into their core architecture, not as afterthoughts. Clear access controls, secure data flows, audit trails, and recognized certifications are non-negotiable for enterprise-grade AI.

Conclusion: What is the right Moveworks alternative for you? 

Choosing an alternative to Moveworks comes down to how ambitious your automation roadmap is over the next 24-36 months. Before you pick a platform, get clear on a few fundamentals: 

• Your current and future use cases: Are you solving one narrow EX problem today, or planning to expand into multiple workflows and business functions? 
• Required scale and reliability: Can the platform handle growing volumes, new regions, and more complex journeys without breaking or slowing down? 
• Flexibility across models, channels, and deployment: Do you need to bring your own models, support new channels quickly, or run in specific cloud or hybrid environments? 
• Governance, security, and guardrails: Especially in enterprise settings, can you trace decisions, enforce policies, and manage risk confidently? 
• Commercial fit: Does the pricing model align with your rollout pace and long-term operating costs? 
• Validation and maturity: What proof points exist, customer outcomes, analyst coverage, or large-scale deployments that reduce adoption risk?

In practice, each platform on this list is strong when used for the purpose it was designed for. For instance, if you only need focused use cases, Glean, Aisera, UiPath, Cognigy, or Lucidworks may fit specific needs. 

But as soon as your AI goals and strategy expand beyond one department, or you need agents that reason, collaborate, and act across multiple systems, the gaps between platforms begin to show. 

Enterprise-scale automation needs a foundation built for breadth, orchestration, deep governance, and long-term resilience. This is where Kore.ai stands out. It’s designed to operationalize AI agents across CX, EX, and business operations with: 

• Broadest sets of agentic use cases across customer experience, employee experience, and operational automation
• Multi-agent orchestration that coordinates tasks across teams, systems, and environments
• Model, cloud, and data agnostic platform
• Plug-and-play enterprise integrations built for complex environments 
• Mature governance and security frameworks 
• Flexible pricing (Request-based, session-based, per-seat, or pay-as-you-go pricing structures)
• Proven scalability, trusted by 400+ Fortune 2000 enterprises
• Recognized as a leader by third-party analysts

If you want a platform that can evolve with your organization, supporting new agents, new departments, and new automation initiatives over time, Kore.ai offers the most comprehensive, future-ready foundation.

Ready to see how Kore.ai can help you build and scale enterprise-grade AI agents? Schedule a custom demo. Not ready yet? Explore our resources section to learn more about Agentic AI.

FAQs

Q1 - Why do companies look for Moveworks alternatives? 

Organizations often explore alternatives when needed, such as broader automation beyond service desk operations, stronger enterprise integrations, more control over models, cloud environments, or data, multi-agent orchestration, mature governance, and compliance. If your needs go beyond employee workflows, a more scalable, enterprise-grade platform may be a better fit.

Q2 - What are the main alternatives to Moveworks?

• Kore.ai - Ideal for enterprise-wide use cases
• Glean: Ideal for knowledge discovery and search
• Aisera: Ideal for service desk operations
• Lucidworks: Ideal for commerce-focused search experiences
• n8n: Ideal for open-source developer-led automation
• UiPath: Ideal for RPA-led workflow automation
• NiCE Cognigy: Ideal for enhancing contact-center operations

If you need to scale across the enterprise, Kore.ai offers significantly more breadth and depth.

Q3 - What should I look for in a Moveworks alternative? 

Key factors include: 

• Scalability across different business functions 
• Clear long-term product roadmap 
• Flexibility across AI models and cloud environments
• Enterprise-grade capabilities
• Proven enterprise deployments 
• Deep integration capabilities 
• Transparent, predictable pricing 
• Strong governance, security, and compliance 

Q4 - How do I pick the right Moveworks competitor for my organization? 

Start by asking: 

• Will we expand to other departments later? 
• Do we need enterprise-grade capabilities? 
• Do we need a clear product roadmap?
• Do we need strict governance and compliance?

If the answer is yes, platforms with broader enterprise capabilities, like Kore.ai, offer more longevity.

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(Legal disclaimer: The content in this guide is intended solely for general information and does not constitute professional, legal, financial, or procurement advice. All assessments are based on publicly available materials and customer-visible product information. Any mention of competitor limitations is for comparative context, not disparagement.

As vendor products evolve rapidly, details may become outdated. Kore.ai makes no representations or warranties regarding the completeness or accuracy of competitor information, and no party should rely on this article as the sole basis for a purchasing decision.)