Agentic Index
Cognigy vs Webex AI Agent (2026)
Both build voice and chat agents for large contact centers, and they differ on how much of the stack the customer controls. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.
Cognigy, owned by NiCE and sold as NiCE Cognigy, builds agents as flows of nodes on a low code canvas, lets the customer choose its own LLM, language understanding, speech to text and text to speech, tests agents with Playbooks, and runs on premises on Kubernetes as well as on shared or dedicated SaaS. Webex AI Agent is Cisco's add on for its own contact centers, with scripted agents and autonomous agents that work toward a goal through up to ten actions, a Webex AI Pro engine chosen from US and Europe variants, and data held in one of eight regions. Choose Cognigy when you need on premises deployment or provider choice at every layer, and Webex AI Agent when Cisco's contact center already carries your calls and you want agents native to it.
This comparison is published by Agentic Index, an independent agentic AI vendor research platform. Cognigy and Webex AI Agent are each graded against the same 14 capability Agentic Index taxonomy, from the vendor's own public materials under the Agentic Index verification standard, alongside 955 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded
Choose Cognigy if
- The platform has to run on your own Kubernetes cluster or a dedicated SaaS instance.
- You want to pick the LLM, the language understanding engine and the speech providers separately.
- Saved Playbooks with assertions should test an agent before each release.
- Snapshots should promote an agent from development to QA to production.
- Your buyers ask for ISO 42001, TISAX or BSI C5.
Choose Webex AI Agent if
- Your contact center runs on Webex Contact Center, Unified CCE or Packaged CCE, and agents should use its routing and reporting.
- Contact center data has to stay in one of eight regions, including Canada, Japan, Singapore or India.
- Autonomous agents should call MCP tools and run Webex Connect flows toward a goal written as instructions.
- Knowledge base syncs should wait for approval before reaching the agent.
| Feature | C Cognigy |
W Webex AI Agent |
|---|---|---|
| Action & orchestration | ||
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Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
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CognigyIntegrations & Tool Calling Cognigy is technology agnostic by design and integrates with any CCaaS, CRM or business system, including Genesys, Avaya, NiCE CXone, Amazon Connect, SAP and Salesforce, taking authenticated action across the contact center estate. Handover Providers are configured per platform, with a NiCE CXone non integrated provider added in the 2026.9 release for handover without a platform level integration, a Salesforce MIAW provider maintained, and Agent Copilot embeddable directly in the Salesforce Agent Console. Beyond handover, Connections hold credentials, Extensions package custom Nodes, and Code Nodes and the Node Execution API reach complex legacy systems and internal tools that have no connector. The actions are transactional, and rebooking, cancellation, order status, invoice requests, payment and refunds are outcomes the agents execute. Sourcedocs.cognigy.com Handover Providers and release notes 2026.9, cognigy.com AI Ops and orchestration pageread 2026-09-06 |
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Webex AI AgentIntegrations & Tool Calling Each autonomous agent carries up to ten actions. MCP client actions connect outside tools and authenticate with OAuth2 client credentials, an API key or custom headers, and each tool run is logged as a success or failure. Fulfillment actions run Webex Connect Flow Builder flows, the route by which an agent reaches back office and CRM systems through Cisco's integration layer, and custom transfer actions route to another AI agent, a person, voicemail or a hunt group. Input entities the action needs are defined in a table or a JSON schema and filled from the conversation. MCP actions cannot be edited once created, so a change means a new action. Sourcehelp.webex.com/en-us/article/ncs9r37/webex-ai-agent-studio-administration-guideread 2026-10-11 |
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Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
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CognigyWorkflow Orchestration Agents are built as Flows of Nodes in a unified visual builder covering chat and voice together. Say and Question Nodes handle turns, LLM Prompt and LLM Entity Extract make model calls, Go To jumps within a Flow, Code Nodes and Transformers carry logic the builder does not express, Search Extract Output handles retrieval, and Handover to Human Agent is a terminal path. Agentic AI reasons across channels and orchestrates actions to move from conversation to resolution, executing transactions such as rebooking, cancellation, order status, invoice requests, payment and refunds. Flows compose into Snapshots that carry all resources, logic, content, configuration, NLU models and Extensions as one deployable unit, so each orchestration ships as a release artifact. Sourcedocs.cognigy.com Node Reference and Snapshots, cognigy.com AI Ops and orchestration pageread 2026-09-06 |
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Webex AI AgentWorkflow Orchestration An autonomous agent works toward a goal written as instructions, deciding from the conversation which of its actions to run and collecting the inputs each needs, while multistep back office work runs in Webex Connect Flow Builder flows the agent calls, with a fulfillment timeout set between 10 and 30 seconds. Custom transfers pass a conversation from one AI agent to another or to a person, announced or silent, so a team can split work across specialist agents. Scripted agents follow defined rules for structured tasks alongside them, and a tenant can hold up to 100 agents of both kinds. Sourcehelp.webex.com/en-us/article/ncs9r37/webex-ai-agent-studio-administration-guideread 2026-10-11 |
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Triggers & Channel Coverage How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools. |
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CognigyTriggers & Channel Coverage Voice, chat and digital channels are served with intelligent IVR and self service in more than a hundred languages, delivered through Endpoints that separate the agent from the channel. Webchat v3 is the web surface, and the in house Voice Gateway has its own self service portal and SIP infrastructure, with SBC configuration and TLS handling exposed in the release notes. Endpoints are kept out of Snapshots so channel configuration and agent logic version independently. In production the platform handles tens of thousands of concurrent sessions and peaks around 375,000 interactions a day, across several independent inbound queues including telephony. Work arrives by channel, and Cognigy describes no scheduled or event driven triggers. Sourcedocs.cognigy.com Endpoints, Voice Gateway and release notes, cognigy.com platform pageread 2026-09-06 |
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Webex AI AgentTriggers & Channel Coverage Calls and digital chats reach the agent through the contact center's own entry points and routing, in Webex Contact Center, Webex Contact Center Enterprise, Unified CCE, Packaged CCE and, in an alpha release, Unified CCX. Digital agents come with the voice subscription order, and Webex Connect Flow Builder hands chats to an agent through its Virtual Agent V2 activity. The agent answers before a customer reaches a person and hands back into the same queues. On voice, callers can interrupt the agent mid reply, and a session closes after three prompts in a row go unanswered. Cisco names voice and chat as the channels, without SMS or WhatsApp. Sourcehelp.webex.com/en-us/article/ncs9r37/webex-ai-agent-studio-administration-guideread 2026-10-11 |
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| Knowledge & context | ||
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Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
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CognigyKnowledge Grounding & RAG Knowledge AI is a retrieval product with its own license, quota model and vector store. Customers upload knowledge as PDF, Cognigy Text or web pages, or connect external systems through Knowledge Connectors, to create Knowledge Sources, and agents use RAG over those documents to give accurate, context aware responses. Retrieval is wired into the Flow through the Search Extract Output Node for agents and the Copilot Knowledge Tile for human agents, which returns source links naming the files an answer came from. The corpus is licensed in Knowledge Chunk quotas allocated across organizations through the Management UI or the Cognigy.AI API, and on premises installations use Weaviate as the vector database, with operators told to upgrade it to v1.22.5. Sourcedocs.cognigy.com Knowledge AI overview and activation, release notes 4.68read 2026-09-06 |
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Webex AI AgentKnowledge Grounding & RAG Knowledge bases take files such as PDFs, Word documents, Excel workbooks and CSV files, written articles and website crawls, up to 2GB and 100 files per knowledge base, 10MB per file and 300 pages per PDF, and one knowledge base can serve several agents. A crawl reaches up to 250 pages at a depth of up to two links, across up to 10 URL patterns and 10 subdomains, and spreadsheets can hold up to 3,000,000 characters. Web sources show a syncing status while content is extracted, and with content approval on, a sync waits as pending approval until someone approves or declines the changes. Payment card, personal and health data are meant to stay out of knowledge bases. Sourcehelp.webex.com/en-us/article/ncs9r37/webex-ai-agent-studio-administration-guideread 2026-10-11 |
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Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
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CognigyMemory & State Persistence Conversation context carries across channels, so a handover keeps history intact, and the Interaction Panel lets a developer inspect what sits in the agent's memory during a session. Cognigy does not say what an agent keeps about a contact between separate conversations, whether state is scoped per user, per session or per organization, how long it lasts, or how an operator inspects or deletes it for one person. Knowledge Sources hold knowledge, not memory. The developer reference is large, and a state model behind the memory inspection may be described there. Sourcedocs.cognigy.com Interaction Panel and Developer Referenceread 2026-09-06 |
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Webex AI AgentMemory & State Persistence Within a conversation the agent fills input entities and keeps them for its actions, and global variables pass values into reports. Each session starts fresh. The studio keeps no memory that carries what a customer said in one conversation into the next, and transcripts are purged automatically after 90 days. Sourcehelp.webex.com/en-us/article/ncs9r37/webex-ai-agent-studio-administration-guideread 2026-10-11 |
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| Control & trust | ||
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Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
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CognigyHuman Oversight & Guardrails Handover Providers are configured per contact center platform, a dedicated Handover Flow controls the interaction with the human agent and the transfer, and a Handover to Human Agent Node sits in the Flow. Agent Copilot workspaces then suggest next actions and surface knowledge with source links to the person now holding the conversation. Escalation is a designed path that keeps context intact, and role based access control enforcing separation of duties limits who can change agent behavior. There is no review and approve step over agent output, such as a pre send queue, draft review mode, confidence threshold or per action sign off. The agent answers and acts on its own until a Handover Node or a configured condition moves the conversation to a person. Sourcedocs.cognigy.com Agent Copilot getting started, Handover Providers and Handover Featuresread 2026-09-06 |
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Webex AI AgentHuman Oversight & Guardrails Agent handover to a human is on by default for every autonomous agent, and custom transfers send callers to a person, a queue or voicemail. Built in guardrails keep the agent from unethical or harmful replies, the instruction optimizer tones down abusive or overly strong wording for the team to accept or discard, and knowledge syncs can be held for a person to approve. EU deployments show an AI transparency notice by default, and previews can show it too. No person approves an individual action before it runs. Sourcehelp.webex.com/en-us/article/ncs9r37/webex-ai-agent-studio-administration-guideread 2026-10-11 |
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Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
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CognigySecurity, Identity & Governance Cognigy's public trust center lists ISO 27001, ISO 27701 and ISO 42001, the last of which certifies an AI management system specifically. Cognigy also holds SOC 2 Type II and PCI DSS 4.0, the latter with independent QSA attestation, along with the TISAX and BSI C5 attestations, GDPR and HIPAA alignment, and work under way mapping SOC 2 controls to HITRUST CSF. Access is governed by granular role based access control enforcing separation of duties, with the Management UI distinguishing admin rights for organization level tasks such as allocating Knowledge Chunk quotas, alongside end to end encryption in transit and at rest and detailed audit logs. Sourcetrust.cognigy.com, docs.cognigy.com Administration and Knowledge AI activationread 2026-09-06 |
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Webex AI AgentSecurity, Identity & Governance Five administrator roles, full, contact center service, provisioning, read only and supervisor, govern AI Agent Studio through Control Hub or Webex Connect, and custom roles can carry narrower permissions such as viewing the audit log. Transcript access is off by default until a full administrator grants decryption through the enterprise profile, tenant encryption keys sit in a key management service, no Cisco employee accesses raw audio or text during inference, and recording playback switches off when payment card data is detected. Webex as a whole holds ISO/IEC 27001 certification and supports HIPAA and GDPR use, but no certification is tied to AI Agent itself, and MCP actions do not support group level access control. Sourcehelp.webex.com/en-us/article/ncs9r37/webex-ai-agent-studio-administration-guideread 2026-10-11 |
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Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
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CognigyObservability & Auditability Detailed audit logs capture every configuration change and user action, recording who altered the agent and when, and cover platform administration as well as conversations. The Interaction Panel executes a Flow node by node in Debug Mode against a chosen Flow, Locale and Snapshot, shows the agent's memory during a session, and can follow a live session by user identifier, so a specific run can be reconstructed step by step. Insights transcripts, from which a Playbook can be generated, and analytics and reporting across the conversational estate sit alongside. Sourcedocs.cognigy.com Interaction Panel and Insights, cognigy.com AI Ops and orchestration pageread 2026-09-06 |
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Webex AI AgentObservability & Auditability Session lists and session details show each conversation an agent handled, filtered by test sessions, handovers, errors or downvoted replies, and MCP tool runs record success or failure. Analytics count sessions, sessions resolved with no human involved, handovers, messages and users, each with daily averages, and custom reports cover AI agent call records and outcome distribution, with scripted agents adding views for training, responses and curation. Each publish saves a version, and change logs record who changed what, where and when, searchable by admins, AI agent developers and custom roles with audit log access. Sourcehelp.webex.com/en-us/article/ncs9r37/webex-ai-agent-studio-administration-guideread 2026-10-11 |
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Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
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CognigyDeployment & Data Residency Cognigy runs as a self hosted product as well as a service. Release notes for on premises installations cover a YAML based data redaction configuration introduced in the 2026.9 release to replace environment variables, with rollout percentage control and per organization exclusions via values.yaml, an ingress controller feature flag governing Traefik middleware resources, parameterized certificate secret names in the sbc-sip DaemonSet and StatefulSet, a Weaviate version upgrade instruction for on premises installations running Knowledge AI, and a concurrency limit for Playbook execution set through values.yaml. Licensing distinguishes shared SaaS, dedicated SaaS and on premises routes, with Knowledge AI quotas administered differently for each, so a customer can run Cognigy inside its own infrastructure with Kubernetes level configuration exposed to the operator. The on premises route needs an operator able to run the underlying Kubernetes cluster. Sourcedocs.cognigy.com release notes 2026.9, 4.68 and 4.72, Knowledge AI activationread 2026-09-06 |
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Webex AI AgentDeployment & Data Residency Contact center data is stored in one of eight regions, the United States, the United Kingdom, the European Union, Canada, Japan, Australia, Singapore and India, and Webex AI Pro US and Europe engines serve customers in the US and the EU. GPU based model and speech processing can run outside the home region, Azure OpenAI runs globally for several regions, and EU inference stays in the EU even during failover. Cisco's residency tables disagree with each other in places, so exact processing locations outside the EU carry some uncertainty. Sourcehelp.webex.com/en-us/article/9qrsly/data-security,-privacy,-and-residency-in-webex-contact-centerread 2026-10-11 |
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| Solution readiness | ||
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Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
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CognigyPrebuilt Agents, Templates & Packs Customers get reusable parts to assemble into their own agents. The Node library covers conversation, logic, LLM prompting, entity extraction and handover, Extensions package custom Nodes, Packages export and import resources, including Knowledge AI resources and Playbooks, between installations, Snapshots capture a complete agent as a portable archive, and prebuilt handover providers and connectors cover the contact center estate. These move work between projects and environments. There is no template gallery, agent library, industry starter pack or marketplace of prebuilt agents, so the route to a live agent is building a Flow from Nodes, configuring Endpoints and handover, and testing it with Playbooks. Sourcedocs.cognigy.com Extensions, Packages, Node Reference and Snapshotsread 2026-09-06 |
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Webex AI AgentPrebuilt Agents, Templates & Packs A new AI agent starts from scratch or from a predefined template, for scripted and autonomous agents alike, and a tenant holds up to 100 agents across both types. Each agent's details export as JSON. Cisco does not name the templates outside the studio itself. Sourcehelp.webex.com/en-us/article/ncs9r37/webex-ai-agent-studio-administration-guideread 2026-10-11 |
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| Platform extensibility | ||
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Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
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CognigyModel Flexibility & Routing The customer sets up an account with one of the supported LLM providers, configures the provider in Settings and selects the model from the supported list, and individual Nodes state which model capabilities they need. The provider set is maintained as a shipped feature, and the 2026.9 release added Google GenAI as a provider with the Gemini 3 family, including gemini-3.1-pro-preview, gemini-3-flash-preview and gemini-3.1-flash-lite-preview. Customers are subject to the terms of the generative AI providers they use, and Cognigy disclaims responsibility for those services, since the customer holds the provider relationship. The same choice extends beyond the language model to natural language understanding, speech to text and text to speech, so the customer assembles the stack, brings the account, selects the model and can swap it later. Sourcedocs.cognigy.com Generative AI and LLMs section, 2026.9 release notes, Knowledge AI overviewread 2026-09-06 |
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Webex AI AgentModel Flexibility & Routing Each agent runs on an AI engine the team picks from the Webex AI Pro family, with standard, US and Europe variants in 1.0 and 2.0 versions and the 1.0 engines due for deprecation. Pro 2.0 handles multilingual contact centers, while the US and Europe engines are English only, and scripted agents run on Webex AI Agent Pro engines with Swiftmatch. The engines are Cisco's own packaging over models that include Azure OpenAI, and a team cannot pick a model provider directly. Sourcehelp.webex.com/en-us/article/ncs9r37/webex-ai-agent-studio-administration-guideread 2026-10-11 |
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APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
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CognigyAPIs, SDKs & MCP Extensibility The Developer Reference covers the Cognigy.AI API, the Playbooks API with its own OpenAPI specification for creating and scheduling test runs remotely, the Node Execution API function reference and the Knowledge Connector API function reference. Extensions build custom Nodes, Packages move resources between installations, and Code Nodes, Transformers and CognigyScript let builders drop to code where the low code builder stops. Administration APIs reach the Management UI, and Knowledge Chunk quotas can be set through the API as well as the interface. An outside caller can drive Cognigy to run a test, execute a node, feed a knowledge connector or administer an organization. Cognigy describes no MCP server for the platform. Sourcedocs.cognigy.com Developer Reference, Playbooks, Knowledge Connector API and Node Execution APIread 2026-09-06 |
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Webex AI AgentAPIs, SDKs & MCP Extensibility Webex for Developers carries Webex Contact Center APIs and a web SDK for contact center applications. Agents themselves are built, tested and published inside the studio, with each agent's details exportable as JSON, and the MCP support in the studio points outward to other tools. Sourcedeveloper.webex.com/webex-contact-center/docs/webex-contact-centerread 2026-10-11 |
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Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
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CognigyTesting, Debugging & Optimization Playbooks are Cognigy's test tool. A Playbook holds up to 50 Steps, each carrying input text and data sent to the agent and Assertions that check the response and aspects of the Flow against a defined value, and assertions can be inverted to check that a value is absent. Runs execute as background Tasks with results in a Runs tab filterable by status and creator. Up to ten Playbooks run at once, with the limit configurable on premises through MAX_CONCURRENT_PLAYBOOK_EXECUTIONS in values.yaml, and a Playbooks API allows remote creation and scheduled runs against the OpenAPI specification. Playbooks can be generated from a live conversation or an Insights transcript and exported as a Package, and Cognigy calls them automated QA testing for regression. The Interaction Panel adds manual runs against a chosen Flow, Locale and Snapshot with node by node debugging, and Snapshots package a complete agent for promotion between development, QA and production endpoints. Sourcedocs.cognigy.com Test section, Playbooks and Interaction Panel, Cognigy support center Playbooks guidanceread 2026-09-06 |
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Webex AI AgentTesting, Debugging & Optimization Agents can be previewed at creation, while being edited and after deployment, through a preview widget, a chat preview or a voice preview, with voice preview available through Control Hub. The Sessions page separates test sessions from live ones and filters handovers, errors and downvoted replies, and scripted agents have their own test and curation views in analytics. Autonomous agents have no saved test cases with pass or fail results. Sourcehelp.webex.com/en-us/article/ncs9r37/webex-ai-agent-studio-administration-guideread 2026-10-11 |
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| Specialist automation | ||
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Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
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CognigyBrowser & Computer Use Agents reach outside systems through Handover Providers, Connections, Extensions, Code Nodes and the Node Execution API, all credentialed programmatic paths, and act on backend systems through APIs and connectors. Cognigy's own surfaces are Endpoints, a Webchat widget, a Voice Gateway and the Agent Copilot workspace embedded in a contact center console, which are channels the agent speaks through or Cognigy's own interfaces. The agents do not control a browser, desktop or remote computer. Sourcecognigy.com AI Ops and orchestration page, docs.cognigy.com Node Reference and Extensionsread 2026-09-06 |
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Webex AI AgentBrowser & Computer Use Agents act through MCP tools, Webex Connect flows and transfers, and website crawls feed knowledge bases when content is added. No hosted browser, remote desktop or screen control is part of the studio. Voice agents collect keypad entries from callers, with digit timeouts and lengths of up to 32 characters, but never drive another system's screen. Sourcehelp.webex.com/en-us/article/ncs9r37/webex-ai-agent-studio-administration-guideread 2026-10-11 |
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Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing | C Cognigy |
W Webex AI Agent |
|---|---|---|
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Entry price Lowest public entry point |
No price is published. Cognigy is enterprise only and quote based. | No public price. AI Agent is an add on to the Webex Contact Center Flex 3.0 license, or ordered through Cisco Commerce Workspace for Webex Contact Center Enterprise and Cisco's Unified contact centers. |
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Pricing confidence How public the numbers are |
Contact only | Contact only |
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Billing Primary billing axis |
A platform license plus usage, with telephony for voice and implementation services billed alongside. | An add on to the contact center license, metered in a unit Cisco does not disclose. |
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Variable cost Workload / overage exposure |
High variable cost | Medium variable cost |
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Free tier / trial Try before you buy |
No free tier
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No free tierTrial
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Buying motion Self-serve vs sales call |
Sales call | Sales call |
NiCE acquired Cognigy in 2025, and it is sold as NiCE Cognigy within CXone Mpower. Webex AI Agent is a Cisco product sold as an add on. Neither lists prices publicly.
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