Appian vs Bizagi (2026)

Agents "perform actions such as routing cases, updating records, or starting processes" through tools; process models configured as tools create or update records through a Write Records node; the Query Records tool reads synced record types; and "AI agents can also use external tools hosted on MCP servers".

The platform and pricing pages list 200+ prebuilt connectors, REST and SOAP, and ODBC, JDBC and message queue integration, with Snowflake and Kafka on Advanced and Premium. Process models, expression rules and other agents serve as custom tools. Query Records is read only and does not apply record security expressions, and writes go through process models.

Sourcedocs.appian.com 26.8 create-and-configure-ai-agent, ai-agent-reference; readread 2026-09-17

Agents act through AI Actions. A builder links connectors already set up in the project, SAP BTP connectors or MCP servers reached over server sent events, picks which of their actions the agent may use and writes the goal into the prompt, and the agent decides when to call each one, with up to 100 actions in total. MCP servers authenticate with an API key sent as Basic, Bearer or a custom header. Agents can gather more data, act in outside systems and start processes in Bizagi or third party systems this way.

Sourcehelp.bizagi.com/platform/en/ai_actions.htmread 2026-10-13

Appian combines deterministic process steps with agent steps. "Process agents run inside a process model using the Execute AI Agent smart service", where the agent interprets the prompt, selects tools and executes each step.

The configuration guide says: "Keep deterministic or rule-based logic (such as conditional flows, validations, or calculations) inside the process model itself, and let the AI agent handle only the reasoning or decision steps." Process models serve as agent tools, and "agents can be added directly as tools" for multi agent collaboration up to two levels deep. A flow can therefore sequence, branch, retry and route around autonomous agent steps, and agents are versioned.

Sourcedocs.appian.com 26.8 agent-studio, create-and-configure-ai-agent, ai-agent-reference; readread 2026-09-17

Agents run inside BPMN processes built in Bizagi Studio, as an action on an AI task that fires when a case enters or leaves it, from a button on a form, from entity forms or inside data pipelines, and Master and Persona entities can now run an agent as an Entity Action with its own input and output mappings. Several agents can run in one process, side by side or one after another, and their outputs map to typed fields in the data model, so later steps, business rules and people use them like any other case data.

Sourcehelp.bizagi.com/platform/en/ai_agents.htmread 2026-10-13

Process agents run as a step inside a process model through the Execute AI Agent smart service, so they start whenever the process does, and the AI Agents overview says agents "trigger workflows automatically" and are used to automate case triage.

The pricing entitlements list consuming events from external Apache Kafka topics on Advanced and Premium as a way to start a process, so an outside event can reach an agent with nobody asking. Chat agents respond when an end user messages them.

Process start events such as timers, record events or messages are not described for agents, and many runs in the agent summary's Initiator field are started by people.

Sourcedocs.appian.com 26.8 agent-studio; appian.com/products/pricing (read 7 August 2026); readread 2026-09-17

An agent on an AI task runs whenever a case reaches that task, with no one asking. Cases themselves start from a timer start event on a schedule, from a message or signal thrown by another process, from events Bizagi consumes off Kafka topics, or from a person in the work portal, and AI Jobs in the Management Console schedule and monitor AI work on their own. Agents can in turn trigger events that start processes in Bizagi or in other systems, and processes can publish events back to Kafka.

Sourcehelp.bizagi.com/platform/en/start_events.htmread 2026-10-13

Agents query record data with the Query Records tool, which can join across related record types, over synced record types: Appian's data fabric keeps a synchronized copy of the customer's source data that stays queryable, so new knowledge is available without retraining.

Agents also connect to enterprise data and documents, using document resources to retrieve context and AI DocCenter models for trained extraction, and the same SQL API infrastructure backs the data fabric tools on the Appian MCP Server. Unsynced and legacy record types, smart search and record security expressions are not available to the Query Records tool.

Sourcedocs.appian.com 26.8 ai-agent-reference, create-and-configure-ai-agent; readread 2026-09-17

Enterprise Knowledge holds catalogs that are processed, indexed and served through retrieval augmented generation while agents run, kept in a vector database that serves retrieval and never trains a model.

File Knowledge builds a catalog from content extracted from documents and serves AI Agents, AI Workers and the Ask Ada assistant, and Bizagi Data Knowledge builds one from records stored in Bizagi entities for AI Agents. Catalogs sit in categories in Studio's AI Hub and are reindexed after a deployment or update.

Agents can also find conceptually similar past cases without exact keyword matches, and the knowledge can extend or replace an agent's default instructions with a company's guidelines and procedures.

Sourcehelp.bizagi.com/platform/en/enterprise-knowledge.htmread 2026-10-13

Conversation persistence "stores chat interactions between an end user and a chat agent across sessions". Each conversation is stored as a session tied to a specific user and chat agent; users can return to and switch between earlier sessions without losing context, and the agent keeps prior messages within a session.

Each session belongs to a single user (other users cannot view, access or share another user's sessions), conversations are retained for audit purposes and end users cannot clear them, and sessions are tied to the environment where they were created. Users cannot delete their history, process agents carry no memory beyond the process, and learning agents have been announced but not shipped. Process and case state belongs to the application's own records.

Sourcedocs.appian.com 26.8 conversation-persistence-chat-agents; readread 2026-09-17

Each agent call works from inputs mapped from the case and the knowledge catalogs attached to it, and writes its outputs back to case fields, so the case carries the state while it runs. Inputs can run to 500,000 characters, so whole documents and long case histories can be passed in on each call. An agent keeps no memory of its own that it reads from one case to the next.

Sourcehelp.bizagi.com/platform/en/ai_agents_faqs.htmread 2026-10-13

Oversight comes from the process around each agent. Process agents run as one step inside a process model, and the documentation tells designers to keep conditional flows and validations in the process and let the agent handle only the reasoning or decision step. The human task, review and escalation nodes of the surrounding process then decide what happens to the agent's output, so approvals can be placed at the node level around any agent step.

The AI Agents overview names "combining AI reasoning with optional human oversight" as a core use, agents fail to start when the person starting them lacks access to a required tool, and Appian's AI agents page describes actions and escalations to people managed in the same workflow. No approval tool specific to agents or per action approval setting is described, so approvals sit in the process design around the agent.

Sourcedocs.appian.com 26.8 agent-studio, create-and-configure-ai-agent; readread 2026-09-17

AI Workers take on tasks people would normally do in one of three modes. In supervised processing the worker does as much of the task as it can and hands it to a person to review or finish, conditional processing follows rules the customer sets to decide when it works alone, and autonomous processing falls back to a person whenever it cannot finish. Each decision comes with its reasoning for a person to check, and agent outputs land in form fields that people review before a case moves on.

Sourcebizagi.com/en/platform/ai-workersread 2026-10-13

Access controls apply to every agent action. "When an AI agent invokes a tool, user access determines whether the process continues or stops", an agent "fails to start if the initiator doesn't have access to required tools", and a sub agent "must respect all access controls defined for that sub-agent". Chat sessions are scoped to the user who started them.

On the FedRAMP Marketplace Appian holds two authorizations, High for Appian Government Cloud and Moderate for its Moderate edition, Appian Government Cloud also holds a DoD Impact Level 5 provisional authorization from DISA, and Appian is SOC 1, SOC 2, SOC 3, ISO 27001 and HITRUST CSF certified. Appian's private AI commitment is never to train on customer data.

Sourcedocs.appian.com 26.8 ai-agent-reference; appian.com/support/resources/trust/compliance; read 2026-09-17; FedRAMP Marketplace and appian.com/industries/public-sector/appian-government-cloud, readread 2026-10-12

Bizagi holds ISO/IEC 27001:2022, its cloud for US government is FedRAMP Moderate, and independent reviews found the cloud meets HIPAA and HITECH requirements. Users sign in through SAML, OAuth or LDAP with two factor authentication, role based segregation of duties and delegated administration govern who can do what, and roles can be kept in step with Microsoft Entra ID. Data is encrypted in transit and at rest, each customer's applications and data are isolated, and an annual transparency report covers government requests for customer data.

Sourcebizagi.com/en/platform/complianceread 2026-10-13

Each agent run can be inspected afterward, step by step. The run history "uses a timeline layout that displays each step chronologically, including tool calls, AI agent reasoning, and outputs".

A Monitor view logs every agent request with run ID, agent version, status, request, AI actions consumed, tool call count, initiator, duration and start time, per agent and across agents, and active runs can be stopped. System level audit logs for AI agent executions track all AI interactions and can optionally capture prompts and responses, separate from the runtime traces. Feedback and LLM grading are part of testing, and Process HQ's process mining covers processes.

Sourcedocs.appian.com 26.8 monitor-ai-agents, ai-agent-reference; readread 2026-09-17

Tracing in the Management Console records AI agent invocations, the requests and responses of the connectors an agent calls, tagged with the case number, and the responses AI Workers produce, at error, warning or information level, and AI Workers show the rationale behind each decision.

Traces are kept for 90 days and are meant for troubleshooting, with the platform's audit and accountability controls kept apart from them. An AI consumption report traces usage to processes, tasks, entities and applications and shows the models and tokens behind each execution, and an AI Metrics dashboard tracks agent use over time by process and by agent.

Sourcehelp.bizagi.com/platform/en/tools-tracing.htmread 2026-10-13

Appian runs in several named environments. Appian Cloud is managed SaaS across multiple cloud regions. Appian Government Cloud runs in an AWS GovCloud virtual private cloud with full commercial feature parity, including AI. Customers can also self manage on Kubernetes (with RPA included from release 24.2), deploy hybrid on AWS, Azure or Google, or run on premises. Agent Studio is included in the Advanced and Premium tiers, and whether agents are available on self managed installs is not stated. Appian Cloud has been reported to run in 24 regions.

Sourcedocs.appian.com 26.5 appian-government-cloud-overview; appian.com/products/pricing; read 7 August 2026, datedread 2026-09-17

Each customer gets a dedicated cloud setup with isolated storage and its own URL, provisioned in the Azure geography it picks at onboarding, US, EU, Asia or US Government, and every service and resource stays inside that geography. Bizagi chooses the exact Azure region within it. Production data is replicated to a paired region and backed up nightly, with a 5 minute recovery point and a 3 hour recovery time.

Sourcehelp.bizagi.com/platform/en/available-regions-for-bizagi-c.htmread 2026-10-13

AI skills come as packaged automation for defined work (classification, extraction and summarization), alongside packaged industry solutions and an application template library, and the 26.8 release adds AI DocCenter extraction and classification models that agents call through a process model. Each can be adopted on its own. No catalog of prebuilt AI agents is offered beyond those skills and solutions. Appian also promises a first application in eight weeks, delivered as a service.

Sourceappian.com/products/platform/artificial-intelligence (read 7 August 2026); docs.appian.com 26.8 create-and-configure-ai-agent; datedread 2026-09-17

AI agent templates deploy straight from Bizagi Studio, with 13 for banking and investments, 7 for customer service and 10 for manufacturing and retail, grouped into predefined Solutions a builder can search by Solution, title or description. They cover jobs such as generating and comparing earnings reports, categorizing customer incidents, obfuscating personal data, composing incident responses, writing knowledge base articles, translating policies, comparing vendors and summarizing RFx responses. Bizagi Copilot helps refine a template's prompt in plain language.

Sourcebizagi.com/en/platform/ai-agent-templatesread 2026-10-13

Designers choose the model for each agent. "AI agents use the model configured in the Model Selection section of the Advanced tab." By default new agents use Auto, "which uses the latest model from the configured provider with automatic fallback", and designers "can also select a specific model or route execution through your own provider account". Which models and providers are on that list is not stated.

Sourcedocs.appian.com 26.8 create-and-configure-ai-agent; readread 2026-09-17

Agents run on Azure OpenAI through Bizagi's private GPT service. For each agent a builder picks a model from those OpenAI currently offers, which change with OpenAI's updates and deprecations, choosing between direct response models and reasoning models with a set reasoning level, and tunes temperature, top p, frequency penalty and presence penalty. Files as inputs need GPT 4o or a newer model. Every choice stays within OpenAI's models, with no option to bring another maker's model or a customer's own deployment.

Sourcehelp.bizagi.com/platform/en/ai_agents_from_scratch.htmread 2026-10-13

Outside agents and systems can call Appian, and Appian agents can call out. The Appian MCP Server's data fabric tools share the agents' SQL API infrastructure, so outside agents can reach Appian. Organizations can administer their own Appian MCP servers so third party agents reach Appian business rules, processes and data, alongside Appian's REST and SOAP web APIs. Appian's own agents also consume external MCP tools, so MCP runs in both directions. Appian also describes Composer, an MCP representation of the entire application estate.

Sourcedocs.appian.com 26.8 ai-agent-reference; Appian World 2026 release (read 7 August 2026); datedread 2026-09-17

The Bizagi API is a RESTful service on OData 4.0 with OAuth 2 bearer tokens, so outside applications can start cases for a process, search cases and work with process data. A JSON file in Swagger 2.0 and OpenAPI 3.0 format describes every OData endpoint for middleware, a full service index lists them, and examples include C# code. Since the Summer 2026 release a REST API also exports and imports deployments, so a team can automate releases from its own pipeline, and API traces can be switched on for debugging.

Sourcehelp.bizagi.com/platform/en/api_odata.htmread 2026-10-13

Evaluation covers agents before and after deployment. Agents are tested in a test pane (process agents) or a chat test experience before deployment, and the AI Agent Reference lists three feedback sources for both agent types: developer feedback at design time in the test pane, an automated LLM grader, and dev and ops feedback in production, with chat agents appearing in the same quality metrics as process agents. The AI Agents overview lists "test and monitor other AI agents to ensure reliable performance" as a supported use, and agents are versioned.

No test suites built on fixed datasets are documented.

Sourcedocs.appian.com 26.8 ai-agent-reference, agent-studio, monitor-ai-agents; readread 2026-09-17

Builders try an agent in a Test Prompt window, which runs one input file at a time, shows which actions the agent called, and can differ from what happens at run time. AI Workers in supervised mode learn from each user after the 50th interaction on a task, building a personal policy from that user's behavior and feedback, and a team can switch that reinforcement learning on or off per task. Bizagi has retired its Autotesting tool, and there is no saved test set, quality gate or measure of how the learning changes results before an agent goes live.

Sourcereleasenotes.bizagi.com/en/release-notes/releases/fall-2025read 2026-10-13

Real application interfaces are controlled through Appian RPA. RPA is a licensed part of the platform, sold by bot count per tier and available to self managed Kubernetes customers from release 24.2, and Appian RPA bots operate the interfaces of applications that expose no programmatic route. These are deterministic bots that work application screens. The agents' tools, which are process models, expression rules, other agents, system tools and external MCP tools, include no computer use tool, so an AI agent does not choose and drive a screen session itself.

Sourceappian.com/products/pricing, /industries/public-sector/appian-government-cloud (read 7 August 2026); docs.appian.com 26.8 create-and-configure-ai-agent; datedread 2026-09-17

Screen level work runs through RPA bots from partners such as Automation Anywhere, which handle manual tasks while Bizagi manages the flow of data between people and robots. The bots and their runtime come from the RPA vendor, and Bizagi's own agents do not drive a browser or desktop themselves.

Sourcebizagi.com/en/solutions/robotic-process-automation/automation-anywhere-and-bizagiread 2026-10-13