| Key features | - Agent Orchestration - agents work on real cases with people in the loop
- Policy Controls & Governance - set what agents can and cannot do at runtime
- Observability & Audit Trail - every decision traceable and logged
- Case Management - complex long-running cases with dynamic routing
- Open-Standard Engines - BPMN, CMMN, and DMN
- Enterprise Cloud - secure, scalable cloud deployment
- Human-in-the-loop - people and agents share processes with sign-off
- Seamless integrations with third-party systems via REST APIs
- AI agent integration with OpenAI, Anthropic, Azure AI, AWS Bedrock
| - Connects to 15+ data systems including Snowflake, Databricks, BigQuery, Redshift, dbt, Airflow, Tableau, Looker, Power BI and Postgres
- Extracts structural metadata including databases, schemas, tables, views, columns and relationship lineage
- Provides Web-UI, MCP server and REST APIs for accessing semantic context
- Automatic incremental updates with configurable sync schedules from on-demand to daily or weekly
- Role-level access controls and data classifications including PII, PHI and SPII
- Only reads metadata without accessing or moving actual data from systems
- Integrates with quality monitoring tools including Monte Carlo, Anomalo and Bigeye
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| What makes it different | - Purpose-built for regulated industries where every action must be attributable, defensible, and reversible
- Open standards (BPMN, CMMN, DMN) prevent vendor lock-in with transparent, portable processes
- Proven at scale - trusted by 600+ enterprises, processes 1 billion events daily
- Built-in compliance and audit trails for regulated work requiring transparency and accountability
| - Eliminates confident AI mistakes by grounding agents in semantic context instead of having them guess from table names
- Reduces AI token costs and speeds up answers by resolving schema and joins once upstream instead of in each agent query
- Ensures consistent answers across all agents and teams using the same definitions and business logic
- Provides complete traceability and auditability of AI decisions with documented context and ownership
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Flowable
Kanlet