DOCSEARCHbyAlgolia
Submit Docs

Fenergo Documentation

website·Indexed 31 days ago

https://docs.fenergox.com

User guides and release notes for Fenergo, featuring documentation on Advanced Reporting, dashboards, the Investor Portal, and API changelogs. Includes details on risk assessment endpoints, entity-level access logic, and integration with data providers like OpenAI, Orbis, and LexisNexis.

Tokens
777.1K
Snippets
1.3K
Records
5.8K
Agent score
54%

What's inside Fenergo

  1. Overview of Advanced Reporting in Fenergo SaaS

    The Advanced Reporting feature allows users to extract data from the Fenergo SaaS platform using standard Structured Query Language (SQL). Because the platform uses a NoSQL database internally, data is re-aggregated into a relational-style table structure to support SQL queries. The results of these queries are returned as CSV files.

  2. Overview of Merge Config in Enterprise Control Plane

    Merge Config allows for selective, path-by-path configuration changes by copying specific settings from one tenant to another. It includes a full diff review process to resolve conflicts before applying changes. This is intended for surgical updates; for full file replacements, use the 'Deploy Config' feature instead.

  3. Overview of Kyra Conversational AI Co-pilot

    Kyra is Fenergo's conversational AI co-pilot designed for compliance officers. Unlike standard chatbots, Kyra orchestrates specialized Document Agents, Policy Agents, and Journey Agents to provide contextual answers to compliance queries (e.g., identifying required documents for specific client types). A core feature of Kyra is explainability, where the system links regulatory requirements to specific client circumstances to explain the reasoning behind its answers.

  4. Overview of Legal Entity Groups in Fenergo SaaS

    Legal Entity Groups allow users to create group constructs to manage legal entities that share common information, such as Investment Managers or Subsidiary Hierarchies. Groups provide a central location for shared information and enable bulk management of data across multiple entities. Groups are treated similarly to legal entities, meaning they can be searched for and have their own Journeys. Data sharing is facilitated through a Parent-Child relationship: a Group can have only one Parent (the primary source of information) but can have multiple Child Legal Entities (which inherit shared information).

  5. Overview of FenX Physical Architecture and Connectivity

    The FenX platform is deployed across three Availability Zones (AZs) within a chosen AWS region to ensure resilience.

    • Entry Points: All integrations (UI, API clients, Postman, Salesforce App) connect via main entry point URLs.
    • DNS: Endpoints like app.fenergox.com map to the private hosted cloud space for authentication and login.
    • Identity Service: Provides secure authentication for API clients and users.
    • Domain Driven Design: The application is split into functional domains (e.g., Risk, Entity Data, Screening) to avoid monolithic structures.
    • Event-Driven Architecture: Domains publish events to a queue for downstream systems to subscribe to, utilizing an immutable time-ordered message store for eventual consistency and high performance under peak loads.

  6. Overview of Kyra Conversational AI Co-pilot

    Kyra is Fenergo's conversational AI co-pilot designed for compliance officers. Unlike standard chatbots, Kyra orchestrates specialized Document Agents, Policy Agents, and Journey Agents to provide contextual answers to compliance queries (e.g., identifying required documents for specific client types). A key feature of Kyra is its ability to provide explainability by linking regulatory requirements to specific client circumstances, ensuring the reasoning behind a requirement is transparent.

  7. Overview of VerifiedImport event subtype

    VerifiedImport is a standardized business service pipeline used to consume entity data and orchestrate updates within Fenergo. Key characteristics include:

    • Stateless Integrations: The calling system does not need to track the entity's state in Fenergo; it can provide a unique identifier to determine if a record should be created or updated.
    • Batch Processing: Supports multiple entities within a single message.
    • Simplified Messages: External systems only need to provide the datakey and value; Fenergo handles data types and validations via internal policy configuration.
    • Automatic Verification: Data is verified as part of the process, and no journey is triggered during the import.

  8. Overview of Fenergo Advanced Reporting

    The Advanced Reporting feature allows users to execute standard SQL queries against specific data domains in the Fenergo SaaS Platform. The system uses an Event Sourced CQRS architecture with real-time projections to maintain a dedicated reporting schema, ensuring that complex queries do not impact application performance.

    Supported Data Domains:

    • Legal Entity Data
    • Journey Data
    • Associations (Related Parties)

    Key Characteristics:

    • Real-time: Data is updated in real time as changes occur on the platform.
    • Isolated Resources: Queries run against a dedicated reporting schema to avoid resource contention with the main application.
    • Timeout: Queries that do not return within 15 minutes are automatically stopped.

  9. Overview of Fenergo Journey Management APIs

    Managing a client entity in the Fenergo SaaS platform is done via Journey Instances, which define the sequence of steps, stages, and tasks required to gather entity data. Five primary APIs are used for this process:

    • Journey Query API: Used to retrieve details of Journey Definitions (schemas) and Journey Instances.
    • Journey Command API: Used to create Journey Instances and edit/update Journey Definitions.
    • Journey Logic Engine API: Used to determine which Journeys are in scope for a specific entity based on configured scoping conditions.
    • Entity Data Command API: Used for managing entity data.
    • Entity Data Query API: Used for querying entity data.

  10. Overview of the Review & Approvals Task

    The Review & Approvals Task provides a collaborative, auditable environment within a journey to review, compare, comment on, and approve entity, product, document, related party, risk, bank account, and investment account information. It replaces offline review processes (like email) to ensure full traceability, consistent decision logic, and centralized communication within Fenergo.

  11. Overview of the Observability API for Transaction Monitoring

    The Observability API provides monitoring and insights for Transaction Monitoring operations. It allows developers to track transaction ingestion status and daily metrics, investigate failed requests via modification ID, monitor bulk transaction file uploads, view rule execution results/alert metrics, and export transaction data reports for compliance and analysis.

  12. Overview of Intelligent Document Processing (IDP) in Documents V2

    Intelligent Document Processing (IDP), also referred to as the Document Agent, is a configurable option for the Documents V2 task. It uses generative AI and Large Language Models (LLMs) to automate the document intake process. When enabled, users can drop multiple files into the generic drop-zone to trigger the following automated workflows:

    • Document Classification: Analyzes content to determine the most appropriate 'Document Type' from user-configured sets.
    • Metadata Extraction: Identifies and stores relevant document metadata based on configured fields.
    • Auto-linking: Automatically links classified documents to document requirements they are deemed 'acceptable' for.
    • Document Splitting: Breaks a single file containing multiple documents into individual files for separate processing.
    • Auto Task-completion: Automatically completes the task if all document requirements are satisfied after processing.
    • Entity Data Extraction: Maps data from eligible documents to data requirements in Policy (requires 'Data Extraction Enabled' in a previous Documents V2 task).
    • Hierarchy Extraction: Extracts related parties to create or enrich entity hierarchies in Fen-X.