Data Ingestion Agent

Agent ID: data-ingestion-agent

Agent Overview
Collects raw data from various specified sources.

Task Description:

Ingest raw data from customer uploads, APIs, or databases. Does not perform deep validation or formatting.

Reusability:

Reusable Component

Agent Type:

Simple AI (Prompt-driven)

Implementation Notes:

Uses connectors for APIs/databases and file handlers. May use AI for initial categorization of unstructured inputs.

Supporting Teams
Teams responsible for the continuous improvement and monitoring of this agent's efficacy.
AI Core Services
Data Governance Council
Performance & Evaluation Metrics
Key indicators of this agent's operational effectiveness and continuous improvement strategy.

Last Evaluated

2024-07-15

Accuracy

99.0%

Latency

avg 150ms (structured), avg 500ms (unstructured basic)

Cost Per Interaction

$0.0002 (structured), $0.001 (unstructured)

Continuous Improvement (RLFT)

This agent is designed for continuous improvement through mechanisms like Reinforcement Learning Fine-Tuning (RLFT), where performance is monitored and models are iteratively updated based on outcomes and feedback.

RLFT Strategy

Monitoring ingestion failures, optimizing connectors.

Last RLFT Cycle

2024-07-01

Next RLFT Review

2024-10-01

General Evaluation Notes

Focus on connection reliability and throughput.

Interaction & Capabilities (A2A)
Information relevant for Agent-to-Agent communication and skill definition.

Identity (Core A2A):

  • Name: Data Ingestion Agent
  • Unique ID: data-ingestion-agent

Primary Function (A2A):

Ingest raw data from customer uploads, APIs, or databases. Does not perform deep validation or formatting.

Defined Agent Skills (A2A Interface):

Skill Orchestration & Execution

The operational logic for this agent, including the invocation and management of its defined skills, is handled by the backend system's orchestration layer. This layer is responsible for the agent's execution sequence, data handling according to its skill schemas, and any necessary interactions with tools or external services. The specific method (e.g., AI model call, deterministic code execution) is detailed in the 'Implementation Notes' within the Agent Overview.

Agent Card JSON (Definition)
The raw JSON representation of this agent's definition, including its skills and evaluation metrics.
{
  "id": "data-ingestion-agent",
  "name": "Data Ingestion Agent",
  "description": "Collects raw data from various specified sources.",
  "isReusable": true,
  "taskDescription": "Ingest raw data from customer uploads, APIs, or databases. Does not perform deep validation or formatting.",
  "icon": {
    "displayName": "FileSearch"
  },
  "agentType": "ai-simple",
  "implementationNotes": "Uses connectors for APIs/databases and file handlers. May use AI for initial categorization of unstructured inputs.",
  "responsibleTeamIds": [
    "team-ai-core",
    "team-data-governance"
  ],
  "skills": [
    {
      "id": "ingest-raw-data",
      "name": "Ingest Raw Data",
      "description": "Collects raw data from specified sources.",
      "inputSchemaExample": "{\n  \"type\": \"object\",\n  \"properties\": {\n    \"sourceList\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"object\",\n        \"properties\": {\n          \"sourceType\": {\n            \"type\": \"string\"\n          },\n          \"sourceDetails\": {\n            \"type\": \"string\"\n          }\n        }\n      }\n    }\n  }\n}",
      "outputSchemaExample": "{\n  \"type\": \"object\",\n  \"properties\": {\n    \"ingestionId\": {\n      \"type\": \"string\"\n    },\n    \"rawDataReferences\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"object\"\n      }\n    }\n  }\n}"
    }
  ],
  "evaluation": {
    "lastEvaluated": "2024-07-15",
    "accuracy": 0.99,
    "latency": "avg 150ms (structured), avg 500ms (unstructured basic)",
    "costPerInteraction": "$0.0002 (structured), $0.001 (unstructured)",
    "notes": "Focus on connection reliability and throughput.",
    "rlftStrategy": "Monitoring ingestion failures, optimizing connectors.",
    "lastRlftCycle": "2024-07-01",
    "nextRlftReview": "2024-10-01"
  },
  "inputs": [
    "gds-customer-docs",
    "gds-crm-data",
    "gds-business-registry-api",
    "gds-news-feed-api",
    "gds-financial-statements-db"
  ],
  "outputs": [
    "gds-raw-document-data",
    "gds-raw-structured-data"
  ]
}