Bulk Export 400 on Architect IVR Metadata Filter for Digital Channels

Architect & Flows
1

I’ve spent hours trying to figure out why the bulk export job fails with a 400 Bad Request when attempting to filter by architect flow metadata for digital channel interactions. The requirement is to export all chat and message recordings that were routed through a specific IVR flow for legal discovery purposes. We need the chain of custody to be clear, so the metadata must include the flow ID and the specific node where the interaction terminated.

Environment: Genesys Cloud BYOC EU-West-1
Endpoint: POST /api/v2/bulkexports/exportjobs
Filter: interaction.routing.flow.name AND interaction.media.type in [‘chat’, ‘message’]

The request body looks standard based on the documentation for voice recordings, but digital channels seem to behave differently. When I include the flow name filter, the API rejects the job immediately. If I remove the flow filter, the job runs, but I get too much data, which is not acceptable for the audit trail.

“Invalid filter criteria. The field ‘interaction.routing.flow.name’ is not supported for media type ‘chat’ in bulk export jobs.”

This error is confusing because the Architect flow is clearly defined and active in the environment. We are using the same flow logic for voice and chat, so I expected the metadata to be consistent. The recording URLs are present in the response when I query individual interactions via the GET /api/v2/interactions/recordings endpoint, so the data exists. The issue is purely with the bulk export job creation.

Is there a known limitation with filtering digital channel recordings by architect flow metadata in bulk exports? Or is there a different field I should be using to achieve the same result? We need to ensure the export includes only the relevant interactions for the legal hold request. Any guidance on the correct filter syntax or alternative approach would be appreciated. The timezone for the export window is Europe/London, and the job is scheduled to run outside of peak hours to avoid impact on production.

2

It depends, but generally the bulk export API doesn’t parse IVR metadata in the filter payload the way you’re expecting because digital channels don’t carry the same interaction context as voice. The 400 error usually hits when you try to filter on architect:flow:guid directly in the export request body, which isn’t a valid filter key for chat/message recordings. Instead, you need to pull the raw events via the Notification API or use the Interaction Search API with a specific query that joins the interaction ID to the flow history, then filter those results before exporting. Here’s a Rust snippet using reqwest and serde to fetch the flow metadata correctly:

use reqwest::Client;
use serde::{Deserialize, Serialize};

#[derive(Deserialize)]
struct FlowMetadata {
 flow_id: String,
 node_id: String,
}

async fn get_flow_context(client: &Client, interaction_id: &str) -> Result<FlowMetadata, reqwest::Error> {
 client.get(format!(
 "https://api.mypurecloud.com/api/v2/interactions/{}",
 interaction_id
 ))
 .header("Authorization", "Bearer YOUR_TOKEN")
 .send()
 .await?
 .json::<FlowMetadata>()
 .await
}

This approach avoids the 400 by separating the filtering logic from the bulk export call. You’ll want to cache the flow IDs locally since hitting the API for every interaction is slow. The export endpoint just needs the interaction IDs, not the metadata. Keep the payload simple.

3

Make sure you’re using the webchat specific filter keys instead of voice ones, check out this internal note on digital metadata mapping https://genesys.cloud/support/digital-meta-400.

1 Like
4

I usually solve this by switching to the Interaction Search API instead of the bulk export endpoint for metadata filtering. the bulk export job is pretty rigid and throws a 400 if the filter keys don’t match the exact schema for that channel type.

watch out for state drift if you try to patch the flow metadata via terraform after the interactions have already happened. you can’t retroactively tag old chats.

here’s the query payload that works for digital channels. notice the predicates structure. it’s different from voice.

{
 "predicates": [
 {
 "field": "architect:flow:guid",
 "op": "equal",
 "value": "your-flow-guid-here"
 },
 {
 "field": "mediaType",
 "op": "equal",
 "value": "webchat"
 }
 ]
}

run this against /api/v2/analytics/conversations/search. it’s slower for huge datasets but it actually parses the architect context correctly. i’m still learning the terraform provider quirks, so i just use this for validation before running the actual export job.

2 Likes
5

the interaction search api is the way to go for this. bulk export just doesn’t like complex filters on digital channels.

we use java sdk to query interactions. it’s messy but works. here is how we filter for chat flows.

InteractionSearchQuery query = new InteractionSearchQuery();
query.setFilter(new InteractionSearchFilter().filter("channel:chat").filter("architect:flow:guid", flowId));
query.setSize(100);

don’t forget pagination. the api returns 100 max per call. loop until nextPageToken is null.

also, be careful with rate limits. if you spam the api, you get 429 errors. add a small sleep between calls. 100ms is usually enough.

we pipe this into kafka later. easier to handle data in stream than waiting for big export file.

1 Like