Making Data Simple
What was said
both Databricks and Snowflake are actually internally using Kuma for some of their machine learning prediction workflows, especially on the sales side in terms of sales lead scoring or predicting what's the next product that the customer is going to engage with.
“both Databricks and Snowflake are actually internally using Kuma for some of their machine learning prediction workflows, especially on the sales side in terms of sales lead scoring or predicting what's the next product that the customer is going to engage with.”
Jure LeskovecMaking Data Simple
What this signalsWhat leaders say on podcasts often shows their current priorities.
podcast-companytechAdoptionGet every podcast signal for Databricks and the companies you sell to, in the tools you already use.
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This page shows a preview. The full podcast-company record in the Signal API and MCP can also have these 8 fields. Some fields are empty for some signals.
Company
linkedin_urlValue in the APIindustriesValue in the APIemployee_count_lowValue in the APIemployee_count_highValue in the APIrevenueValue in the APIdescriptionValue in the APISignal
signal_nameValue in the APIassociationValue in the APIGET /v1/signals/a320366e-eceb-5476-9bbe-d9e209a9d12a returns this record as JSON. POST /v1/companies/enrich returns every signal for databricks.com.
{
"signal_id": "a320366e-eceb-5476-9bbe-d9e209a9d12a",
"signal_type": "podcast-company",
"signal_subtype": "techAdoption",
"detected_at": "2026-10-25T15:23:44+00:00",
"company": {
"name": "Databricks",
"domain": "databricks.com"
},
"data": {
"is_ad": false,
"quotes": [
"both Databricks and Snowflake are actually internally using Kuma for some of their machine learning prediction workflows, especially on the sales side in terms of sales lead scoring or predicting what's the next product that the customer is going to engage with."
],
"timing": "ongoing_state",
"speaker": "Jure Leskovec",
"evidence": "both Databricks and Snowflake are actually internally using Kuma for some of their machine learning prediction workflows, especially on the sales side in terms of sales lead scoring or predicting what's the next product that the customer is going to engage with.",
"headline": "Databricks · techAdoption · ongoing_state (2024-05)",
"episode_id": "62067499064",
"event_date": "2024-05",
"podcast_name": "Making Data Simple",
"published_at": "2026-10-21",
"episode_title": "Ep. 420 ICYMI - Why Your Structured Data Is Stuck - and How Graph Neural Networks Unlock It, with Jure Leskovec, Stanford Professor and Co-Founder of Kumo",
"date_confidence": "inferred",
"speaker_relation": "own_customer",
"transcript_source": "transcript",
"recorded_at_estimate": "2024-05"
}
}
curl https://signals.autobound.ai/v1/signals/a320366e-eceb-5476-9bbe-d9e209a9d12a \
-H "X-API-KEY: $AUTOBOUND_API_KEY"curl -X POST https://signals.autobound.ai/v1/companies/enrich \
-H "X-API-KEY: $AUTOBOUND_API_KEY" \
-H "Content-Type: application/json" \
-d '{"domain":"databricks.com","limit":20}'Long text fields are shortened on this page.
Looking up one signal by its id is free. Enrich costs 2 credits per signal returned; a call with no results is free.