Data Makers Fest 2026
Diogo Sá (AI Data Scientist, Airbus) at Data Makers Fest 2026.
Source
Extracted by Autobound
From the Signal API record- Signal
- Conference talks
- Conference
- Data Makers Fest 2026
- Date
- May 5, 2026
- Location
- Porto, Portugal
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The full record
From the Signal API recordPeople
- Diogo SáAI Data Scientist, Airbus · Speaker
Details
- Conference ends
- May 6, 2026
Extraction
- Confidence
- High
- Relevance
- 65%
- Detected
- May 31, 2026
- signal_type
conference-speaker- signal_subtype
conferenceSpeaker
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The API returns more than this page shows
This page shows a preview. The full conference-speaker record in the Signal API and MCP can also have these 19 fields. Some fields are empty for some signals.
Contact
full_nameValue in the APIjob_titleValue in the APIlinkedin_urlValue in the APIemailValue in the APIfirst_nameValue in the APIlast_nameValue in the APIcityValue in the APIstateValue in the APIcountryValue in the APIseniorityValue in the API
Company
linkedin_urlValue in the APIindustriesValue in the APIemployee_count_lowValue in the APIemployee_count_highValue in the APIrevenueValue in the APIdescriptionValue in the API
Signal
signal_nameValue in the APIassociationValue in the API
And 1 more fields.
Show the full JSONHide the full JSONThe record on this page and the API request
GET /v1/signals/7f32f677-6113-5aa8-84d4-034b914c4e45 returns this record as JSON. POST /v1/companies/enrich returns every signal for airbus.com.
{
"signal_id": "7f32f677-6113-5aa8-84d4-034b914c4e45",
"signal_type": "conference-speaker",
"signal_subtype": "conferenceSpeaker",
"detected_at": "2026-05-31T00:00:00+00:00",
"company": {
"name": "Airbus",
"domain": "airbus.com"
},
"data": {
"summary": "Diogo Sá (AI Data Scientist, Airbus) at Data Makers Fest 2026.",
"relevance": 0.65,
"confidence": "high",
"speaker_bio": "Diogo Sá is an AI/ML Engineer with over four years of experience in production-grade AI. At Airbus, he develops GenAI multi-agent applications, focusing critically on robust evaluation, LLM safety, and defining LLMOps standards for responsible, scalable deployment.Previously, he standardized ML development at Continental and led a data-centric transformation at Vestas that prevented over €20 million in repair costs.His expertise spans GenAI (LLMs, RAG, Agents), Deep Learning, and MLOps automatio",
"conference_url": "https://www.datamakersfest.com",
"conference_date": "2026-05-05",
"conference_name": "Data Makers Fest 2026",
"contact_resolved": false,
"conference_topics": [
{
"key": "topic",
"value": "data"
},
{
"key": "language",
"value": "english"
},
{
"key": "language",
"value": "portuguese"
}
],
"domain_match_score": 10,
"conference_end_date": "2026-05-06",
"conference_location": "Porto, Portugal",
"domain_match_confidence": "high"
}
}
curl https://signals.autobound.ai/v1/signals/7f32f677-6113-5aa8-84d4-034b914c4e45 \
-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":"airbus.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.