AI-powered digital identity resolution across social platforms
Available at: https://entity-resolution-demo.parallel.ai
This API finds all social media profiles belonging to a single person. Give it a name, email, username, or any profile URL—it returns verified matches across Twitter, LinkedIn, GitHub, Instagram, Facebook, TikTok, and more.
The problem: People fragment their presence across dozens of platforms. Traditional search can't reliably connect these scattered identities.
The solution: AI-powered entity resolution that finds and verifies profiles through cross-referencing and confidence scoring.
- Richer prospect intelligence: Find prospects' GitHub repos, technical blogs, conference talks beyond LinkedIn
- Better qualification: A CTO active on GitHub is different from one who isn't
- Warmer introductions: Discover mutual connections across any platform
- Complete candidate profiles: Evaluate technical skills (GitHub), communication (Twitter), thought leadership (blogs)
- Passive sourcing: Find engineers active on GitHub but not updating LinkedIn
- Cultural fit: See how candidates present themselves across contexts
- Relationship intelligence: Identify vocal advocates and at-risk customers
- Multi-channel engagement: Meet champions where they are
- Expansion signals: Track when decision-makers change roles
- CRM deduplication: Merge duplicate records by linking profiles to single entities
- Enrichment at scale: Turn sparse contact data into rich profiles
- Attribution accuracy: Know which database profiles are the same person
- Submit a person identifier (name, email, username, or profile URL)
- AI searches across major platforms and verifies matches
- Returns structured profile data with confidence indicators
Built using Parallel's Task API and OAuth Provider.
// Submit resolution request
const response = await fetch("https://your-api.com/resolve", {
method: "POST",
headers: {
"Content-Type": "application/json",
"x-api-key": "your-api-key",
},
body: JSON.stringify({
input: "john.doe@techcorp.com or @johndoe on Twitter",
}),
});
const { trun_id } = await response.json();
// Poll for results
const result = await fetch(`https://your-api.com/resolve/${trun_id}`, {
headers: { "x-api-key": "your-api-key" },
});
const { profiles } = await result.json();{
"profiles": [
{
"platform_slug": "twitter",
"profile_url": "https://twitter.com/johndoe",
"is_self_proclaimed": true,
"is_self_referring": true,
"match_reasoning": "Profile bio links to LinkedIn and GitHub profiles found in search",
"profile_snippet": "CTO @TechCorp | Building AI infrastructure | Thoughts on ML systems"
},
{
"platform_slug": "github",
"profile_url": "https://github.com/johndoe",
"is_self_proclaimed": true,
"is_self_referring": false,
"match_reasoning": "Linked from Twitter profile, same name and company affiliation",
"profile_snippet": "CTO at TechCorp. 50 repositories, 2.3k followers"
}
]
}is_self_proclaimed: Profile was discovered through the person's own references. Either directly mentioned in input, linked from a mentioned profile, or linked transitively. High confidence indicator.
is_self_referring: Profile links back to other profiles in the result set. Bidirectional verification increases confidence.
match_reasoning: Human-readable explanation of why the AI matched this profile. Use for quality assurance and debugging.
- Sales teams: 10x more context per lead in CRM
- Recruiting firms: 30 minutes → 30 seconds per candidate
- Customer success: Early warning system via social sentiment
- Investment firms: Due diligence on startup founders
- Marketing: Identify real industry influencers
The API only returns high-confidence matches. No false positives means you can trust the results for critical decisions like sales outreach, hiring, and compliance.