> ## Documentation Index
> Fetch the complete documentation index at: https://docs.meetorbis.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Contact Research
> Orbis automatically fills in missing contact details using AI and third-party data sources.
Contact enrichment fills in information you didn't supply manually — things like a person's current job title, company, social profiles, profile photo, and professional background. Orbis enriches contacts automatically after import and on demand.
## What enrichment fills in
When enrichment runs on a contact, Orbis attempts to populate the following fields:
Job title, headline, professional summary, industry, job role, seniority level, and inferred years of experience
Current employer, company domain, and company website — and triggers company enrichment to fetch a logo if not already present
LinkedIn URL, Twitter/X, GitHub, and other public social profiles
A profile photo sourced from public data
City, region, country, and metro area
LinkedIn headline, about section, and follower count when a LinkedIn profile is matched
Enrichment only writes to fields that are currently empty. It won't overwrite data you've already entered or data from a previous enrichment run.
## How enrichment is triggered
### On import
Enrichment starts automatically after a CSV import completes. Newly added contacts are queued for enrichment in the background. You don't need to do anything — the fields appear on the contact profile as the data is fetched.
### On demand
You can manually trigger enrichment on any individual contact from their profile page. Look for the **Enrich** option in the contact's action menu. This is useful if you've added a contact manually or if you want to refresh enrichment data for a specific person.
## Data sources
Orbis uses the following data sources during enrichment:
| Source | What it provides |
| ------------------------ | -------------------------------------------------------------------------------------------------------------------- |
| **PeopleDataLabs (PDL)** | Professional background: job title, company, location, skills, social profiles, inferred salary, years of experience |
| **Google Search** | LinkedIn profile discovery when PDL doesn't return a direct match |
| **Brandfetch** | Company logos and brand colors for associated companies |
Enrichment runs automatically within your plan's included quota. If enrichment stops completing on new contacts, you may have reached your plan's enrichment limit — contact support to learn more.
## Enrichment confidence levels
Not every contact enrichment produces the same quality result. Orbis tracks a **match confidence** level for LinkedIn enrichment:
| Level | Meaning |
| ---------- | -------------------------------------------------------------------------------------- |
| **High** | The LinkedIn profile was matched directly to the contact's email or unique identifiers |
| **Medium** | The profile was matched by name and company, which may have false positives |
| **Low** | A possible match was found but the signals were weak |
| **None** | No match was found |
The confidence level is visible in the contact's profile and can be filtered in the contacts list via the **Match Confidence** column. This helps you identify contacts where the enriched LinkedIn data should be reviewed before you act on it.
Filter the contacts list by **Match Confidence = low** or **none** to find contacts that would benefit from manual profile review or a manual enrichment trigger.
## Founder detection
As part of enrichment, Orbis checks whether a contact is likely a founder based on their LinkedIn profile and job title signals. A **Founder** badge appears on the contact profile when this is detected, along with the confidence level of that detection.