Mercury ATS Integration
Bring Skima Intelligence to Mercury
Skima AI brings explainable AI-scores and insights, and collaborative feedback directly into Mercury ATS. No extra logins, no workflow disruption.
What You'll See in Mercury ATS with Skima AI
By integrating Skima AI with Mercury ATS, your team gets AI-powered recruiting insights embedded into Mercury modules.
AI Match Scores (0-100) are displayed on each candidate profile.
AI-generated bullet points summarizing reasons for candidate-job fit.
"Skima Screened" tag enabling quick filtering and pipeline organization.
Shortlist page for manager/skip plus optional comments.
Activity notes capturing hiring manager feedback for audit and compliance.
A clear top 10 shortlist that updates automatically as new candidates arrive. This ensures your team always works on the best candidates first.
Why Mercury Recruiting Teams Pick Skima AI
Mercury ATS users integrate Skima AI as it boosts their ATS with intelligent scoring, matching, and automation, without forcing them to switch systems.
Stay Within Mercury
All scores, rationale, and feedback appear directly in Mercury's interface.
Simplified Collaboration
Managers provide quick decisions via Skima AI's secure activity notes.
Always Fresh Data
Scores update instantly using Mercury's webhooks and API events.
Candidate Rediscovery
Skima AI resurfaces qualified candidates from Mercury to reduce time-to-fill and boost ROI.
What Skima AI Writes Back to Mercury ATS
| Writes back to | Type | Example |
|---|---|---|
| AI Match Score | Number (0–100) | 92 |
| AI Reasons | Multi-line text | "5 yrs healthcare exp; CRM" |
| Skima Screened Tag | Boolean/Tag | True |
| Shortlist Link | URL | https://skima.ai/shortlist/1 |
| HM Feedback | Enum | Approve/Reject/Maybe |
| HM Comment | Text | "Strong communication skills" |
| Stage Change (Optional) | Status | "Skima Shortlisted" |
| Evidence File Attachment | File | SKIMA_Evidence.pdf |
Note: Skima AI writes structured data back to Mercury ATS, leveraging its native DataVerse objects and Dynamics 365 extensibility model.
How Does the Shortlist Loop Work?
Skima AI creates a seamless hiring collaboration loop inside Mercury ATS, eliminating friction and extra tools.
Recruiter Shares Shortlist
A secure, no-login URL is logged as an activity note on the candidate or vacancy.
Manager Provides Feedback
Managers click Approve, Reject, or Maybe and can add optional comments.
Skima AI Updates Mercury
Feedback is pushed back as activity notes and status updates on candidate records.
Recruiter Acts on AI Insights
Recruiters see a live, AI-ranked shortlist for confident candidate progression.
The result is transparent collaboration, faster decisions, and a full audit trail within Mercury's workflow.
Field Map for Mercury ATS Integration
A clear mapping ensures IT and recruiting teams understand every data exchange between Mercury and Skima AI.
Skima AI securely consumes the following Mercury data via API and webhooks to enable candidate scoring and rediscovery:
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Vacancy Data: job ID, title, description, department, location, hiring manager.
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Candidate Data: name, email, phone, LinkedIn profile URLs, resume attachments.
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Application Data: application status, dates, prior interview feedback.
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Historical Interaction: previous job opportunities, source tracking, candidate tags.
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Custom Fields & Skills: structured metadata for enhanced AI matching.
After scoring and ranking, Skima AI writes structured results back to Mercury:
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Custom Fields & Notes: AI Match Score and detailed reasons stored for each candidate.
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Candidate Tagging: "Skima Screened" label for quick filtering across recruitment workflows.
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Activity Notes: Shortlist links and hiring manager feedback recorded on candidate records.
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Pipeline Status Updates: Optional stage transitions via Power Automate flows.
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Attachments: Detailed evaluation evidence stored in SharePoint or OneDrive.
This bidirectional sync ensures hiring managers always see transparent AI insights and real-time collaboration data inside Mercury's opportunity-centric workflow.
Set up Your Mercury Integration
Mercury + Skima AI integration requires administrative setup and minimal IT effort,.
Here are 5 steps to set up your Mercury ATS integration:
Generate and configure API credentials in Mercury's Azure AD tenant for OAuth2 client credentials authorization.
Register webhook endpoints in Mercury to receive real-time candidate and vacancy updates.
Set up custom DataVerse fields, tags, and activity note templates to store AI match scores and feedback.
Validate integration on pilot vacancies: upload resumes, confirm AI scores and reasons, submit manager feedback, and verify logging.
Enable integration organization-wide and monitor with built-in ROI dashboards and automatic check-ins on candidate pipeline health.
Security &
Responsible AI
for Mercury
Integrations
Trust and compliance are key when integrating Skima AI with Mercury ATS. Our approach ensures candidate data stays secure, decisions remain transparent, and hiring managers stay in control while working within Mercury's security framework.
- Encryption of all data in transit and at rest using TLS 1.2+ and Microsoft's secure data centers.
- OAuth2-based authentication using Azure Active Directory, eliminating password storage.
- Role-based access controls and data redaction modes to protect candidate privacy.
- Transparent AI decision-making with explainable match scores to avoid bias or unfairness.
- Audit trails are maintained in Mercury's native logs for compliance with GDPR, SOC 2, and other frameworks.
- No automated rejection; all hiring decisions remain fully controlled by human users.
Skima AI combines explainable AI with strict security practices, ensuring your Mercury ATS integrations remain compliant, auditable, and fair while avoiding bias and discrimination risks.
Customer Snapshot: 30-Day Pilot with Mercury ATS
58%
Time-to-screen
2X
Interviews from top-10
+24 NPS
HM Satisfaction
Frequently Asked Questions
Everything you need to know about the Mercury ATS Integrations.
Does Skima AI support Mercury ATS integration? How?
Yes, Skima AI connects via Mercury's OAuth2-secured REST APIs and webhook events, enabling real-time AI scoring, feedback writing, and seamless embedding of insights directly within the Mercury ATS interface.
What fields does Skima AI write back to Mercury?
Skima AI writes match scores, AI rationale notes, screening tags, manager feedback, optional pipeline stage updates, and evidence attachments into native DataVerse fields, maintaining data integrity and traceability.
How long does Mercury integration setup take?
Integration setup typically requires 90–120 minutes, covering API credentialing, webhook configuration, custom field setup, and pilot validations to ensure accurate candidate scoring and feedback workflows within Mercury.
Are webhooks required?
Webhooks are recommended for instant score updates and real-time AI insights. If unavailable, Skima AI safely falls back to 10–15 minute polling to maintain near real-time synchronization.
Where do Match Scores and Reasons appear?
Scores and AI reasoning appear as custom fields and activity notes on candidate and application records within Mercury, fully integrated into the platform for transparency and traceable insights.
Can manager feedback stay inside Mercury?
Yes, hiring manager approvals, rejections, and comments are captured as activity notes, preserving a complete audit trail and maintaining full visibility of decisions within Mercury ATS.
What security measures protect candidate data?
Data security includes OAuth2 authentication via Azure AD, role-based access, encrypted storage, audit logging, and adherence to GDPR and SOC 2 standards, ensuring safe and compliant handling of candidate data.
Does Skima AI automatically move candidate stages?
Stage changes are optional and configurable using Power Automate flows, allowing teams to automate pipeline progression or retain manual recruiter control based on preferred workflow practices.
How often are match scores refreshed?
Scores refresh instantly via webhook triggers on candidate or job changes and periodically every 10–15 minutes using polling if webhooks are unavailable, ensuring continuous AI-driven insights.
Can Skima AI help rediscover past candidates in Mercury?
Yes, Skima AI leverages historical candidate records, prior applications, and tags to surface qualified past candidates, enabling efficient talent rediscovery and improved hiring ROI within Mercury's data model.