Platform — pegarecruiter Intelligence Infrastructure

02 / Designed For Everyone

Built for every stakeholder
in the hiring chain.

Pipeline visibility,
quality at a glance.

TA leaders get a real-time command center for every open role — from inbound volume to shortlist quality — with trend data that actually informs headcount strategy.

📊

Pipeline AnalyticsTrack quality scores across roles, sources, and time periods. Spot where quality drops off.

🎯

Source IntelligenceKnow which job boards and sourcing channels produce the highest-confidence candidates.

⚡

Velocity MetricsTime-to-shortlist, decision latency, and stage conversion — automatically tracked.

94%

Pipeline Quality

2.4d

Avg to Shortlist

10k

Evaluated.

87%

Accept Rate

Avery Chen

92% match

Marcus Reid

88% match

Sofia Liu

74% match

Ranked shortlists
with reasoning — not just scores.

Stop reviewing bulk applications manually. pegarecruiter surfaces the top candidates with structured explanations you can use in a debrief, not just numbers you have to guess at.

🔍

Evidence-Based RankingEach candidate comes with a ranked list of supporting signals — tenure, skill match, culture fit.

🚩

Flag & FilterIntelligent risk flags highlight salary mismatches, job-hopping patterns, or skill gaps proactively.

📋

One-Click Debrief NotesExport structured candidate summaries directly into your ATS notes or Slack.

Avery Chen · 92% Confidence

Skill Match

9/10 required skills matched including Rust, distributed systems

Tenure

4.2yr avg tenure, 2 promotions at last company

Growth Arc

Consistent upward trajectory in scope and compensation

Salary Fit

⚠ Expects $15k above band — flagged for review

Confidence the candidate
cleared a real bar.

Hiring managers get a clear signal about every candidate before they walk in the room — with enough context to have a better conversation, not just a resume summary.

✅

Pre-Interview BriefingA structured one-pager per candidate: top strengths, known gaps, and suggested interview focus areas.

🎯

Role-Specific CalibrationScores are calibrated against your specific role requirements — not generic matching.

📈

Outcome Feedback LoopYour hire/no-hire decisions improve the model. The more you use it, the sharper it gets.

Marcus Reid

Staff Backend Engineer · 88% confidence

Top Strengths

→ Deep systems programming (C++, Rust)
→ Led 3 infrastructure migrations at scale
→ Open source contributor (4.2k GitHub stars)

Suggested Interview Focus

→ Team leadership (limited evidence in history)
→ Cross-functional stakeholder management

Strong hire signal Probe leadership

Every decision is
defensible by design.

pegarecruiter was built with compliance teams in mind. Every output is audit-ready, every model is bias-monitored, and every evaluation is logged with a complete chain of evidence.

🔒

Full Audit TrailEvery evaluation, decision, and model version is logged. Exportable for internal review.

⚖️

Disparate Impact Monitoringconfigurable fairness monitoring across selected protected attributes.

🛡️

Data Residency & DPAChoose US, EU, or APAC data residency. Custom DPAs available for enterprise agreements.

🛡️

SOC 2 Type II

Annual audit · Ernst & Young

Active

🇪🇺

GDPR Compliance

EU data processing agreement

Active

🌐

CCPA

California consumer privacy

Active

⚖️

EEOC Audit Export

One-click report generation

Review

📊

Disparate Impact

Real-time monitoring enabled

0 alerts

API-first. Everything
is an endpoint.

Every capability in pegarecruiter is available via REST API. Build custom integrations, embed intelligence into your own tooling, or pipe data into your data warehouse directly.

⚡

Sub-100ms LatencyReal-time evaluation API designed for high-throughput production environments.

🔗

Webhook EventsPush-based event system for stage changes, score updates, and compliance alerts.

📚

Full SDK SupportNode.js, Python, and Go SDKs with complete TypeScript types. OpenAPI spec included.

// Evaluate a candidate in real-time const response = await fetch( 'https://api.pegarecruiter.com/v1/evaluate', { method: 'POST', headers: { 'Authorization': `Bearer ${API_KEY}`, 'Content-Type': 'application/json' }, body: JSON.stringify({ role_id: 'role_abc123', candidate: { resume_url, linkedin_url } }) } ); // → { score: 0.87, signals: [...], explanation: {...} }

A defensible moat in
a $200B market.

pegarecruiter is building the intelligence infrastructure layer for hiring — the category that every enterprise talent organization will need as AI hiring tools face increasing regulatory scrutiny.

📈

$200B TAMGlobal talent acquisition software market, growing at 8.4% CAGR through 2030.

🔒

Regulatory Tailwindconfigurable fairness monitoring across selected protected attributes.

🔁

Data Network EffectEvery evaluation improves the model. Outcome data from 10k evals is a durable competitive moat.

💰

Expansion Revenuestrongly increasing by volume growth and seat expansion as customers hire more. Usage-based upside is uncapped.

strong%

Net Revenue Retention

Associatedwith

Enterprise Customers

strongx

YoY Growth

strong

Avg. Payback Period

Investor materials available — NDAs and data room access for qualified investors. Contact office@pegarecruiter.com

Architecture built for
production scale.

pegarecruiter's infrastructure handles 50,000+ evaluations per day with sub-100ms latency, horizontal scaling, and zero-downtime deployments. Every layer is independently auditable.

↓ Inbound

Source

ATS Connectors

Greenhouse, Lever, Workday, SAP SF, iCIMS, and 36 more

Source

REST API

Direct ingestion for custom stacks. Sub-50ms ack.

Source

Webhooks

Real-time push on candidate stage changes

Source

File Upload

Bulk CSV, PDF resumes, assessment exports

Core · Proprietary
Signal Intelligence Engine
NLP parsing, skill graph traversal, tenure modeling, behavioral signal extraction, salary market calibration. weighted signal types.

Safety

Bias Monitor

Continuous disparate impact analysis. Alerts at 4/5ths rule thresholds.

Memory

Outcome Store

Feedback from hire/no-hire decisions. Improves model precision over time.

Output

Confidence Score

Calibrated 0–100 score with uncertainty bounds. Not a percentile rank.

Output

Explanation Layer

Structured JSON explanation. Human-readable summary. SHAP values for technical audit.

Output

Audit Log

Immutable event log. Model version, timestamp, input hash, output. Export to S3 or GCS.

Delivery

ATS Write-back

Scores, notes, and rankings written back to your ATS automatically

Delivery

Dashboard

Role-based views for TA, recruiters, managers, and compliance

Delivery

Slack / Email

Real-time candidate alerts and pipeline digests

Delivery

Data Warehouse

Snowflake, BigQuery, Redshift connectors for analytics

↓ Outbound

Works with your
entire stack.

Native connectors for 40+ ATSs, HRISs, and productivity tools. Data flows both ways — pegarecruiter reads in and writes back, keeping your system of record clean.

Applicant Tracking

ATS Platforms

Greenhouse

Native

Lever

Native

Workday

Native

SAP SuccessFactors

Native

iCIMS

Native

HRIS & Payroll

People Systems

Rippling

Native

Bamboo HR

Native

ADP

Beta

Gusto

Beta

Namely

Native

Communication

Productivity

Slack

Native

Microsoft Teams

Native

Gmail / Google

Native

Outlook 365

Native

Calendly

Beta

Data & Analytics

Warehouses

Snowflake

Native

BigQuery

Native

Redshift

Native

S3 / GCS

Native

REST / Webhook

Always

REST API & Webhooks

Full programmatic access to every pegarecruiter capability. OpenAPI spec, SDKs for Node.js, Python, and Go, and a Postman collection — all in the docs.

POST/v1/evaluateEvaluate a candidate

GET/v1/pipeline/{role_id}Full pipeline view

POST/v1/rolesCreate a role context

GET/v1/audit/{eval_id}Fetch audit trail

POST/v1/feedbackSubmit outcome signal

// Webhook event payload { "event": "candidate.evaluated", "timestamp": "2026-02-15T09:41:22Z", "data": { "candidate_id": "cnd_xyz789", "role_id": "role_abc123", "score": 0.87, "confidence": "high", "flags": ["salary_gap"], "explanation_url": "..." } }

Enterprise-grade security
by default.

Security, privacy, and compliance aren't features — they're the foundation. Every customer gets SOC 2 Type II controls, GDPR compliance, and full data residency options out of the box.

🔐

Data Encryption

AES-256 at rest, TLS 1.3 in transit. Encryption keys are customer-managed in AWS KMS or GCP KMS. Zero pegarecruiter access to plaintext candidate data.

AES-256TLS 1.3KMS

🛡️

SOC 2 Type II

Annual SOC 2 Type II audit covering security, availability, and confidentiality. Report available under NDA to qualified enterprise prospects.

SOC 2 TypeIIAnnual audit

🌍

Data Residency

Choose where your data lives: US (us-east-1), EU (eu-west-1), or APAC (ap-southeast-1). Data never leaves your chosen region. Custom DPA for EU customers.

USEUAPACCustom DPA

⚖️

GDPR & CCPA

Full compliance with GDPR Article 22 (automated decision-making rights), CCPA data subject requests, and EEOC record-keeping requirements. One-click deletion.

GDPRCCPAEEOC

👤

RBAC & SSO

Role-based access control with fine-grained permissions. SAML 2.0 and OIDC SSO via Okta, Azure AD, and Google Workspace. MFA enforced by default.

SAML 2.0OIDCMFA

📋

Immutable Audit Logs

Every evaluation, model version, user action, and API call is logged in an immutable audit trail. Export to your SIEM, S3, or review in-platform.

ImmutableSIEM ready

Five core capabilities.
One unified platform.

Each capability is independently powerful — together they form a complete intelligence infrastructure for modern hiring.

01 · Signal Engine

340+ Weighted Signal Types

The engine parses every input through a multi-stage NLP pipeline, traverses a proprietary skill graph to identify adjacent competencies, and applies tenure models calibrated to your industry and stage.

Skill adjacency graph with 2.4M node taxonomy

Career velocity and growth trajectory modeling

Salary market calibration via real-time data

Behavioral signal extraction from unstructured text

02 · Latency

Sub-100ms,
at any volume.

Real-time evaluation API built on horizontally scalable microservices. No batch jobs. No overnight queues. Decisions happen as fast as candidates arrive.

Avg: 94ms · P99: 180ms

03 · Explainability

Every score has
a reason.

Structured explanations in JSON, human-readable summaries, and SHAP values for technical audit. Built to satisfy NYC Local Law 144 and the EU AI Act's automated decision-making requirements.

JSON explanation with per-signal weights

Human-readable summary for managers

SHAP values for legal/technical audit

04 · Fairness

Bias Detection
& Monitoring

Continuous disparate impact monitoring across gender, race, age, and disability status. Automated alerts when selection rates cross 4/5ths rule thresholds — before legal exposure, not after.

Real-time monitoring across 7 protected attributes

Automated 4/5ths rule threshold alerts

Quarterly fairness audit reports

05 · Feedback Loops

The model gets better the more you use it.

Outcome signals — hire/no-hire decisions, 90-day performance ratings, voluntary attrition — feed back into the model automatically. Over time, pegarecruiter calibrates to your specific hiring context: your role requirements, your culture, your definition of a great hire. No data science team needed.

Signal In

Hire/no-hire decisions, 90-day reviews, attrition events, manager ratings

→

Model Update

Weekly fine-tuning cycle. Signal weights adjust to your hiring context.

→

Better Predictions

Confidence calibration improves. False positive rate drops. Quality goes up.

The intelligence
layer hiring
has been missing.

Built for every stakeholder
in the hiring chain.

Pipeline visibility,
quality at a glance.

Ranked shortlists
with reasoning — not just scores.

Confidence the candidate
cleared a real bar.

Every decision is
defensible by design.

API-first. Everything
is an endpoint.

A defensible moat in
a $200B market.

Architecture built for
production scale.

Works with your
entire stack.

REST API & Webhooks

Enterprise-grade security
by default.

Five core capabilities.
One unified platform.

The infrastructure
your hiring deserves.

The intelligencelayer hiringhas been missing.

Built for every stakeholderin the hiring chain.

Pipeline visibility,quality at a glance.

Ranked shortlistswith reasoning — not just scores.

Confidence the candidatecleared a real bar.

Every decision isdefensible by design.

API-first. Everythingis an endpoint.

A defensible moat ina $200B market.

Architecture built forproduction scale.

Works with yourentire stack.

REST API & Webhooks

Enterprise-grade securityby default.

Five core capabilities.One unified platform.

The infrastructureyour hiring deserves.

The intelligence
layer hiring
has been missing.

Built for every stakeholder
in the hiring chain.

Pipeline visibility,
quality at a glance.

Ranked shortlists
with reasoning — not just scores.

Confidence the candidate
cleared a real bar.

Every decision is
defensible by design.

API-first. Everything
is an endpoint.

A defensible moat in
a $200B market.

Architecture built for
production scale.

Works with your
entire stack.

Enterprise-grade security
by default.

Five core capabilities.
One unified platform.

The infrastructure
your hiring deserves.