AI screens 250 applicants
before you finish your coffee.

Q: How does the competency model get built for each role and can it be customised?

The model is built from three sources and typically holds 20–40 weighted attributes: the parsed job description, hiring manager input, and historical success data from similar roles in your ATS. It is fully editable by the TA team — attribute weights, must-have flags, disqualifying criteria — and improves over time for recurring roles.

Q: How does the agent handle bias mitigation and is it compliant with employment law?

Bias mitigation runs at three levels: exclusionary job-description language is flagged, first-pass scoring anonymises name, gender, age, graduation year, address, and school prestige, and demographic parity monitoring covers the output with a full audit trail. It is designed to meet EEOC adverse impact analysis, the EU AI Act, and the UK Equality Act 2010, producing explainable shortlists for human recruiters rather than making hiring decisions.

Q: Can the agent match internal employees to open roles, not just external candidates?

Yes — internal talent mobility is a native, often highest-ROI capability. The agent ingests workforce data from Workday, SAP SuccessFactors, or ADP to build a skills graph per employee, then runs the same competency scoring to surface strong internal matches before the external post goes live. Internal hires sourced this way ramp faster and stay longer.

Q: What does the ranked shortlist actually look like and what information does it provide?

Each candidate appears as a profile card with a composite match percentage, per-attribute score breakdown, strengths, identified gaps, and the specific evidence behind each score — so reviewers see exactly why Candidate A scored 87% and Candidate B 71%. Shortlists, with an AI-generated fit summary, deliver inside your existing ATS — Greenhouse, Lever, iCIMS, or Workday.

Q: How does the agent generate interview questions and how are they different from standard question banks?

Interview guides generate individually per candidate from their match profile, not a static bank. The agent targets competency areas where evidence was partial and generates STAR-framework questions with role-specific context, and for technical roles scopes verification tasks to the identified gaps.

Q: Which ATS and HRIS systems does the agent integrate with?

Native ATS integrations include Workday Recruiting, SAP SuccessFactors, Greenhouse, Lever, and iCIMS. HRIS coverage for internal mobility spans Workday HCM, SAP SuccessFactors, ADP, and BambooHR, plus LinkedIn Talent Hub and assessment platforms like Codility and HackerRank — all configurable for GDPR and CCPA data residency.

Q: What does implementation look like and how long before results are measurable?

Implementation runs 6–8 weeks: ATS integration, model calibration on 18–24 months of historical hiring data, a live pilot on 3–5 roles, then go-live with bias monitoring and TA training. Time-to-fill improvements (typically 25–35%) show from the first complete hiring cycle; bad-hire reduction is measurable after 2–3 cycles.

Q: How is this resume parsing software different from a keyword based applicant screening software?

Most applicant screening software relies on keyword Boolean logic that includes or excludes resumes on exact term matches. As resume parsing software, this agent parses each application into a structured competency profile and scores demonstrated skills, adjacent skill inference, and experience depth — surfacing qualified candidates keyword filters miss.

Q: Does the candidate screening software remove bias and stay compliant with employment law?

Yes. The agent anonymises name, gender, age, graduation year, address, and school prestige during first-pass scoring, ranking purely on demonstrated competencies, with demographic parity monitoring and a full audit trail. It is designed to meet EEOC adverse impact analysis, the EU AI Act, and the UK Equality Act 2010, producing explainable shortlists rather than making the hiring decision.

Bonami X-AI scores every application against the full role profile and returns a ranked, explainable shortlist in minutes — so recruiters action the top 10, not 250.

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Standards We Build To

Compliance is a design constraint we wire in from day one — not a review step before launch. Every agent we ship is built to the security, privacy, and governance standards that enterprise data demands.

Privacy & Data Protection

Customer and employee data protected across every region you operate in.

GDPR
CCPA
HIPAA
PIPEDA
DPDP Act 2023

Security & Risk

Security and risk controls, independently audited.

SOC 2 Type II
ISO/IEC 27001
OWASP Top 10
NIST CSF

AI Governance & Trust

Responsible-AI controls built into every agent — auditable decisions, human-in-the-loop review, and guardrails against bias and data leakage.

ISO/IEC 42001
NIST AI RMF
EU AI Act
Model Audit Trails
Human-in-the-Loop

Data Governance & Operations

Enterprise-grade data management with audit trails, role-based access, and validation engineered into every release rather than bolted on before launch.

Audit Trails
Role-Based Access
Data Residency
Release Validation

Accessibility

Usable by every employee and customer, by design.

WCAG 2.1 AA
Section 508

Reliability & Uptime

Production-grade availability backed by monitoring and SLAs.

99.9% Uptime SLA
SSO / SAML
Encryption at Rest

Core Capabilities of the AI Candidate-to-Role Matching Agent

Six capability pillars — from multi-dimensional skills matching to internal talent mobility and AI-generated interview guides.

Builds a competency model from job descriptions, hiring-manager input, and historical success profiles — a 20–40 attribute scoring rubric that captures real role requirements, not a keyword list.

A composite score for every applicant in seconds — skills match, experience depth, career trajectory, and team fit, ranked and fully explainable.

Anonymised scoring strips name, gender, age, address, and school-prestige signals — candidates are ranked purely on demonstrated competencies.

A workforce skills graph built from HRIS data, performance reviews, and learning records — matched to open roles before external candidates.

Interview guides tailored to each shortlisted candidate's match profile — questions target identified skills gaps, not one generic set.

Personalised status updates at every pipeline stage — receipt acknowledgement, screening timelines, rejection feedback, and next-step guidance.

Skills Matching & Competency Mapping

Builds a competency model from job descriptions, hiring-manager input, and historical success profiles — a 20–40 attribute scoring rubric that captures real role requirements, not a keyword list.

Candidate Scoring & Ranked Shortlists

A composite score for every applicant in seconds — skills match, experience depth, career trajectory, and team fit, ranked and fully explainable.

Bias Mitigation & Fairness Controls

Anonymised scoring strips name, gender, age, address, and school-prestige signals — candidates are ranked purely on demonstrated competencies.

Talent Mobility & Skills Graph

A workforce skills graph built from HRIS data, performance reviews, and learning records — matched to open roles before external candidates.

Interview Guides & Assessment Design

Interview guides tailored to each shortlisted candidate's match profile — questions target identified skills gaps, not one generic set.

Candidate Experience & Pipeline

Personalised status updates at every pipeline stage — receipt acknowledgement, screening timelines, rejection feedback, and next-step guidance.

Security & Compliance Responsibility

Every AI agent we build is designed with data protection and security at its core — tailored to your compliance requirements.

Why People Leaders Deploy Bonami's

From Keyword Matching to Genuine Skills Intelligence

Traditional ATS filtering is keyword matching — a candidate either has "Python" in their resume or they are filtered out, regardless of whether they have demonstrated the underlying competency through adjacent tools or described outcomes.

From 250 Resumes to a Ranked, Explainable Shortlist in Minutes

The six-second resume review is a rational response to impossible volume — an enterprise TA team cannot give each 250-application role the deep review that accurate assessment requires.

From Hiring Manager Intuition to Structured, Defensible Decisions

Harvard Business Review research shows unstructured interviews predict job performance at a validity coefficient of just 0.38 — meaning gut-feel assessments are wrong about job performance nearly two-thirds of the time.

Real Business Impact

Measurable improvements in efficiency, customer experience, and operational performance.

AI-Driven Social Media Personalization & Moderation Platform

Building a trust-centered social ecosystem with AI personalization, real-time moderation, and sentiment analytics — improving engagement by 70% and achieving 95%+ harmful content detection accuracy.

Business results:

70% improvement in engagement

95%+ harmful content detection accuracy

35% increase in content relevance

Read Success Story

AI-Driven Social Media Personalization & Moderation Platform

AI-Powered Workforce & Shift Management Platform

Improving scheduling efficiency by 45% with AI-driven conflict resolution.

Business results:

45% scheduling efficiency improvement

90% reduction in manual HR docs

30% increase in employee engagement

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AI-Powered Workforce & Shift Management Platform

How We Work With You

Our process is designed to be clear, collaborative, and focused on delivering real business value. We believe the best AI solutions come from understanding your specific challenges and goals first.

We start by learning about your business objectives, current systems, and team capabilities. This helps us identify the right opportunities for AI to make a real impact.

Based on what we learn, we create a detailed plan for your AI implementation. This includes technical requirements, timeline, and success metrics.

We develop the AI solution in iterative cycles with regular check-ins. This allows us to adjust based on your feedback and ensure everything works as expected.

We handle the technical deployment and train your team to use the new AI tools effectively. This includes documentation and hands-on support.

After launch, we continue to monitor performance, make improvements, and help you get the most value from your AI investment.

Why People Leaders Deploy Bonami's

From Keyword Matching to Genuine Skills Intelligence

From 250 Resumes to a Ranked, Explainable Shortlist in Minutes

From Hiring Manager Intuition to Structured, Defensible Decisions

Our Process

Core Capabilities of the AI Candidate-to-Role Matching Agent

Six capability pillars — from multi-dimensional skills matching to internal talent mobility and AI-generated interview guides.

Skills Matching & Competency Mapping

Builds a competency model from job descriptions, hiring-manager input, and historical success profiles

Candidate Scoring & Ranked Shortlists

A composite score for every applicant in seconds

Bias Mitigation & Fairness Controls

Anonymised scoring strips name, gender, age, address, and school-prestige signals

Talent Mobility & Skills Graph

A workforce skills graph built from HRIS data, performance reviews, and learning records

Interview Guides & Assessment Design

Interview guides tailored to each shortlisted candidate's match profile — questions target identified skills gaps, not one generic set.

Candidate Experience & Pipeline

Personalised status updates at every pipeline stage

A Single Bad Hire at Mid-Manager Level Costs an Average of $240,000 — Five Times the Annual Salary.

SHRM's research on failed hires includes lost productivity, hiring team time, onboarding costs, team disruption, and re-recruitment.

Get Talent Audit

The Right Candidate Is in Your Pipeline. Your Process Is Failing to Find Them.

The average corporate job posting receives 250 applications, yet recruiters spend only 6–7 seconds reviewing each resume — leading to one in three hires being considered a "bad hire" within the first year, with costs from $14,900 to $240,000 (SHRM).