Section 01

The Mandate. The Intelligence. The Opportunity.

Hadaf's mandate is to serve three very different stakeholders. Hadaf's asset is 25 years of accumulated intelligence. The opportunity is to connect the two — deliberately, systematically, at scale.

The mandate
Who Hadaf serves

Three stakeholders. Very different needs.

Citizens
A meaningful career path, not just a job
Often unclear needs
Companies
Right talent for right requirements, at the right time
Mixed needs
Government
National outcomes, workforce readiness, Vision 2030 delivery
Clear outcomes

Clear needs are easy. Unclear needs are where intelligence matters.

The intelligence
What Hadaf holds

25 years, already earned.

Knowledge assets
What the organization knows
Citizen recordsLabor market dataEmployer dataTraining outcomesPolicies & regulationsHistorical decisionsReportsDocuments
Expertise assets
How the organization makes decisions
SME expertiseBusiness rulesOperating proceduresAssessment frameworksEligibility criteriaIntervention methodologiesBest practices

The intelligence exists. What's missing is the activation layer.

The opportunity

Transform 25 years of institutional knowledge and expertise into an AI Intelligence Hub — a reusable layer that powers agentic workflows across every stakeholder need, clear or unclear.

Section 02

The AI Intelligence Hub.

Institutional assets become reusable layers. Layers power agents. Agents work with people. Every cycle gets smarter.

Visual 1 of 2 · The Hub Architecture
↻ Continuous learning loop
Stakeholder outcomes
Every stakeholder, better served.
Citizens
Personalized career pathways
Proactive career guidance
Barrier support coordination
Companies
Refined talent shortlists
Proactive quota advisory
Retention support
Government
Forward-looking labor intelligence
Program ROI attribution
Policy impact simulation
delivers to
Agentic workflow layer
Two agent types. Different purposes. Same Hub.
Experience agents
Interface with stakeholders
Simplify journeys · Understand needs · Deliver outcomes
Requirement Collection Agent
Understands company needs
Interview & Refining Agent
Enriches candidate profiles
Career Guidance Agent
Personalizes citizen pathways
Execution agents
Reason, match, monitor
Behind the scenes · No stakeholder-facing interface
Skills Matching Agent
Ranks candidate-role fit
Compliance Agent
Monitors Nitaqat and subsidy
Retention Risk Agent
Flags churn pre-subsidy end
Illustrative · Real agent portfolio defined in discovery
activates
Prediction & reasoning
The Hub predicts, reasons, recommends
Demand forecastingSkills gap projectionCandidate-role fitRetention predictionProgram effectiveness attribution
powers
Institutional foundation
25 years of accumulated knowledge and expertise
Knowledge layer
Citizen recordsLabor marketEmployer dataTraining outcomesPoliciesHistorical decisions
Expertise layer
SME expertiseBusiness rulesAssessment frameworksEligibility criteriaIntervention methodologiesBest practices
External data
Feeds the foundation
Company financials & hiring plans
Sector performance & growth
Macro-economic indicators
Nitaqat regulatory pipeline
Educational pipeline data

The foundation is what Hadaf owns. External signals are what keep it current.

Visual 2 of 2 · How agents and people work together

Agents recommend. People decide. The system learns.

Agent
Analyzes, matches, recommends
Screens 1000s of records in seconds
Applies 25 years of institutional patterns
Proposes ranked recommendations with reasoning
Where machines excel
Recommendation Inbox
◆ →
◆ →
← ✓
Decision Response
Human-in-the-loop
Reviews, decides, guides
Validates agent recommendations
Applies contextual judgment
Guides system learning through overrides
Where judgment matters
Three learning loops

The Hub doesn't just serve. It evolves.

01
The Hub gets smarter with every project
What learns:
Frameworks. Data. Prediction models.
Written back to:
Enriches the Institutional Foundation. Sharpens the Prediction Layer.
02
Every agent improves with every interaction
What learns:
The Interview Agent notices accent confusion. The Matching Agent learns from officer overrides.
Written back to:
Agent behavior refined. New agent capabilities identified.
03
The Hadaf team sees what's needed next
What learns:
Where the Hub falls short. What new capabilities stakeholders want.
Written back to:
Feature roadmap. New agents commissioned. Strategic direction shaped by Hadaf.

The Hub serves. And Hadaf drives its evolution.

An agentic OS for Hadaf

Not a tool. Not a chatbot. An operating system that runs on Hadaf's own knowledge and expertise — extending it, activating it, and getting sharper with every cycle.

Section 03

Traditional hiring ends. Agentic hiring compounds.

In a traditional hiring flow, if a candidate doesn't match a role, the process ends — and every insight collected during screening and interviewing is lost. Agentic hiring inverts this. Every candidate interaction enriches the institutional foundation. A missed match for Company A becomes a strong match for Company B — with a richer profile than before.

The contrast

Two ways to run a hiring workflow.

The traditional flowLinear. Rigid. Ends at rejection.
Requirement filed
Candidates sourced manually
Interview conducted · Notes taken
Match decision
↙ Match
No match ↘
Placement made
Exit · Positive
Rejection sentInterview data discarded · Profile never updated
Dead-end · Data lost
90% of the intelligence generated during recruitment is thrown away when a candidate is rejected. Every future match starts from zero.
The agentic flowBranching. Compounding. Every path enriches the Hub.
Requirement captured · OR proactive signal detected
→ Foundation enrichedmarket context, quota impact
Candidates matched · Skills + culture + retention
→ Foundation enrichedmatch patterns learned
Voice pre-screening + interview conducted
→ Foundation enrichedsoft skills, motivation captured
Human officer reviews in Decision Inbox
→ Foundation enrichedoverride patterns train agents
↙ Match
No match ↘
Placement activated · Onboarding begins
Exit · Sustained placement
↺ Placement outcome tracked · Feeds learning
Profile enriched · Re-routed to better-fit roles
Loops back · Compounding
↺ Re-enters matching for other open roles
Every interaction — even for candidates not matched — enriches the Institutional Foundation. Nothing is thrown away. Every hiring cycle starts smarter than the last.

The traditional flow ends. The agentic flow loops. That difference — repeated across millions of interactions — is how institutional intelligence compounds.

The modules · Already built

Seven modules. One connected workflow.

Every module below is a live capability in Lyzr's HR Agentic OS. Together they run the agentic flow shown above — with humans in the loop where judgment matters.

01
Talent Pipeline

Pipelines pre-built for anticipated demand. When Nitaqat changes are forecast or sector demand surges, qualified Saudi talent is already identified and ready.

agent
02
Candidate Sourcing

When a specific requirement arrives, the sourcing agent searches Jadarat, Tamheer graduates, Doroob completers — and applies 25 years of institutional patterns to surface non-obvious matches.

agent
03
Candidate Matching

Ranks candidates on hard skills, culture fit, and predicted retention. Every ranking includes the reasoning — no black box. Officers see why each candidate scored where they did.

agent
04
Pre-screening Voice Agent

First-level qualification via voice interview in Arabic or English. Captures soft skills, motivation, communication style. Every response enriches the candidate's profile — permanently.

agent
05
Decision Inbox

Officer reviews shortlists, interview summaries, and agent recommendations in one place. Approves, overrides, or requests refinement. Every decision logged and used to sharpen the agents.

human
06
Interview Scheduling

Once the officer approves a shortlist, interview coordination is automated. Calendars synced, invitations sent, reminders managed. Officer time is protected for judgment work.

agent
07
Employee Onboarding

Placement activated. Subsidy pre-validated. GOSI registration triggered. Candidate onboarded to the employer's workflow. Outcome tracking begins — feeding the next cycle's learning.

agenthuman
The Hub difference

The modules are ready. What Hadaf brings is the institutional knowledge that makes them uniquely yours.

Section 04

Every build funds the next.

The AI Intelligence Hub is not built in one shot. It is built through a disciplined portfolio — measuring each candidate use case, then prioritizing across strategic value, human judgment, and shared capability. Every win funds the next.

01
Step 01 · Scoring

Every workflow measured on quantitative criteria

Scoring works best when it is:
Quantitative — based on measurable data (volume, cycle time, cost, data availability)
Granular — evaluated at individual workflow level, not aggregate
Consistent — same criteria applied across every candidate use case

Scoring produces a rank order. But rank alone doesn't reveal what to build first — or where to reuse what you've already built.

Illustrative scoring worksheet from a prior engagement.
02
Step 02 · 2×2 Prioritization

From scores to strategy

The 2×2 layer adds what scoring alone can't:
Strategic judgment — political context, stakeholder readiness, timing considerations
Portfolio view — how each workflow relates to others across the pipeline
Capability visibility — which workflows share underlying requirements and can be built once
Deploy now

High value · High feasibility

Invest & build

High value · Lower feasibility

Quick wins

Lower value · High feasibility

Investigate

Lower value · Lower feasibility

Illustrative wave structure from a prior engagement.
Within step 02 · Capability clustering

One capability, many workflows

The 2×2 does one more thing scoring can't — it surfaces workflows that share underlying capability requirements. Same data sources. Same integration patterns. Same agent architectures. Build the capability once. Reuse it across every workflow that needs it. That's how the portfolio stops reinventing the wheel.

Hiring intelligence
Retention monitoring
Program effectiveness
Shared capability
Finance data integration

Built once. Powers three workflows. Every future workflow needing finance data reuses it.

Without clustering, three workflows require three separate integrations — three teams, three timelines, three budgets. With clustering, one capability serves all three. And when the fourth workflow arrives, the same capability serves it too — at zero additional integration cost.

The compounding playbook

Small wins fund big builds. Shared capabilities compound. Momentum compounds into transformation.

Section 05

Government-grade by design.

For a government partner, five things are non-negotiable: control of the stack, security at every layer, scale for national volumes, responsible AI at every decision, and full auditability. Everything else is a nice-to-have.

The five pillars

Non-negotiables for a government partner.

Sovereignty

Any LLM. Any cloud. Any framework. Hadaf owns and controls the stack. No lock-in, ever.

Security

SOC 2 Type II · ISO 27001 · PDPL-compliant · Data residency in KSA · Encrypted at rest and in transit · Zero data leaves the Hadaf boundary.

Scalability

Proven at millions of transactions · Multi-tenancy · Horizontal scaling · High-availability SLA · Ready for national scale.

Responsible AI

Bias monitoring · Fairness controls · Explainability · Human oversight at every high-stakes decision · Autonomy ladder from Assist to Autonomous.

Auditability

Every agent decision logged · Immutable audit trails · Role-based access · Compliance reporting · Agent CI/CD with full traceability.

Platform architecture

Sovereign full-stack agent platform

What's included

The Lyzr partnership — one platform, three enablers.

The Agentic Workbench powers the engine. The three enablers accelerate the journey on top of it.

Consulting

Journey planning · Use case prioritization · Value realization · MBR/QBR frameworks

Forward Deployed Engineers

Applied engineers embedded with Hadaf · Accelerate first builds · Transfer capability to Hadaf's team

Training + Knowledge Repository

Enablement for Hadaf independence · Reusable modules · Faster future builds

The foundation · Core platform
Agentic Workbench

The platform that powers everything above. Build, run, govern, and improve agents in one place. The three enablers accelerate delivery on top of this foundation. Without the Workbench, there is no engine to enable.

The partnership promise

Lyzr is not a vendor Hadaf depends on. Lyzr is the enabler that makes Hadaf independent.

Section 06

Proven where trust must be earned.

Government agencies. Global consulting firms. Fortune 500 enterprises. Lyzr has already been chosen where the stakes are highest and the scrutiny is deepest.

Chosen by peers

Trusted by the environments Hadaf operates in.

Accenture logo
WTW logo
Publicis Groupe logo
Crown Castle logo
KPMG logo
Prophet logo
Global consulting · Fortune 500 · Regulated enterprises
Backed by

Strategic investors betting on Lyzr's agentic future.

Accenture Ventures logo
Rocketship.vc logo
Firstsource logo
Strategic investors · Capital and conviction
Recognized by the firms that shape the market

Awards and analyst recognition.

CB Insights logo
CB Insights · 2026
Top AI 100
Ranked #6

By Mosaic Score. Top 6% of the cohort.

Gartner logo
Gartner · 2026
Hype Cycle for Agentic AI
Featured Mention

Named vendor in the emerging agentic AI category.

HFS Research logo
HFS Horizons · 2026
Enterprise Innovator
Horizon 2

Agentic Technology category.

Everest Group logo
Everest PEAK Matrix® · 2026
Agentic AI Products
Major Contender

Recognized in the leading independent evaluation.

Independent analyst validation · 2026
Certified · Secure · Ready

The credentials that matter.

SOC 2 Type II
Security & availability
ISO 27001
Information security
GDPR + PDPL
Data protection
HIPAA-ready
Healthcare-grade privacy
SOC 2 Type II + ISO 27701
Privacy management
The difference

Why partners choose Lyzr over building internally.

Speed to production

WTW went live faster on Lyzr than on internal build attempts. Where compliance is real, speed depends on the platform.

Compounding economics

ShadowLM captures approved decisions, fine-tunes small models on them, and reduces inference cost over time — up to 90%. Internal builds get more expensive; Lyzr gets cheaper.

Governance built-in

Audit trails, autonomy ladder, hallucination management, in-path guardrails. Building this internally is 5-6 months of engineering before writing a single workflow.

The partnership

Hadaf brings 25 years of institutional knowledge and expertise. Lyzr brings the platform to activate it. Together — an AI Intelligence Hub that serves every stakeholder, every day, sharper every cycle.

Confidential · Prepared for Hadaf leadership · Lyzr · 2026