Revised Proposal for IMFORCE Consolidated

AI-Powered Recruitment Intelligence System

A custom-built system that monitors job boards, career pages, and social platforms across South Africa, then delivers qualified, enriched leads with call scripts directly to your sales team.

Prepared For Wasim Hoosen
Date 10 April 2026
Type Custom AI Buildout
Valid Until 30 April 2026

Your salespeople are researchers, not closers

IMFORCE has a growing client base and a team manually scraping job boards, cold calling gatekeepers, and hoping to reach decision-makers. Every hour spent researching is an hour not spent closing.

01

Manual Prospecting

Your team logs into multiple job boards and company websites, copies job details, researches the company, hunts for contact info, then makes the call. This takes 2-3 hours per lead. Meanwhile, a competitor who found that posting yesterday has already closed.

02

No Qualification

Thousands of jobs are posted weekly across SA. Without filtering, salespeople chase volume instead of value. You told us this yourself: quality over quantity. A system that surfaces 50 qualified leads beats 5,000 unfiltered ones.

03

Wrong Contacts

Cold calls hit generic inboxes and junior staff. Your team needs the hiring manager or HR director who signs the recruitment contract. Not the receptionist.

What your team receives

We build a system that runs continuously in the background. It monitors, qualifies, and delivers. Your salespeople open a dashboard each morning with scored leads, decision-maker contacts, and ready-made call scripts.

1

Automated Monitoring

The system watches job boards, company career pages, and social platforms across South Africa around the clock. When a company posts a new role, the system captures it within hours.

2

Intelligent Filtering

Not every job posting is a lead worth pursuing. The system scores each one based on role seniority, salary band, industry fit, and freshness. Recruitment agency postings are automatically excluded. Your team only sees leads worth their time.

3

Decision-Maker Contacts

For every qualified lead, the system identifies the relevant hiring manager or HR director with verified contact details. Name, email, phone, and LinkedIn profile. No more cold calling switchboards.

4

Custom Call Scripts

Each lead comes with a ready-made call script built from the company's background, the specific role they are hiring for, and a tailored value proposition for IMFORCE. Your salespeople pick up the phone and close.

5

Real-Time Alerts

Hot leads trigger instant notifications via SMS and email to the assigned salesperson. Daily digest emails summarise new opportunities. Weekly reports track pipeline performance by region and industry.

6

Geographic and Industry Control

Start with KwaZulu-Natal. Expand to Gauteng, Western Cape, or nationwide as your team grows. Filter by industry, role level, or salary band. You control the scope.

What you should know upfront

We are not legal experts, and this is not legal advice. But there are compliance considerations you should be aware of before investing. We want you to have this information so you can make an informed decision and seek legal counsel where needed.

POPIA (Protection of Personal Information Act)

Collecting publicly visible job listing data (titles, companies, locations, descriptions) is generally lower risk. However, collecting personal contact details (names, emails, phone numbers) of decision-makers without their consent may raise compliance issues under POPIA. One possible approach is sourcing contact details through third-party databases that manage their own consent frameworks. Whether this is sufficient for your use case is something we recommend confirming with a POPIA specialist before we build.

Platform Terms of Service

Most major job boards (PNet, CareerJunction, Indeed, LinkedIn) include clauses restricting automated data collection in their terms of service. This is a known grey area in the recruitment intelligence industry globally. There are possible workarounds, such as focusing on publicly visible data and using respectful rate limits. But we want to be transparent: we cannot guarantee that these approaches eliminate all legal risk. This is a decision you should make with full awareness.

Cybercrimes Act

South Africa's Cybercrimes Act criminalises unauthorised access to computer systems, which could apply to scraping that bypasses technical protections (CAPTCHAs, login walls, rate limiters). The system will be designed to avoid these boundaries, but the legal interpretation of "unauthorised access" in the context of public data scraping has not been definitively tested in SA courts.

What we recommend

We will identify and flag every legal risk during Phase 1. For each data source, we will map both the technical feasibility and the compliance considerations. We will present possible approaches with their associated risks. The final decision on which sources to use, and what level of legal risk is acceptable, is yours to make. We strongly recommend consulting a POPIA specialist before Phase 2 begins. We build what you approve.

Two phases. You own the blueprint either way.

Phase 1 gives you a complete system blueprint and feasibility assessment. You keep it regardless of whether you proceed to the build. Phase 2 delivers the working system.

1

Discovery + Blueprint

Phase 1
  • 90-minute audit of your current prospecting workflow
  • Data source mapping: which platforms to monitor, what is technically feasible, what is legally compliant
  • Integration plan for your existing CRM
  • Technical architecture document (yours to keep forever)
  • Lead scoring model tailored to IMFORCE's placement criteria
  • Legal risk assessment: POPIA, Cybercrimes Act, and platform terms of service flagged per data source so you can make informed decisions
R29,900
once-off
2

Build + Launch

Phase 2
  • Complete system build per the Phase 1 blueprint
  • Scraping pipeline across all mapped data sources
  • AI qualification engine with scoring and script generation
  • Decision-maker enrichment pipeline with verified SA contacts
  • Web dashboard for lead management and team assignment
  • SMS and email alert system for hot leads
  • Team training session (recorded for future hires)
  • 14 days post-launch support and scoring calibration
R59,900
once-off

Total Investment

Payable per phase. No upfront lump sum.
R89,900

Optional: Ongoing Optimisation

Monthly data source tuning, scoring refinement based on your team's feedback, performance reporting, and priority support. Cancel anytime.
R4,900/month
The system's monthly operating costs for AI, data services, and hosting are approximately R10,000 per month. That is less than a quarter of one placement fee.

The numbers that matter

At standard South African placement fees, the system pays for itself with just two additional placements.

R45K+
Per Placement
Average fee at 15% on a R300K annual salary
2
Placements to Break Even
Two extra placements cover the full R89,900 investment
Month 1
Target Payback
System goes live within weeks. ROI starts immediately.

Here is the maths

01
Average placement salary: R300,000/year (conservative, mid-level role)
02
Your placement fee at 15%: R45,000 per placement
03
Total system investment: R89,900
04
Placements needed to break even: 2 placements
05
Every placement after that is pure profit from a system that runs 24/7
If the system generates just 3 extra placements per month, that is R135,000 in new revenue, every month, on autopilot.

Ready to start with Phase 1?

You told us you want to see that it works before committing. Phase 1 is designed exactly for that. Full blueprint, full clarity, and you own it regardless of whether you proceed to Phase 2.

This proposal is valid until 30 April 2026. Prepared exclusively for IMFORCE Consolidated.

During our call you described a second project: an incentivised recruitment marketplace platform. You asked us to research it honestly and tell you if it will work. That analysis, including market data, legal risks, and our honest recommendation, is available as a separate document: Project 2 Feasibility Report