AI that instantly filters irrelevant candidates for Sudan logistics roles
Recruiters waste hours sifting through irrelevant candidates like construction project managers when searching for remote logistics talent in Sudan on platforms like Himalayas.
LogiScreen uses a specialized AI model trained on African logistics terminology, common hiring mismatches, and regional context to automatically score and rank candidates. Recruiters upload resumes or connect their ATS and receive only relevant matches with plain-English explanations of why someone fits or doesn't fit a remote logistics role in Sudan. This eliminates hours of manual sifting through construction managers and unrelated profiles.
Recruiters and operations leaders at logistics firms hiring remote specialists in Sudan and similar African markets
Domain-specific AI trained exclusively on 5000+ labeled African logistics resumes and real hiring outcomes, allowing it to detect subtle relevance signals that general tools miss.
professional
Extracts skills, experience, education and location from PDF, DOCX and image resumes
Uses custom prompts and few-shot learning to score candidates on logistics relevance for African markets
Interactive table with candidate cards, match scores, and detailed reasoning
Pre-built templates for common Sudan remote logistics roles with contextual prompts
Process up to 50 resumes at once with batch reporting
Define industries, titles and keywords to automatically reject
One-click import from Greenhouse, Lever and BambooHR
Export professional PDF reports with AI insights for hiring teams
Share screenings and notes with team members
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No | |
| company_name | text | Yes |
| role | text | Yes |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| title | text | No |
| description | text | Yes |
| requirements | text | Yes |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| full_name | text | No |
| text | Yes | |
| location | text | Yes |
| parsed_skills | text | Yes |
| years_experience | int | Yes |
| raw_resume_text | text | Yes |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| job_id | uuid | Yes |
| candidate_id | uuid | No |
| user_id | uuid | No |
| score | int | No |
| reasoning | text | Yes |
| status | text | No |
| created_at | timestamp | No |
/api/jobsCreate new job requirement for screening
/api/screenUpload resume(s) and trigger AI screening
/api/jobs/[id]/matchesRetrieve ranked candidates with reasoning for a job
/api/candidates/searchSearch previously screened candidates
/api/subscription/webhookHandle Stripe subscription events
/api/reports/[id]Generate and download PDF screening report
Limited to 5 screenings per month
None
Usage-based overages
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 110 | 7% | $192 | $2,304 |
| Month 6 | 720 | 14% | $2,520 | $30,240 |
AI trained specifically for remote logistics roles in Sudan and Africa. Instantly filter out construction managers and unrelated profiles.
1. personally message 30 logistics recruiters on LinkedIn who have posted Sudan or East Africa roles in the past 6 months offering lifetime 50% discount for case study. 2. Post detailed problem-solution thread on r/recruiting and r/logistics with waitlist link. 3. Sponsor one virtual meetup of African Supply Chain professionals on LinkedIn and offer 25 free Pro accounts to attendees.
Large remote talent database
Generic search produces many irrelevant results for specialized roles
Hyper-specialized AI that understands logistics domain and African context
Enormous network effects
Requires significant manual filtering and lacks domain intelligence
Automated, explainable AI filtering specific to logistics in Sudan/Africa
Continuous feedback loop from recruiter overrides and outcomes creates a proprietary dataset of African logistics hiring patterns that improves the model weekly.
LLM costs have dropped dramatically while remote talent pools in Sudan and East Africa have matured significantly post-2022 internet infrastructure investments.
AI accuracy below 80% on first version
Combine LLM with deterministic keyword and industry filters. Include easy human override and feedback mechanism to improve model.
Recruiters reluctant to trust AI for hiring
Emphasize transparency with full reasoning shown for every decision and offer money-back guarantee.
Data privacy compliance with Sudanese and EU laws
Implement strict consent flows, data minimization, and consult African privacy lawyer before launch.
Success: At least 9 confirm they would pay $25/month for a specialized filter
Success: NPS > 40 and at least 15 users complete 10+ screenings
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