Yarn EJar is the AI contract reader that extracts every clause from a Saudi lease, maps it to your internal fields, and syncs the result into your operational system. Officially integrated with the EJAR platform.
A Saudi operator with 500 units registers or renews roughly 40 to 80 EJAR contracts every month. Each one is a mix of regulated clauses and landlord-specific annexes, typically Arabic, often scanned. Reading them manually is slow, it is error prone, and it creates the compliance risk you were trying to avoid.
A clerical review of each contract takes real time. Multiply by your monthly volume. That is a full FTE you cannot redeploy to higher value work.
One wrong SAR amount or date in your PMS means a mismatch with EJAR, a delayed renewal, or a flagged invoice. Fixing one of these after the fact is a week of back-and-forth.
Renewal dates, rent escalations, penalty clauses. Critical data lives inside PDFs instead of a queryable system. Nobody sees the full portfolio at once.
Yarn EJar replaces the 20 minute manual review with an AI pass that preserves every clause and exposes the structured data to the rest of your stack.
PDF, scanned image, or direct pull from the EJAR platform. Arabic, English, or mixed. The AI handles stamped and handwritten addenda the same way it handles clean digital PDFs.
Parties, property, rent amount and schedule, tenure dates, penalty clauses, renewal terms, bank details, and annexed obligations. Every extracted field links back to the exact source line in the contract for audit.
Push to Yarn PMS, your ERP, or any REST endpoint you configure. Contracts also flow into EJAR registration if that part of the process is still pending.
From upload to structured output in under 60 seconds, even for mixed language scanned PDFs with addenda.
Native integration with Yarn PMS, REST API for custom endpoints, and webhook triggers for downstream automation.
Role based access, review queues, approval workflows, and a collaborative annotation layer so legal can flag a clause without exporting to Word.
Portfolio dashboard with upcoming renewals, at risk contracts, rent escalation forecasts, and an alert feed your team can action.
Simple per-contract pricing. No seat fees for reviewers. Volume discounts kick in automatically at 500, 2,000, and 10,000 contracts per month.
Data hosted inside the Kingdom, PDPL compliant by design, NCA ECC controls applied to every storage and transit path.
Three tiers. Pick the one that matches your monthly contract volume. Move between tiers whenever volume shifts.
SAR 299 / month
Up to 50 contracts per month.
SAR 999 / month
Up to 500 contracts per month, then SAR 1.50 per extra contract.
Custom
2,000+ contracts per month, volume tiered.
EJar is designed for operators who cannot afford a compliance surprise in a vendor audit.
Personal data handling rules applied to every upload. Data subject rights supported natively, including deletion and portability.
Encryption at rest and in transit, role based access, session logging, and quarterly penetration testing against Essential Cyber Security Controls.
Direct link to EJAR's registration and renewal APIs, so contract reading and filing happen in the same flow.
Yes. The model was trained on real Saudi lease documents, including scanned pages with stamps, handwritten addenda, and mixed Arabic and English sections. Accuracy drops slightly with very poor scans; the system flags low confidence fields for human review.
On clean PDFs we measure over 98% field accuracy. On scanned documents it is around 93%. The review queue surfaces every low confidence field so a reviewer can correct it in seconds. Corrections feed back into fine tuning.
Both. Customers often adopt EJar first as a standalone AI reader, then connect it to Yarn PMS or their existing system. The REST API is the same either way.
Inside Saudi Arabia. We use Saudi cloud regions for all customer data, encrypted at rest with keys managed under NCA ECC controls. Your contracts never leave the Kingdom.
Upload a sample contract during the demo. You will see the extracted fields, the confidence scores, and the integration output before we talk about pricing.
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