Technical Implementation & Commercial Proposal

AI-Powered Translation Management System (TMS) Integration for SOCPA

Project Strategy

Torjoman's approach prioritizes the AI core: benchmarking and selecting the most accurate open-source engines for SOCPA's specialized terminology first. Once the engine is frozen, we will migrate our proven TMS core into the SOCPA environment, applying a custom White-Label UI and integrating the Kashiff Proofreading Engine for final quality assurance.

Implementation Timeline (8 Months)

1

AI Engine Benchmarking & Language Modeling

MONTH 1 - 3

  • ● Comparative Benchmarking: Testing multiple open-source LLMs (Llama 3, Mistral, AraBART) to identify the best accuracy for professional accounting texts.
  • ● Knowledge Loading: Preparing Translation Memories (TM) and Terminology Bases (TB) for the selected engine.
  • ● Model Freezing: Establishing the baseline AI version to ensure consistency and auditing capabilities for exam cycles.
2

Triple-Node Infrastructure & White-Label UI

MONTH 3 - 4

  • ● Infra Setup: Provisioning and hardening the three-node environment (AI Engine, App Server, Big Data Server) within SOCPA's network.
  • ● Branding: Implementing SOCPA's visual identity (emerald theme, logos) and RTL typography into our TMS product.
  • ● UX/Bug Fixes: Resolving existing UI bugs and optimizing workflows for professional translation tasks.
3

Platform Integration & Kashiff Engine

MONTH 4 - 6

  • ● Full Sync: Integrating the frozen AI engine into the productized Torjoman TMS via secure local API.
  • ● Kashiff Proofreading: Implementing the automated grammar and spelling gate for post-review text validation.
  • ● Productization: Final backend refinements and performance tuning for the high-concurrency offline environment.
4

QA, Training & Final Handover

MONTH 6 - 8

  • ● Validation: End-to-end UAT cycles to meet the 95% accuracy KPI.
  • ● Technical Transfer: Deep-dive training for SOCPA's IT teams on AI and Big Data node management.
  • ● Closeout: Handover of all Source Code, BRDs, and Architecture documentation.

Financial Proposal (USD)

One-time Implementation

Licensing, White-Labeling & AI Engineering

$300,000
  • ✔ Local AI Benchmarking & Specialization.
  • ✔ White-Label TMS Customization & Bug Fixes.
  • ✔ Kashiff Engine Deep Integration.
  • ✔ IP Transfer & Full Source Code Delivery.

Annual Support Fee

Maintenance & SLA (Starts Year 2)

$50,000/year
  • ✔ Priority L3 Response for AI/Kashiff Issues.
  • ✔ Bi-Annual AI Model Performance Review.
  • ✔ Ongoing Offline Security Compliance Patches.

Hardware Infrastructure Architecture

Isolated Triple-Node Cluster

To run Large Language Models and specialized proofreading engines locally, we recommend a high-performance triple-server environment:

1. AI Engine Node

Hosting the frozen LLM and Kashiff Engine. High GPU demand.

  • • Dual NVIDIA A100 (80GB) or 4x L40S
  • • 128GB High-speed RAM
  • • PCIe Gen 5.0 Communication
$65,000 - $85,000

2. Application Node

Hosts the productized Torjoman TMS, Web UI, and workflow logic.

  • • Dual-Socket 64-Core Enterprise CPU
  • • 128GB RAM (Standard ECC)
  • • Local SSL & High-speed Intranet
$15,000 - $22,000

3. Big Data Node

Houses massive Translation Memories (TM) and Terminology Bases.

  • • Enterprise NVMe Raid-10 Storage
  • • 256GB RAM for heavy DB caching
  • • High-throughput Local Networking
$12,000 - $18,000

Total Estimated Infrastructure CAPEX:

$92,000 - $125,000