← Semua Articles

Binaan AI the Rules. PHP Executes at Skala.✎ Edit

👁 475 tontonan
Binaan AI the Rules. PHP Executes at Skala.
Building Smarter Pengkompil Penyata Banks with AI + PHP Automasi

Most discussions around Document AI focus on using AI to process every document.

We took a different approach.

At Ainna, AI is used to build the parser, not to run the parser.

When a baharu bank statement format is introduced, AI analyses the document and generates four reusable components:

✅ Sedang parse Rules – Identify transaction tables, dates, descriptions, debit, credit, and balances.

✅ Cleaning Rules – Correct OCR issues, merge fragmented rows, remove headers and footers, and normalize the extracted data.

✅ Peraturan Pengesahan – Verify running balances, detect duplicates, validate transaction integrity, and check data consistency.

✅ Keyakinan Pemarkahan – Assign a keyakinan score to every compiled statement based on extraction and validation accuracy.

Once generated, these rules are stored as reusable rule sets.

From that point onward, our PHP execution engine processes future statements using the saved rules-without calling AI again.

The result is:

  • ⚡ Lebih Pantas execution

  • 💰 Significantly lower AI costs

  • 📊 Consistent outputs

  • 🚀 Boleh Skala processing for millions of statements

AI is only invoked when keyakinan drops below a user-defined threshold.

For example:

  • Keyakinan ≥ 95% → Execute using existing rules.

  • Keyakinan < user threshold → AI analyses the document, refines the rules, or creates a baharu parser version.

This creates a continuous improvement loop where AI enhances the system only when required, while routine processing remains deterministic, lightweight, and cost-efficient.

AI builds the intelligence. PHP executes it at scale.

For high-volume document processing, this architecture is often more economical, predictable, and easier to maintain than sending every document through an LLM.

#ArtificialIntelligence #PHP #DocumentAI #OCR #FinTech #Automasi #RuleEngine #DataEngineering #MachineLearning #BankStatement #Ainna

Ruang pembaca

Apa pendapat anda?

Komen disemak sebelum diterbitkan. Email diperlukan untuk moderasi dan tidak dipaparkan kepada pembaca.

✦ Reaksi dijana sistem - contoh automatik, bukan komen pembaca sebenar
Mei China

如果还有95%的后续,我会继续读。

Kavitha India

Clearer than the vendor decks I get about keyakinan < user threshold.

Arjun India

Useful. We are dealing with PHP executes it at scale right now.

Artificial Intelligence

Article image
Edge AI Kecerdasan IoT dan Linux terbenam di pinggir 14 edge agents → offline-capable Terokai →
SmartCity Infrastruktur dan operasi bandar pintar berkuasa AI 24 domains → one intelligent operating layer Terokai →
Robotics Robotik yang ditadbir di pinggir industri Perception → safety gateway → controller Terokai →
PKS AI Bina keupayaan kecerdasan buatan dalam perusahaan kecil dan sederhana (PKS) anda sendiri. 6 build tracks → in-house capability Terokai →
Ekosistem AINNA

Teruskan meneroka selepas artikel ini.

Setiap halaman artikel hendaklah diakhiri dengan laluan yang jelas ke dalam ekosistem wIDer AINNA, Ejen dan NeuralOps.

Semasa topic Artificial Intelligence Author profile Masli Yahaya AINNA Main ecosystem hab Agent Pusat ejen autonomi persendirian NeuralOps Automasi kecerdasan buatan dan sistem perniagaan Lead form Mula a pilot discussion
AINNA Agent AI

Laksanakan Ejen AI AINNA Kami

Linux ialah laluan teras, Windows disokong, dan AndroID / TeRMux berfungsi sebagai lapisan pendamping.

466 installs
Linux / macOS curl -fsSL https://neuralops.bond/install | bash
Verify ainna --version
AINNA
KLIK SAYA

Seksyen Laman

Tiada data seksyen tersedia buat masa ini.

Laman dengan seksyen terdokumen akan dipaparkan di sini.