// Solutions

Three NLP Solutions. One Coherent Methodology.

Each solution addresses a distinct language processing challenge. They share a common approach — domain-specific training, multilingual capability, and integration built in from the start.

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// Approach

How We Approach Every Engagement

Before any model is trained, we invest time in understanding your language environment. This scoping work shapes everything that follows.

Discovery

Map your language data, use cases, integration points, and success criteria before any building begins.

Data Preparation

Structure, clean, and annotate your domain data. Provide guidance on collection where data is limited.

Training & Evaluation

Train models on your data, evaluate rigorously on held-out sets, and share results before delivery.

Integration & Handover

Connect the system to your environment, document thoroughly, and ensure your team can operate it confidently.

// Solution 01

Custom Language Model Development

Building tailored NLP models for specific business applications, including text classification, named entity recognition, and intent detection. The process involves domain-specific data collection guidance, model architecture selection, training, and integration support. Suitable for organisations with unique language processing needs in Bahasa Malaysia, English, or multilingual contexts.

// example transformation

input → "Aduan pelanggan: sistem tidak berfungsi sejak semalam"

↓ intent_classifier · entity_extractor

output → intent=complaint, entity=system, time_ref=yesterday, lang=ms

What's included:

Domain data collection guidance and structuring
Model architecture selection and justification
Fine-tuning on your domain vocabulary and patterns
Evaluation report on held-out domain data
Integration support and deployment documentation

Typical process steps:

1.Discovery call and language environment mapping
2.Data audit and collection plan
3.Architecture selection and training run
4.Evaluation, feedback, and iteration
5.Integration, documentation, and handover

RM 9,000

Scope-based fixed price

Enquire About This Solution

// Well suited for

Customer support ticket classification and routing
Internal helpdesk intent detection in Bahasa Malaysia
Named entity recognition in regulatory or legal domains
Multilingual chatbot understanding layers

// Well suited for

Brand perception monitoring across Malaysian social media
Customer feedback analysis from surveys and reviews
Internal employee communication sentiment tracking
News and media coverage topic extraction

// Solution 02

Sentiment & Text Analysis Platform

Development of sentiment analysis and text mining tools that process customer feedback, social media content, and internal communications. The service includes data pipeline setup, model calibration for local language nuances, and delivery of a structured reporting interface. Helpful for brands and organisations monitoring public perception.

// example transformation

input → "Servis ok tapi tunggu lama sangat, tak berbaloi"

↓ sentiment_pipeline · topic_extractor

output → sentiment=negative, topic=wait_time, aspect=value, score=-0.61

What's included:

Full data ingestion pipeline setup
Sentiment and topic model calibration for Malaysian language
Structured reporting interface (dashboard or export format)
Handling of Bahasa Malaysia, English, and mixed-language inputs
Documentation and integration support

Typical process steps:

1.Source data audit and channel mapping
2.Pipeline design and ingestion setup
3.Model training and language calibration
4.Reporting interface development
5.Review, adjustment, and handover

RM 5,500

Scope-based fixed price

Enquire About This Solution

// Solution 03

Document Understanding & Extraction

Implementation of AI-powered document processing systems that extract structured information from unstructured text documents such as contracts, invoices, and regulatory filings. Services cover template analysis, extraction model training, and integration with existing document management workflows.

// example transformation

input → purchase_order_march2026.pdf (8 pages, unstructured)

↓ extraction_model · template_mapper

output → {vendor, amount, po_number, due_date, line_items[]}

What's included:

Template analysis across your document types
Extraction model training on your actual documents
Structured output in JSON or your preferred format
Integration with existing document management workflows
On-premise deployment option for sensitive document environments

Typical process steps:

1.Document type inventory and template analysis
2.Extraction schema design with your team
3.Model training and accuracy benchmarking
4.Edge case review and correction
5.Workflow integration and handover

RM 4,200

Scope-based fixed price

Enquire About This Solution

// Well suited for

Automated invoice and purchase order data entry
Contract review and key clause extraction
Regulatory filing information extraction
Onboarding document processing and verification

// Compare Solutions

Choosing the Right Solution

Not sure which solution fits your situation? This comparison may help. You're also welcome to get in touch and we'll talk through it.

Feature	Language Model	Sentiment Platform	Doc Extraction
Works with unstructured text
Bahasa Malaysia support
Structured output / reporting
Intent / classification focus		Partial	—
Perception / sentiment analysis	—		—
Document / file processing	—	—
On-premise deployment option
Starting price	RM 9,000	RM 5,500	RM 4,200

// Shared Standards

Technical Standards Across All Solutions

Privacy & Data Handling

Data handling agreements in place before any project begins. On-premise deployment available. Explicit data retention policies for all client material.

Evaluation & Reporting

Every system is evaluated on held-out domain data. Pre-delivery evaluation reports cover performance metrics and known limitations.

Integration Support

Integration to your existing systems is included in scope. REST API, batch file, or direct database connection — whichever fits your environment.

Documentation

Technical documentation, user guides, and maintenance notes accompany every delivery. Written so your team can operate and evaluate the system independently.

Post-Delivery Support

Structured maintenance options available. Language models may need recalibration as your data evolves — we support that on an ongoing basis.

Malaysian Language Standard

All systems are validated against Malaysian language use — including Bahasa Malaysia formal and informal registers, Malaysian English, and common code-switching patterns.

// Next Step

Not sure which solution fits?

That's a reasonable place to start. Get in touch and we'll discuss your language processing situation honestly — and tell you which approach, if any, makes sense for it.

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