Our Mission

AI That Supports, Not Replaces

We build artificial intelligence systems designed to work alongside human expertise, offering structured insights and data-backed support for complex decisions.

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Our Story

Iridael was founded in 2021 by a small team of data scientists and software engineers who had worked across finance, healthcare, and legal sectors in Singapore. We noticed a pattern: many organisations wanted to use AI but felt uncertain about how to integrate it without disrupting their existing workflows or expertise.

Rather than building systems that promised to automate entire processes, we chose a different path. We focus on creating tools that present structured information, surface relevant patterns, and quantify uncertainty — all while keeping human judgment at the center of important decisions.

Our name, Iridael, comes from the idea of iridescence — the way light reveals different perspectives depending on the angle. Similarly, we believe AI should illuminate data from multiple angles, helping decision-makers see patterns they might have missed while respecting their domain expertise.

Today, we work with organisations across legal, pharmaceutical, financial, and publishing sectors, helping them process complex text data, recognise domain-specific entities, and curate large content repositories. Each project starts with understanding your specific terminology, workflows, and decision-making contexts before we write a single line of code.

Our Team

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Li Wei Chen

Lead Data Scientist

Li Wei specialises in natural language processing and has developed entity recognition systems for legal and pharmaceutical clients across Southeast Asia.

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Ravi Nagarajan

Solutions Architect

Ravi designs integration approaches for AI systems, ensuring new tools work smoothly within existing operational workflows and infrastructure.

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Maya Tan

Client Engagement Lead

Maya manages client relationships and ensures project deliverables align with organisational needs and expectations throughout the engagement.

Our Approach to Quality

We follow established practices for responsible AI development and maintain clear communication throughout each engagement.

Data Privacy Standards

We follow Singapore's Personal Data Protection Act and can work within your existing security frameworks. Your data remains on your infrastructure unless cloud deployment is specifically requested.

Model Performance Documentation

All deliverables include performance metrics, evaluation methodologies, and documentation of model limitations. We explain what the system can and cannot do with appropriate context.

Continuous Calibration

We provide retraining workflows and documentation for ongoing model updates. As your data or requirements evolve, you can refine the system or engage us for support.

User-Centered Design

We involve end users in interface prototyping and validation. Systems should be intuitive for your team, regardless of their technical background.

Transparent Methodology

We explain our modeling choices, data processing steps, and evaluation criteria in clear language. No black boxes — you should understand how the system reaches its outputs.

Ethical AI Principles

We design systems that respect human agency and expertise. Our tools surface information and patterns but leave judgment and decision-making authority with your team.

Working With Us

Each engagement begins with a consultation where we discuss your current workflows, information gaps, and decision-making contexts. We want to understand not just what you need the system to do, but how it will fit into your team's existing practices.

From there, we move into domain learning. For entity recognition projects, this means studying your terminology and annotation guidelines. For decision support systems, it involves mapping your decision processes and identifying relevant data sources. For content curation, we explore your taxonomy and user needs.

Development includes regular check-ins where we share progress, gather feedback, and refine our approach. We believe in iterative collaboration rather than delivering a finished product at the end without your involvement along the way.

Deployment includes training for your team, clear documentation, and a handover period where we ensure everyone is comfortable using the new system. We can provide ongoing support contracts if you'd like assistance with model refinement or system updates.

Our goal is to build something useful that your team actually adopts, not impressive technology that sits unused because it doesn't fit how you actually work.

Interested in Learning More?

We'd be happy to discuss your needs and explore whether our approach might be a good fit for your organisation.

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