Ethical AI Framework Design
Set principles, risk tiers, approval gates, and escalation routes for every model in your inventory.
Typical engagement: 4–6 weeksAI ethics Singapore · governance · compliance
Responsible AI is your competitive moat.
A single biased model decision can cost millions in fines, reputation, and lost contracts. Lorong AI gives boards, CROs, DPOs, and engineering teams a clear way to govern AI before risk becomes an incident.
Request a governance gap analysisPractical AI governance frameworks
Comprehensive governance services, not generic advice.
Each engagement ends with named owners, usable controls, and evidence your board or regulator can review. The work fits your existing product and DevOps processes.
Bias Audits & Fairness Testing
Test protected groups, proxy features, selection effects, and outcome equity in credit, hiring, and care models.
Typical engagement: 3–5 weeksModel Validation & Explainability
Review performance, assumptions, drift controls, explainability methods, and human override procedures.
Typical engagement: 3–6 weeksRegulatory Alignment
Map controls to MAS expectations, PDPA obligations, IMDA guidance, and the risk appetite set by your board.
Typical engagement: 2–4 weeksGovernance Dashboard Build
Give risk teams one view of model inventory, bias alerts, validation status, incidents, and owners.
Typical engagement: 6–10 weeksBoard & Delivery Team Support
Turn policy into decisions with board briefings, control playbooks, and working sessions for product and MLOps teams.
Typical engagement: 1–3 weeksEthical AI audits
What a bias audit actually looks like.
No black boxes. We show how each finding was reached, which group it affects, and what your team can change next.
We agree the decision, users, protected groups, model version, and business threshold under review.
We check missingness, representation, label quality, sampling, and proxy variables before testing outcomes.
We examine how inputs influence decisions and identify features that need removal, restriction, or review.
We compare error rates and approval outcomes across groups using AI Verify and open-source fairness libraries.
You receive ranked fixes, accountable owners, retest dates, and evidence requirements for model validation.
AI compliance consulting
Governance that maps to MAS, IMDA, and your board's risk appetite.
Controls should answer a real question: who can approve this model, what evidence exists, and what happens when performance changes?
| Governance service | MAS alignment | IMDA / AI Verify | PDPA and board evidence |
|---|---|---|---|
| Risk classification | |||
| Bias audit | |||
| Model validation | |||
| Monitoring dashboard |
The crosswalk becomes specific to your sector, model, and control environment. See our financial services work
Fairness health
72%
Last validation: 14 May 2025
Open alerts
04
Credit modelReview
Hiring modelStable
Care triageReview
Model inventory
Validated08
Due this month02
Owner assigned12
Pipeline status
Drift checksOn
Audit trailReady
Escalations02
Oversight without noise
A governance dashboard your CRO will love, not fear.
We connect model inventory, monitoring signals, validation records, and accountable owners to the MLOps tools you already use.
1
Spot drift and fairness alerts before a review meeting.
2
Open the evidence behind every model status.
3
Give engineering a clear remediation queue.
"The dashboard gave our risk team one shared view of model ownership and open actions."
Ragulan Coh, Risk Operations LeadStart with a clear baseline
Don't wait for an audit finding to close your AI governance gap.
Book a 60-minute working session with Lorong AI. We will identify the highest-risk control gaps and outline the next practical steps.