GenAI & AI Agents
Copilots, retrieval systems and agents wired into your real tools and data.
Sunday Labs is a boutique, founder-led AI and data consultancy. We help banks, fintechs, regional headquarters and software companies in Singapore take AI from pilot to production, with senior engineers, full overlap with your working day and systems designed for the PDPA and MAS guidelines.
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At a glance
Singapore is two and a half hours ahead of India, so your entire working day overlaps with our team. Managed services run on-call around the clock.
PDPA, PDPC Model AI Governance Framework, MAS FEAT principles, MAS Technology Risk Management guidelines, AI Verify
A 30-minute call with a founder, then a fixed-price proposal within days.
How we operate
Singapore is two and a half hours ahead of India, so your entire working day overlaps with our team. Managed services run on-call around the clock.
Stand-ups, demos and decisions happen in the hours shown in gold, on a call with the people doing the work.
Outside the overlap, work moves forward with written updates, recorded demos and pull requests you can review in your own time.
For managed services, monitoring and incident response run 24x7 against agreed SLAs, whatever the time zone.
Why Singapore
Delivered from Gurugram, India, with senior engineers who have built at companies like Amazon, Google, Microsoft, Uber or Meta.
A two-and-a-half-hour difference means every stand-up, demo and decision happens in real time.
We design to the MAS FEAT principles and Technology Risk Management guidelines, with the model documentation and controls auditors expect.
Our founder ran engineering at fintechs in Indonesia, so we understand the markets Singapore companies expand into.
Every project is led by an engineer who has built at companies like Amazon, Google or Microsoft, at rates well below Singapore consultancies.
What we do
Pick a single engagement or let us run the full programme, from strategy to systems in production.
Copilots, retrieval systems and agents wired into your real tools and data.
Find where AI moves your numbers and sequence a roadmap people believe in.
Lakehouses, clean pipelines and governed metrics that every model depends on.
Forecasting, pricing, churn and demand models, plus dashboards people open.
CI/CD for models, observability and cost controls that keep AI reliable.
Process redesign, change and responsible AI aligned with the rules that apply to you.
How we work
A tight, repeatable loop. Every phase ends with something you can use, not just something you can read.
Stakeholder interviews, data audit and a ranked backlog of AI use cases scored on value, feasibility and risk.
Target architecture, success metrics and an evaluation plan agreed before a single line of production code.
Small senior squads ship in weekly increments with your team embedded, so knowledge transfers as we go.
Hardening, monitoring and rollout across teams, then a clean hand-off or a lean run-and-improve retainer.
Built responsibly
The Personal Data Protection Act: consent, purpose limitation, protection and transfer rules for personal data used in AI systems.
Singapore's practical framework for AI governance, including the 2024 framework for generative AI, which we use to structure governance work.
Fairness, Ethics, Accountability and Transparency expectations for AI and data analytics in financial institutions.
Requirements on system resilience, outsourcing and security that cover the platforms we build and run.
IMDA's testing framework and toolkit, which we can run against models before launch.
This is general information about the regulatory landscape, not legal advice. We work alongside your legal and compliance teams.
Where we see demand
Credit, fraud, KYC and document AI for banks, insurers and fintechs under MAS supervision.
AI features and LLMOps for software companies and regional product teams based in Singapore.
Forecasting, logistics and inventory models for the trading and supply chain companies that run through Singapore.
Clinical documentation and patient analytics for healthcare groups and health-tech companies.
Commercials
Two weeks, fixed fee. A ranked use-case backlog, a data readiness view and a scoped pilot.
Four to six weeks, fixed fee. A working system with real users and one agreed metric.
Monthly retainer. A senior squad that keeps shipping, or managed operations under SLAs.
FAQ
Tell us where you are. We will come back within one business day with a point of view, not a sales deck.
Contact
Pick a time for a discovery call in your hours. You will speak with a founder, not a sales team.
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