Research support built on method, not assumption
We founded Novarc Labs to fill a specific gap — the space between standard AI consulting and academic research, where applied work lives.
Back to HomeHow Novarc Labs came to exist
Novarc Labs was established in Singapore in 2019 by a group of researchers and applied scientists who had spent years observing the same pattern: organisations with serious AI research questions were being underserved by both sides of the market. Standard consulting firms approached AI as a deployment exercise. Academic institutions moved at a pace and in a register that did not suit operational contexts.
The work we do sits in the space between those two. We engage with organisations that have a defined research question — something specific, bounded, and intellectually demanding — and provide structured support through the methodological stages of that work. We are not a software development shop, and we are not a think tank. We are a small, selective practice that treats research process as a craft.
Our work is based in Singapore, and we primarily serve organisations operating in the region — though the nature of research means we frequently engage with literature, datasets, and collaborators well beyond these borders. We are familiar with the particular data environments, regulatory contexts, and institutional cultures that shape AI research in Singapore and across Southeast Asia.
To support organisations pursuing meaningful AI research with the same rigour and honesty we would apply to our own work.
The people who do the work
Dr. Jonathan Lim
Principal Research LeadJonathan leads applied research engagements across NLP and structured data domains, with prior experience at A*STAR and the National University of Singapore.
Sarah Chen
Research Design & MethodologySarah specialises in evaluation methodology and experimental design for AI systems, with a background in cognitive science and applied statistics.
Rohan Nair
Literature & Landscape AnalysisRohan manages structured literature reviews and technology landscape reports, bringing a systematic approach drawn from his background in information science and research synthesis.
How we hold ourselves to account
Methodological transparency
We document every methodological choice and the reasoning behind it. Clients receive a clear account of how conclusions were reached, not just what they were.
Confidentiality by default
All client research questions, data, and findings are treated as confidential. We do not reference or build on client work in other engagements without explicit agreement.
Peer-reviewed standards
Research outputs are structured and reviewed to a standard consistent with academic peer review — clear claims, cited evidence, and honest acknowledgement of uncertainty.
Ethical AI research practice
We follow Singapore's Model AI Governance Framework and relevant international standards. Where research raises ethical dimensions, we surface them proactively in our work.
Data protection compliance
We comply with the Personal Data Protection Act (PDPA) 2012 in all data handling activities and advise clients on relevant obligations where research involves personal data.
Clear communication throughout
We flag issues, constraints, and unexpected findings promptly rather than resolving them silently. Clients are kept informed at each stage of the engagement.
Applied AI research support across Singapore's knowledge economy
Singapore's position as a regional hub for technology, finance, and life sciences creates a distinctive context for AI research — one where methodological quality, regulatory awareness, and practical applicability must coexist. Novarc Labs operates within this context, working with corporate R&D functions, government agencies, and research institutes across the city-state.
Our work spans several applied AI domains: natural language processing for business intelligence and document analysis, machine learning evaluation methodology for operational systems, AI landscape analysis for strategic and procurement purposes, and research design for novel problem contexts where standard frameworks require adaptation.
We hold no proprietary platform or software interest. Our recommendations are shaped entirely by the research question and the evidence we find — not by product alignment or commercial partnership. This independence is, we believe, fundamental to the value of what we offer.
Interested in working together?
Reach out to start a conversation about your research question. We'll respond within one business day.
Contact Novarc Labs