Engineer Production AI Inside the Rules.
Many AI consultancies stop at slide decks. Synthesised.ai ships production-grade systems with eval-loops, governance evidence packs, and Singapore, Australian and New Zealand regulatory context built into delivery.
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AI Development Services Engineered for Production.
Synthesised.ai operates a focused service catalogue for organisations that need to ship generative AI into production rather than experiment with it indefinitely. Each engagement delivers a working system, an eval-set, an observability layer, and a governance evidence pack as a single deliverable.
AI-Powered CMS Development
Build AI inside your CMS without breaking editorial governance. Schema-aware embeddings, editor approval gates, and pre-publish hallucination checks into Webflow, WordPress, Sanity, Contentful and Strapi.
→Custom LLM Application Development
Production-grade LLM applications with eval-loops, telemetry, and rollback paths instrumented at sprint one. The same engineering rigour as classical infrastructure, applied to non-deterministic systems.
→Generative AI Strategy and Consultancy
Strategy work scoped against IMDA AI Verify and Singapore PDPA, with use-case discovery and a governance review scoped into the engagement, not a follow-on consulting engagement.
→AI Workflow Automation
Engineering-grade workflow automation for AU and SG enterprises needing idempotent retries, audit logs, and Privacy-Act-aware data handling beyond no-code agency defaults.
Multi-Agent AI Systems
Production-ready multi-agent systems with step budgets, eval-by-step coverage, and replay logs that guard against the loop and runaway-cost failure modes that stall agentic deployments.
Enterprise AI Deployment and MLOps
Site reliability engineering for non-deterministic systems: drift detection, hallucination monitoring, per-tenant cost attribution, and the dashboards engineering and finance need to share.
Why Most AI Projects Stall Between PoC and Production.
A production LLM application is a microservice with a non-deterministic core. The same eval gates, the same rollback paths, and the same telemetry that engineers expect from classical infrastructure all apply, only the failure modes are new.
Many AI consultancies stop at the demo. Demos pass evaluation by accident. Production passes by discipline.
Synthesised.ai engineers production AI by attaching eval-loops, observability, and governance artefacts to every sprint, so the system that ships is the same system a later audit or tender review examines.
In practice, when you hire Synthesised.ai for an AI build, the system goes live with its own test suite, its own monitoring dashboards, and the governance evidence your procurement and risk teams need to keep it running. None of that arrives later as a separate consulting engagement.
The first risk every enterprise AI project carries is silent quality drift. Every prompt change Synthesised.ai ships is regression-tested against a frozen eval-set before it merges, so a tweak that improves one use case does not quietly break another. Eval-set versioning lives next to the code, not in a wiki nobody reads, and every release pull request includes the diff against the previous eval run.
The second risk is operational blindness once the system is live. Synthesised.ai instruments per-tenant cost attribution, hallucination-rate monitoring, and drift detection at sprint one, not after the first incident report forces it. Engineering and finance see the same dashboards, so a token-budget anomaly is visible the same day it happens, not three weeks later when the bill arrives.
The third risk is the governance evidence pack arriving too late. ISO/IEC 42001 control coverage, NIST AI RMF function alignment, IMDA AI Verify dimension mapping, and Singapore PDPA data-flow diagrams are produced alongside the build. The pack is a deliverable in the engagement, not a follow-on consulting SOW once a tender or an audit forces the question.
Singapore-Headquartered, Active in Australia and New Zealand.
Singapore
Synthesised.ai is registered in Singapore as Synthesised AI Pte. Ltd. under UEN 201634844R, and serves Singapore, Australia, New Zealand and South East Asia. Engagements build to the IMDA AI Verify framework and the Singapore Model AI Governance Framework (second edition), with PDPA-aware data flows applied at training-data ingestion rather than only at user-input time. Bilingual delivery in English and Mandarin is available across scoping, technical artefacts, and governance documentation.
Singapore services →Australia and New Zealand
Synthesised.ai serves organisations in Australia and New Zealand. Australian engagements reference Australia's Guidance for AI Adoption, the Privacy Act 1988 and the Australian Privacy Principles; New Zealand engagements reference the Privacy Act 2020 and its Information Privacy Principles. Cross-jurisdictional engagements, where Singapore, Australian and New Zealand governance evidence travels together, are a specific design goal.
AI in Australia and New Zealand →Engineering-Led. Singapore-Founded. Hands-On.
Kevin Dam founded Synthesised.ai to apply engineering discipline to production generative AI. He builds with AI tools in his own business and applies what works there to client engagements.
The job Synthesised.ai is built for is the one Kevin keeps seeing inside enterprise AI programmes that stall: a working PoC with no eval-set, a deployed system with no observability, a tender opportunity with no governance evidence. Synthesised.ai exists to engineer those gaps closed before they become incidents.
Built to the Frameworks Procurement Teams Check.
Synthesised.ai engagements can produce evidence mapped to the regulatory and engineering frameworks Singapore enterprise and government tenders often reference. Where the studio stands on each framework: Certifications & partnerships
ISO/IEC 42001
The international AI management-system standard, voluntary unless a contract requires it. Engagements can include a control coverage table mapped to lifecycle stages from intent through decommissioning.
NIST AI RMF
A voluntary US framework often referenced in cross-border procurement. An AI RMF function alignment table covering govern, map, measure, and manage.
IMDA AI Verify
Singapore's open-source AI testing toolkit. A per-engagement dimension map across the 11 AI Verify principles, plus the supporting test artefacts.
Privacy law & DISR
Singapore's PDPA and the Australian and New Zealand Privacy Acts are law; Australia's DISR guidance is voluntary. Purpose-mapping registers, data-flow diagrams, and consent maps come before any training-data ingestion begins.
Common Questions Buyers Ask First.
Synthesised.ai is a commercial AI development consultancy, registered in Singapore as Synthesised AI Pte. Ltd. under UEN 201634844R. AI Singapore (AISG) is a government-funded national research programme run from the National University of Singapore. The two are separate entities with separate missions. Buyers occasionally land on either expecting the other, so it is worth naming the difference up front.
No. Synthesised.ai is a production AI consulting studio, registered in Singapore as Synthesised AI Pte. Ltd. under UEN 201634844R, that builds AI systems for client organisations. Synthesized (synthesized.io) is a London company that makes test data software. Synthesise AI (synthesise.ai) is a tool for creating digital products. Synthesis AI (synthesis.ai) is a San Francisco company that generates synthetic data for computer vision. The names are close, so it is worth naming the difference up front.
Big-4 advisory engagements often centre on strategy, ethics frameworks and transformation roadmaps. No-code AI agencies typically ship template automations sized for small businesses. Synthesised.ai sits in the gap between the two and engineers production-grade AI systems with the governance evidence pack baked in. The deliverable is a working system that procurement, engineering, and internal audit or assurance can each evaluate from the same set of artefacts.
Yes. Synthesised.ai serves organisations in Singapore, Australia, New Zealand and South East Asia. Australian engagements reference Australia's Guidance for AI Adoption and the Privacy Act 1988; New Zealand engagements reference the Privacy Act 2020. Engagements elsewhere in South East Asia are scoped case by case against the local data-protection law.
Synthesised.ai publishes no rates: scope and cost are set at the scoping call. As an illustration, a discovery phase can run 2 to 4 weeks and a production build 6 to 12 weeks, including the time to assemble the governance evidence pack. These timelines are illustrative; scope, deliverables, acceptance criteria and timing are agreed for each engagement.
Stop Pretending Your PoC Is Production.
Most AI projects stall because eval-loops, observability, and governance were skipped during the demo. Synthesised.ai engineers them in from sprint one, so the system that ships still holds up when procurement, engineering, and audit or assurance each ask their own questions. Book a discovery call to scope your production-AI engagement.
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