12 Best AI Consulting Firms in Singapore (2026)
Reading time: 34 min | Last updated: 2 October 2026 | By Kevin Dam
The best AI consulting firm in Singapore is the one whose type matches the job you need done: advice on where AI fits in the business, or a working AI system running inside it. Local “best AI consultancy” lists rarely make that split. They place strategy firms, systems integrators, specialist data firms and small build studios in one table, even though each type sells a different output, staffs the work differently and qualifies for different funding. Choosing an AI consultant from a mixed league table works like tendering legal work from a list that mixes litigators and conveyancers: the category decides fit before the name does.
In this guide, we cover what an AI consulting firm actually delivers, why the choice matters for Singapore buyers in 2026, the four firm types you will meet, how AI consulting is funded in Singapore after the September 2026 grant changes, and the features that separate a firm that can ship from one that can only advise. After the buyer education, we review 12 firms with a Singapore AI consulting practice, each in the same structure: what the firm is, its main capabilities, its pricing basis as published in September 2026, the buyer it suits, and what its own documentation or a named third party says about its limits.
What is an AI consulting firm?
An AI consulting firm is a service business that helps an organisation decide where to use artificial intelligence, and then designs, builds, integrates or governs the systems that do it. The word “consulting” covers a wide span. At one end sits pure advice: an assessment of AI readiness, a portfolio of prioritised use cases, a business case and a roadmap. At the other end sits engineering: a team that connects a model to the company’s data, writes the code, tests it against real inputs, puts it into production and monitors it afterwards.
Most engagements in Singapore fall somewhere between those ends, and the useful question for a buyer is where on the span a given firm is strongest. Five jobs account for most of the work:
- Opportunity and readiness assessment. Mapping processes, data and skills to find the use cases where AI earns its cost, and ranking them by value and feasibility.
- Strategy and business case. Turning the ranked use cases into a roadmap with budgets, owners and success measures that a leadership team can approve.
- Build and integration. Designing and engineering the system itself: retrieval over company documents, AI agents that take actions, conversational assistants, document processing, forecasting models, and the integrations that connect them to existing software.
- Governance and risk. Setting the controls around the system: data handling under Singapore’s Personal Data Protection Act (PDPA), human approval for consequential actions, evaluation, logging and incident handling.
- Adoption and change. Training staff, redesigning the process around the new system and measuring whether people use it.
A firm can be excellent at the first two jobs and have no engineers of its own. Another can build quickly and have little to say about operating-model change. Neither is a weakness in itself; it only becomes one when the buyer hires for the wrong job.
Advice, build or both
The simplest way to read any AI consulting proposal is to ask what physically exists at the end of it. If the answer is a document, you have bought advice. If the answer is software that your staff or customers use every day, with someone accountable for keeping it running, you have bought a working system. Both are legitimate purchases. The trouble starts when a buyer who needs a working system receives a roadmap, or when a buyer who needs a board-level plan receives a narrow tool that nobody asked for.
Why the choice matters for Singapore businesses in 2026
AI adoption in Singapore is no longer confined to large enterprises, which is why the consulting market has filled up with firms of very different shapes. According to IMDA’s Singapore Digital Economy Report 2024/2025, AI adoption among Singapore SMEs rose from 4.2% in 2023 to 14.5% in 2024, while adoption among non-SMEs rose from 44.0% to 62.5% over the same period. The same report finds that SMEs using AI apply it across an average of three business functions and non-SMEs across five, with information technology (49%), customer service (43%) and finance and accounting (40%) the most common functions.
Those figures describe two very different buyers. A non-SME running AI across five functions needs coordination, governance and change management across the business. An SME trying AI in its first one to three functions needs a single system that works and pays back. The consulting firms that serve each buyer well are rarely the same firms.
The second reason the choice matters is the gap between a pilot and production. Gartner predicted on 25 June 2025 that over 40% of agentic AI projects will be cancelled by the end of 2027, citing escalating costs, unclear business value and inadequate risk controls. The same release estimates that only about 130 of the thousands of vendors claiming agentic AI capabilities are genuine, and describes “agent washing”: rebranding existing assistants, robotic process automation and chatbots as agentic products. A consulting firm that cannot show evaluation, cost tracking and approval controls on a system it has already shipped is a firm whose projects are more exposed to that failure pattern.
The third reason is that even the largest firms are good at different things. In Forrester’s Q2 2026 evaluation of AI consulting services, which covered ten large providers, the analyst firm concluded that “all 10 providers are great partners for the right situation”, with strengths varying by industry and use case. If that holds among ten global firms of similar scale, it holds more strongly across a Singapore market that runs from ten-thousand-person integrators to founder-led studios.
Advice or a working system: the four firm types in Singapore
Almost every firm that appears on a Singapore AI consulting shortlist belongs to one of four types. Each type sells a different primary output and is bought through a different route.
Management and professional services consultancies sell advice first. Their AI practices assess readiness, build business cases and redesign processes, and many now attach an AI build centre or platform to that advice. They suit leadership teams that need an organisation-wide plan and the governance to go with it.
Systems integrators and cloud partners sell delivery on a platform. They implement AI inside an existing technology estate, often on one cloud provider or one software ecosystem, and they are the natural route for funding programmes that run through cloud providers.
Specialist AI and data firms sell depth in one domain or capability, such as data platforms or AI for regulated financial institutions. They suit buyers with a well-defined problem in that domain.
Build studios sell a working system. They are smaller, founder-led or senior-led teams that scope, build and hand over one production system at a time, typically for SMEs and mid-market firms.
| Firm type | What you buy | Who writes the production code | Typical engagement shape | Funding route most often used | Fits best when |
|---|---|---|---|---|---|
| Management and professional services consultancy | Assessment, roadmap, business case, governance design | An in-house build centre, a partner, or the client’s own team | Multi-phase programme | Direct budget; some activities under enterprise grants | Leadership needs a cross-functional AI plan |
| Systems integrator or cloud partner | Implementation on a named platform or cloud | The integrator’s delivery teams | Platform rollout or managed service | Cloud-provider programmes and credits | The estate is already standardised on one platform |
| Specialist AI and data firm | Deep work in one domain or capability | The firm’s own specialists | Defined build in its domain | Direct budget | The problem sits squarely in the firm’s specialism |
| Build studio | One production system, handed over | The same senior people who scoped it | Single use case to production | Direct budget or enterprise grants | One process needs a working system soon |
The table explains why local rankings mislead. A list that puts a professional services network next to a founder-led studio compares a firm built to run a five-function transformation with a firm built to ship one system. Both can be the “best” answer, for different buyers. For a region-wide view of the same idea, our companion guide groups the best AI consulting firms across APAC by firm type. Singapore AI product companies and development shops, as distinct from consultancies, are assessed in our shortlist of the top AI companies in Singapore by delivery evidence.
One widely ranked list for this search term, for example, places a national AI research programme and an AI platform vendor alongside consultancies (accessed 29 September 2026). Neither sells consulting in the sense a buyer means. Read any list with the firm type in mind before you read the order.
Firms that span more than one type
Some firms genuinely span two types. A professional services network can run its own AI build centre; a build studio can sell short advisory workshops; an integrator can bring a proprietary AI product. That is normal, and it is not a reason to dismiss a firm. The test is which output the firm is strongest at, measured by what it has actually delivered. Ask each firm to describe its last three engagements by output: how many ended in a document, and how many ended in a system still running today. The ratio tells you more about the firm’s type than its website does.
How AI consulting is funded in Singapore in 2026
Funding changes which firm you can hire, so it belongs in the shortlist decision rather than after it. Two routes matter most as of September 2026, and one of them changed this week.
The Enterprise Compute Initiative
The Enterprise Compute Initiative (ECI) is a programme run by Digital Industry Singapore (DISG) that pairs cloud credits and tools with co-funded AI consultancy. According to DISG’s programme page (last updated 8 September 2026), the programme is worth up to S$150 million, and the Government supports 70% of consulting costs, capped at S$105,000 per company, with the company paying the remaining 30%. The consultancy covers minimum viable product development and change management.
The eligibility bar is higher than many buyers expect. The same page lists a Singapore-registered business with at least 10 employees, CEO-level sponsorship, a technical team of two or more engineers, AI specialists or data scientists, prior experience with a custom AI solution, accessible datasets for the proposed use cases, and the financial stability to complete the project.
The detail that matters most for shortlisting sits in the ECI factsheet (updated 10 February 2026). It states that the total supportable consulting cost is capped at S$150,000, that consultant partners are nominated by the participating cloud service providers for their expertise in that provider’s platform, and that on approval “your assigned CSP will get in touch with onboarding information including your assigned Partner”. In practice, an ECI buyer chooses a cloud provider first, and the consulting partner follows from that choice. A buyer set on a particular consultancy needs to check whether that firm is nominated by the relevant cloud provider before applying. Caps and eligibility are as of the dates shown and can change; confirm them with DISG before relying on them.
The EDGE Grant replaces EDG, PSG and MRA
Enterprise Singapore’s EDG page states that the Enterprise Development Grant, the Market Readiness Assistance grant and the Productivity Solutions Grant cease on 29 September 2026, with applications from 30 September 2026 made under the EDGE Grant. Ongoing projects continue to be processed. According to Enterprise Singapore’s EDGE Grant page (accessed 29 September 2026), EDGE spans eight business areas and more than 100 activities, including automation and digitalisation, business strategy and innovation; it supports up to 70% of qualifying costs for SMEs and up to 50% for non-SMEs, with activity-specific levels, and caps total support at S$100,000 per company per year across all activities, refreshed each 1 April. Funding is paid on a reimbursement basis after the project is completed and paid for.
Two practical consequences follow. First, a consultancy’s website that still advertises “PSG-approved” or “EDG-supported” AI packages describes schemes closed to new applications from 30 September 2026, so ask how the firm’s offer maps to EDGE activities. Second, under EDG, Enterprise Singapore required applicants claiming management consultancy costs to engage consultants holding Singapore Accreditation Council-accredited TR 43 or SS 680 certification, per the same EDG page; the page exempted consultants giving technical advice on developing new technology, and solutions vendors. Check whether an equivalent condition applies to the EDGE activity you plan to claim.
| Funding route | Administered by | Support level (as published) | Cap | Who picks the consultant | Check before you shortlist |
|---|---|---|---|---|---|
| Enterprise Compute Initiative | Digital Industry Singapore | 70% of consulting costs | S$105,000 per company (on S$150,000 supportable cost) | Assigned through the participating cloud provider | Is the firm nominated by your cloud provider? |
| EDGE Grant (from 30 September 2026) | Enterprise Singapore | Up to 70% for SMEs, up to 50% for non-SMEs, varies by activity | S$100,000 per company per year across activities | The applicant, subject to activity rules | Which EDGE activity covers the work, and does the firm meet its conditions? |
| Direct budget | The buyer | Not applicable | Not applicable | The applicant | Total cost after handover, not the fee alone |
Governance frameworks buyers will hear about
Singapore’s AI governance instruments are largely voluntary, and a good consultant will say so. The PDPA is law. The Personal Data Protection Commission’s Advisory Guidelines on use of Personal Data in AI Recommendation and Decision Systems are advisory: they explain how the PDPA applies when personal data is used to develop AI systems, how to inform people and obtain consent, and the obligations of third-party AI developers acting as data intermediaries. AI Verify, developed by IMDA and the PDPC with industry participants, is a voluntary testing framework that assesses AI systems against 11 governance principles; it was released as a pilot on 25 May 2022 and updated for generative AI risks on 29 May 2025. ISO/IEC 42001 is a voluntary management-system standard unless a contract requires it; ISO notes that certification is a legal or contractual requirement only in some industries. Be cautious of any proposal that presents a voluntary framework as a legal requirement, or a framework “alignment” as a certification.
What to look for in an AI consulting firm in Singapore
The criteria below separate firms that can deliver the output you need from firms that can only describe it. Weight them according to whether you are buying advice or a working system.
1. Named production references
Ask for two systems the firm has put into production, the client names where consent allows, how long each has run, and who operates it now. A reference that is still a proof of concept is evidence of prototyping skill, not of delivery. Where client names are confidential, ask for the architecture, the go-live month and a reference call.
2. Who writes the code
Many consulting proposals are sold by one team and delivered by another. Ask which named people will scope, build and support the system, how much of their time is allocated, and whether any part of the build is subcontracted. For advice-only work, ask who will implement the roadmap and whether the firm stays involved.
3. Evaluation and monitoring
A production AI system needs a test set of real inputs with expected outputs, a way to rerun it after every change, and monitoring of accuracy, latency and model cost once live. Ask to see an evaluation report and a monitoring dashboard from a past engagement. Firms that cannot show either tend to discover quality problems after launch.
4. Approval controls for AI actions
When an AI system can send a message, change a price, move money or publish content, the question is what it is allowed to do without a person’s approval. Good firms design limits, expiries and audit logs into the system from the start. As one example, Synthesised.ai built a revenue-and-operations platform for a management consultancy in which any AI action touching a live advertising budget or live website needs approval, proposals expire after 15 minutes, budget changes are capped at plus or minus 50%, and every AI-executed action is audit-logged. Ask each firm how its past systems handle the same problem.
5. Data residency and PDPA handling
Ask where prompts, documents, embeddings and logs are stored, which model providers process them, and whether any data is retained or used for training by those providers. For Singapore personal data, ask how the firm’s design reflects the PDPA and the PDPC’s advisory guidelines, and whether a Singapore-region deployment is available if your policies require it.
6. Funding route eligibility
If you intend to use the Enterprise Compute Initiative, the firm must be the partner your cloud provider nominates. If you intend to claim EDGE, the work must map to an eligible activity and the firm must meet that activity’s conditions. Settle this before the tender, not after the proposal.
7. Handover and ownership
Ask, in writing, what you own when the engagement ends: source code, prompts, evaluation sets, infrastructure definitions and documentation. A firm’s own accelerator or platform can shorten delivery, but it also ties the system to that firm unless the licence terms say otherwise.
8. Total cost after handover
A consulting fee is only part of the cost. Model usage, cloud hosting, software licences, monitoring tools and your own staff time continue after the firm leaves. Ask each firm to estimate the monthly running cost of the system it proposes and to show how it measured that cost on a past build.
9. Sector and process references
Firms that have built for your sector know where the data lives, which regulations bite and which processes resist change. Ask for work in your sector or, failing that, in a process that looks like yours: document-heavy operations, customer conversations, forecasting or approvals.
10. Engagement size that fits you
Every firm has a smallest engagement it runs well. A large network’s minimum scope can exceed an SME’s whole budget, while a small studio can lack the capacity for a programme across several countries. Ask for the smallest and largest engagement the firm delivered in the past year.
How to build a shortlist of AI consultants in Singapore
A defensible shortlist takes four steps, and each one removes firms rather than adding them.
Step 1: Decide the output. Write one sentence that describes what exists at the end of the engagement: “a roadmap approved by the board”, “a WhatsApp assistant answering from our product documents”, “an agent that drafts purchase orders for approval”. That sentence tells you the firm type.
Step 2: Decide the funding route. If you plan to use the ECI, start with your cloud provider’s nominated partners. If you plan to claim EDGE, confirm the activity and its conditions. If you are paying directly, you have the widest choice.
Step 3: Shortlist three to five firms of the right type. Use the criteria above, and discard any firm that cannot give you named production references for the kind of output you need.
Step 4: Run a paid discovery or a structured proposal round. Ask each firm the same questions and compare the answers side by side:
- Which two systems like ours have you put into production, and who runs them today?
- Who, by name, will scope, build and support our system?
- How will you evaluate the system before launch, and what will you monitor after?
- What can the system do without a person’s approval, and where is that logged?
- Where will our data be stored and processed, and by which model providers?
- What do we own at handover, and what remains licensed from you?
- What will the system cost to run each month after you leave?
A firm that answers these clearly and in writing is usually the firm that will run the engagement clearly.
The 12 best AI consulting firms in Singapore at a glance
Firms are grouped by type, from advice-led to build-led, and sit alphabetically within each type. The order places each firm between advice and a working system; it does not rank quality. Synthesised.ai publishes this guide and sits in its alphabetical place among the build studios.
| # | Firm | Firm type | Best For | Pricing (source, September 2026) | Check before buying |
|---|---|---|---|---|---|
| 1 | ABeam Consulting | Management consultancy | AI tied to business-process and systems change | No public rate identified as at 30 September 2026 (checked ABeam Singapore) | Ask for South East Asian references and whether a single build without wider process work is in scope |
| 2 | Deloitte | Professional services network | Regulated enterprises running agentic AI with risk and assurance work | No public rate identified as at 30 September 2026 (checked Deloitte South East Asia) | Confirm which Zora AI components are licensed and what transfers at handover |
| 3 | PwC | Professional services network | Financial services, government and logistics firms wanting AI with legal, tax and assurance services | No public rate identified as at 30 September 2026 (checked PwC Singapore AI Hub) | Ask how much of the delivery team sits in Singapore |
| 4 | Accenture | Systems integrator | Multinationals rolling out AI across several markets | No public rate identified as at 30 September 2026 (checked Accenture newsroom) | Confirm where your firm sits against the US$300 million to US$3 billion revenue band of its Accenture Edge offer |
| 5 | Digigen | Cloud partner | Businesses adopting AI inside Google Cloud or Microsoft | No public rate identified as at 30 September 2026 (checked Digigen) | Ask for production references and whether custom model development is in scope |
| 6 | NCS | Systems integrator | Government agencies and large enterprises | No public rate identified as at 30 September 2026 (checked NCS) | Confirm which components are NCS products and how they are licensed |
| 7 | Total eBiz Solutions (Avanade) | Systems integrator | Singapore organisations standardised on Microsoft | No public rate identified as at 30 September 2026 (checked TeBS) | Ask for references on your platforms if your estate runs outside Microsoft |
| 8 | Artefact | Specialist data and AI firm | Enterprises that want AI built on a stronger data foundation | No public rate identified as at 30 September 2026 (checked Artefact) | Ask whether a narrow, build-only scope is available if your data is already in order |
| 9 | Neurons Lab | Specialist AI firm | Banks, insurers and wealth managers | No public rate identified as at 30 September 2026 (checked Neurons Lab) | Confirm it takes work outside financial services, where its site places its focus |
| 10 | 41 Labs | Build studio | SMEs automating sales conversations, quotes or documents | Projects from about S$10,000 (per 41 Labs) | Its own guide says it is not the right fit for multi-department transformation with formal audit oversight |
| 11 | OTG Lab | Build studio and software house | SMEs and institutions wanting workshops plus grant-supported builds | No public rate identified as at 30 September 2026 (checked OTG Lab) | Confirm whether the production build is a separate engagement from the blueprint |
| 12 | Synthesised.ai | Build studio | Mid-market firms and consultancies needing one governed AI system in production | Scoped per enquiry (no public rate card) | Look elsewhere for strategy-only engagements or multi-country transformation programmes |
Reviews of the 12 best AI consulting firms in Singapore
1. ABeam Consulting
ABeam Consulting is a Tokyo-headquartered, process-led management consultancy suited for organisations that want AI delivered as part of wider business-process and systems change. It operates in Singapore through ABeam Consulting (Singapore) Pte. Ltd. and ABeam Analytics Pte. Ltd. at Cross Street, and its company profile gives a group headcount of 9,632 as of 1 April 2026, 32 offices as of 19 February 2026 and a founding date of 1 April 1981.
Top features
- Generative AI Starter App for identifying efficiency use cases (ABeam)
- LLM implementation and internal knowledge search systems (ABeam)
- AI governance consulting and AI talent training (ABeam)
- Demand forecasting and explainable AI implementation support (ABeam)
Pricing: No public rate identified as at 30 September 2026 on ABeam’s Singapore AI services page.
Best for: Organisations that want AI introduced alongside process redesign and systems implementation.
How does it compare? The case studies referenced on ABeam’s Singapore AI services page (accessed 30 September 2026) are mostly Japanese organisations, including LIXIL, NEC and Kao Corporation. Check before buying: ask for South East Asian references.
2. Deloitte
Deloitte is a multidisciplinary, assurance-anchored professional services network suited for regulated enterprises that want agentic AI run alongside risk and assurance work. Deloitte launched its Asia Pacific Agentic AI Centre of Excellence from Singapore on 3 June 2025, with more than 120 AI specialists and more than 6,000 practitioners across the region, and a stated regional pipeline of AI implementations above US$1 billion.
Top features
- Agentic AI Centre of Excellence run from Singapore (Deloitte, 3 June 2025)
- Zora AI platform, which Deloitte states is built on NVIDIA AI (Deloitte)
- Trustworthy AI principles applied to implementations (Deloitte)
- Functional focus on finance, procurement, and sales and marketing (Deloitte)
Pricing: No public rate identified as at 30 September 2026 in Deloitte’s release.
Best for: Regulated enterprises in Asia Pacific that want agentic AI and assurance from one network.
How does it compare? Deloitte’s own release describes the centre’s delivery around its Zora AI platform. Check before buying: confirm which components are licensed from Deloitte and what transfers at handover.
3. PwC
PwC is a global, assurance-led professional services network suited for financial services, government and logistics organisations that want AI delivered with legal, tax and assurance services. According to Singapore EDB’s release, the PwC network committed over US$4 million over three years to an AI Hub in Singapore, including an “AI factory” for financial services, government and logistics, and collaboration with the National University of Singapore. PwC states that it was named a Leader in The Forrester Wave: AI Consulting Services, Q2 2026.
Top features
- AI factory approach for scaling repeatable use cases (PwC Singapore AI Hub)
- Generative AI literacy workshops (PwC Singapore AI Hub)
- Responsible AI frameworks for AI use and data governance (PwC Singapore AI Hub)
- Legal generative AI for contract analysis (PwC Singapore AI Hub)
Pricing: No public rate identified as at 30 September 2026 on the PwC Singapore AI Hub page.
Best for: Financial services, public sector and logistics organisations wanting AI connected to legal, tax and assurance advice.
How does it compare? According to the EDB release, the Singapore hub’s team numbered 15 AI researchers and data scientists in May 2025, with a target of 20. Check before buying: ask how much of the delivery team for your build sits in Singapore.
4. Accenture
Accenture is a global, delivery-scale systems integrator built for multinationals rolling AI out across several markets and platforms. Accenture announced an AI Refinery Engineering Hub in Singapore on 26 November 2024, extending its Center for Advanced AI in Singapore as part of a US$3 billion global AI investment, to research, develop and deploy custom models for sectors including healthcare, financial services and the public sector. Its fiscal 2025 results (25 September 2025) reported US$5.9 billion of generative AI new bookings.
Top features
- AI Refinery Engineering Hub in Singapore (Accenture, 26 November 2024)
- Custom model development and deployment (Accenture)
- Applied research across healthcare, financial services, public sector, energy and sustainability (Accenture)
- Accenture Edge unit for mid-market firms (Accenture, 23 June 2026)
Pricing: No public rate identified as at 30 September 2026 in Accenture’s releases.
Best for: Multinationals that need AI delivered across several countries and platforms at once.
How does it compare? Accenture’s launch of Accenture Edge (23 June 2026) defines its mid-market offer around companies with annual revenue between US$300 million and US$3 billion, so check before buying: a smaller Singapore firm can ask which Accenture offer, if any, covers a company of its size.
5. Digigen
Digigen is a young, cloud-partner consultancy suited for businesses adopting AI inside Google Cloud or Microsoft environments. Its about page states that it was established in 2023 by cloud specialists, with a Bangkok head office and a Singapore office, and that it is a certified Google Cloud Partner and a Microsoft Solutions Partner. Its homepage lists Google Gemini and Microsoft Copilot integration, workflow automation and AI agents.
Top features
- Google Gemini and Microsoft Copilot integration (Digigen)
- Workflow automation and orchestration (Digigen)
- AI agents through its Agentiv division (Digigen)
- Cloud migration and managed support (Digigen)
Pricing: No public rate identified as at 30 September 2026 on Digigen’s site.
Best for: Businesses on Google Cloud or Microsoft that want AI switched on inside those tools.
How does it compare? Digigen’s own about page dates the firm to 2023, and its homepage lists assistant integration, workflow automation and agents. Check before buying: ask for production references and whether custom model development is in scope.
6. NCS
NCS is a large, government-experienced technology services provider suited for public agencies and large enterprises running AI across complex estates. Part of Singtel, NCS states that it employs more than 15,000 people across Singapore, Australia, China, India and the Philippines and manages about 4,000 active projects. On 9 July 2026 it expanded its Sunshine.AI suite and announced plans, with Digital Industry Singapore, to hire more than 130 AI practitioners over three years.
Top features
- Sunshine.core platform for building and running AI agents (NCS, 9 July 2026)
- Sunshine.guardian AI governance engine (NCS)
- Sunshine.builder no-code tool (NCS)
Pricing: No public rate identified as at 30 September 2026 on NCS’s site.
Best for: Government agencies and large enterprises with legacy systems and many existing vendors.
How does it compare? NCS’s July 2026 release centres its AI offer on its own Sunshine.AI products. Check before buying: confirm which components are NCS products and how they are licensed.
7. Total eBiz Solutions (Avanade)
Total eBiz Solutions is an established, Microsoft-focused systems integrator suited for Singapore organisations standardised on the Microsoft stack. Founded in Singapore in 2003, TeBS joined Avanade when the acquisition completed on 30 September 2025, with more than 200 professionals moving across, according to TeBS’s announcement. Its website lists AI and machine learning, automation, data and Microsoft business applications.
Top features
- AI and machine learning solutions (TeBS)
- Robotic process automation (TeBS)
- Dynamics 365 and Power Platform delivery (TeBS)
- Data analytics and engineering (TeBS)
Pricing: No public rate identified as at 30 September 2026 in TeBS’s announcement.
Best for: Singapore organisations that want AI built into Microsoft 365, Dynamics or Power Platform.
How does it compare? TeBS’s announcement positions the combined business around Microsoft technologies. Check before buying: organisations running other cloud or software ecosystems can ask for references on those platforms.
8. Artefact
Artefact is an international, data-led AI consultancy suited for enterprises that want AI use cases built on a stronger data foundation. Its website (accessed 30 September 2026) describes data and AI consulting across the value chain, from strategy and data foundations to customer-facing and operational AI, and its offices page lists 36 offices in 27 countries, including Singapore, with its head office in Paris.
Top features
- AI and data strategy (Artefact)
- Data foundations and platforms (Artefact)
- Customer-facing and operational AI use cases (Artefact)
- Sector work across retail, financial services, healthcare and telecommunications (Artefact)
Pricing: No public rate identified as at 30 September 2026 on Artefact’s site.
Best for: Enterprises whose AI plans depend on fixing data platforms first.
How does it compare? Artefact’s own site frames its work from data strategy and data foundations upwards. Check before buying: a buyer with clean data and one narrow automation can ask whether a build-only scope is available.
9. Neurons Lab
Neurons Lab is a focused, regulation-aware AI specialist designed for banks, insurers and wealth managers. Its website (accessed 30 September 2026) describes AI training programmes and custom agentic AI systems for financial institutions, lists offices in London and at Raffles Quay in Singapore, and shows clients including HSBC and Visa. The firm announced on 2 June 2026 that it had achieved the AWS AI Competency in the Agentic AI category.
Top features
- Custom AI agents for financial institutions (Neurons Lab)
- AI training across leadership, technical and non-technical teams (Neurons Lab)
- Work across retail, corporate and private banking, insurance and wealth (Neurons Lab)
- AWS AI Competency in Agentic AI (Neurons Lab, 2 June 2026)
Pricing: No public rate identified as at 30 September 2026 on Neurons Lab’s site.
Best for: Banks, insurers and wealth managers wanting a financial-services build specialist.
How does it compare? Neurons Lab’s site describes its work as serving financial institutions; buyers in other sectors can confirm whether it takes their work.
10. 41 Labs
41 Labs is a founder-led, build-focused AI studio designed for Singapore SMEs automating one high-value workflow. Its homepage describes custom AI systems for quoting, document processing, customer service and workflow automation, and a WhatsApp sales agent product, and states that its founder has delivered about 50 AI projects. Its guide to AI consulting in Singapore states that the person who scopes a project builds it, and that projects run 4 to 8 weeks from scope to live.
Top features
- Custom AI systems trained on client data (41 Labs)
- WhatsApp AI sales agent, offered as a managed service (41 Labs)
- Quote and document processing automation (41 Labs)
- Founder-led scoping and build (41 Labs)
Pricing: Custom projects from about S$10,000, per 41 Labs; its managed sales agent is listed from $690 a month on its homepage (September 2026).
Best for: SMEs automating one sales, quoting or document workflow with a small senior team.
How does it compare? 41 Labs’ own guide states that it is not the right fit for transforming ten departments at once with formal audit oversight.
11. OTG Lab
OTG Lab is a broad, grant-oriented software and AI house suited for SMEs and institutions that want workshops, training and builds from one Singapore vendor. OTG Lab Pte Ltd (UEN 201939004C) states that it has more than 80 specialists and more than 2,000 clients, and offers software, AI, agentic AI, chatbot, IoT and training services. Its AI consulting service runs as three sprints: discovery and process mapping, solution design and architecture, and an implementation blueprint.
Top features
- Structured AI consulting workshops in three sprints (OTG Lab)
- AI, agentic AI and chatbot development (OTG Lab)
- AI training courses (OTG Lab)
- Vendor listings under several government funding schemes (OTG Lab)
Pricing: No public rate identified as at 30 September 2026 on OTG Lab’s consulting page, which advertises “up to 50% funding”.
Best for: SMEs and institutions wanting training, a workshop-led plan and a build from one vendor.
How does it compare? OTG Lab’s consulting page ends the consulting service at an implementation blueprint, so confirm whether the build is a separate engagement; its homepage references PSG and EDG, which Enterprise Singapore closes to new applications after 29 September 2026.
12. Synthesised.ai
Synthesised.ai is a build-led, production-focused AI studio designed for Singapore businesses that need a working AI system rather than a strategy report. Synthesised AI Pte. Ltd. (UEN 201634844R) is headquartered in Singapore and serves Singapore, Australia, New Zealand and South East Asia. It builds custom AI systems to production, including agents, conversational AI, integrations, generative AI solutions and workflow automation, and advises on AI adoption along the way. Its delivery follows one practical approach, adapted to the business and use case: discover, prototype, productionise, with evaluation, observability and governance controls agreed for each engagement. Because Synthesised.ai built the systems below, it can describe them in more detail than the other firms.
For a Singapore-based digital-marketing and content-production operation serving a multi-brand roster across APAC, Synthesised.ai built LLM MediaOS: a multi-tenant, white-label, node-based AI workflow platform that runs keyword research, LLM-drafted briefs and scripts, image generation and video generation in one visual workflow, with branded workspaces, a credit-metered model gateway, and its database and application servers in the Singapore region (AWS ap-southeast-1). The client reports about 5 hours saved per finished content piece and about an 80% reduction in production time.
For a management consultancy advising local service businesses, it built Perispark, a revenue-and-operations platform with ad-platform connections, a conversational ads analyst over a deterministic metric layer, and approve-before-execute governance for any AI action touching a live budget or live site. The client reports about 200 consultant hours returned per month across a 20-client roster and 5 to 10% of managed ad spend recovered. For another consultancy, RefinedAI runs scheduled AI-visibility checks across ChatGPT, Claude, Gemini and Perplexity with per-check prompt, model and response fingerprints; the client reports that a 40-check sweep across four assistants runs unattended for about US$0.78 in model costs. The full write-ups sit in the case studies.
Synthesised.ai builds to ISO/IEC 42001 practices and handles data in a PDPA-aware way; its framework and certification status is set out on the certifications and partnerships page. It works with models from several providers, including Anthropic and Google, and holds no partner tier with either. Founder Kevin Dam builds with AI tools in his own business and applies what works to client engagements.
Its work to date is build-led. A pure strategy-only engagement is not its track record, and a buyer who wants a roadmap without a build is better served by the advice-led firms above.
Top features
- Production builds. Systems are scoped to reach production with the client’s data and users, not to end at a demonstration.
- Approval controls on AI actions. Agents that touch live budgets or live sites can be designed with expiring proposals, change caps and audit logs, as in Perispark.
- Multi-tenant AI platforms. White-label workspaces, metered model access and hosting in the Singapore region, as in LLM MediaOS (database and application servers in AWS ap-southeast-1).
- Conversational AI grounded in supplied documents. Relay unifies WhatsApp, Slack and Gmail into one CRM view, answers on WhatsApp from supplied documents and hands over to a person when the answer is not in them; email replies are planned rather than live.
- Reproducible AI monitoring. Prompt, model and response fingerprints make each check repeatable, as in RefinedAI.
- Evaluation and observability agreed per engagement. Test sets, logging and monitoring are settled with the client for each build.
- Founder-built agentic systems. Kevin Dam built and runs multi-step AI agents in production at Aemorph, his related search-visibility agency, including a content-architecture pipeline and an agent that orchestrates other agents.
- Advice attached to the build. Use-case selection and adoption guidance are delivered by the team that builds the system.
Pricing: Synthesised.ai does not publish a rate card; fees are scoped through an enquiry.
Best for: Singapore mid-market firms and consultancies that need one AI system built, governed and running in production.
How does it compare? Not built for strategy-only engagements or for enterprise-wide transformation programmes across several countries; buyers who need either are better served by the professional services networks and integrators above.
How to choose the right AI consulting firm in Singapore
Decision framework
| Question | If yes, shortlist | If no, shortlist |
|---|---|---|
| Is the output a plan or roadmap rather than software? | Management consultancies and professional services networks | Integrators, specialists or build studios |
| Will you use the Enterprise Compute Initiative? | Your cloud provider’s nominated partners | Any firm type |
| Is your estate standardised on one platform or ecosystem? | Integrators and cloud partners for that platform | Specialists or build studios |
| Is the problem specific to a regulated sector such as banking? | Sector specialists or professional services networks | Generalist integrators or build studios |
| Do you need one system in production within a quarter or two? | Build studios and specialist firms | Larger firms with programme structures |
| Will AI take actions in live systems (payments, prices, publishing)? | Firms that can show approval controls on a past build | Any firm that meets your other criteria |
| Is the rollout across several countries at once? | Global integrators and networks | Regional firms and build studios |
Guidance by role
For CEOs and managing directors: decide the output first and hold the firm to it. If you need a working system, ask to meet the people who will build it before you sign.
For CFOs: compare total cost after handover, not the fee. Confirm the funding route early: ECI partners are assigned through the cloud provider, and EDGE claims are reimbursed after completion and payment, which affects cash flow.
For CTOs and heads of IT: test evaluation, monitoring, data residency and ownership of code and prompts. Ask for an architecture diagram of a live system similar to yours.
For heads of operations: insist on a named process owner, a baseline measure taken before the build and a plan for how staff will use the system on day one.
For risk and compliance leads: ask how the design reflects the PDPA and the PDPC’s advisory guidelines, what the system is allowed to do without approval, and where every AI action is logged. Treat AI Verify and ISO/IEC 42001 as voluntary frameworks unless a contract requires them.
Implementation trade-offs
Every choice here trades one strength for another. Larger firms bring breadth, sector benches and governance depth, at the cost of programme overhead and minimum engagement sizes that can exceed an SME budget. Build studios bring speed and continuity, because the people who scope the work also build it, at the cost of capacity for multi-country programmes. Platform-aligned integrators shorten delivery and unlock cloud-provider funding, at the cost of tying the system more closely to one ecosystem. Funding lowers the price, but it also shapes the choice: the ECI assigns a partner through the cloud provider, and EDGE reimburses after the fact. Decide which trade-off you can live with before you read proposals, and the shortlist narrows itself.
What to expect in the first 90 days
Whatever firm type you choose, expect the first three months of an engagement to produce evidence rather than slides. In the first month, expect an agreed use case, a named process owner, a baseline measure of the current process and access to the data the system will use. In the second month, expect a working prototype tested against real inputs, with the evaluation set written down so it can be rerun. In the third month, expect either a decision to move to production, with running costs estimated and approval controls designed, or a clear reason to stop. A firm that cannot describe its first 90 days in these terms before you sign is unlikely to run them that way after.
Frequently asked questions
What does an AI consultant do in Singapore? An AI consultant helps an organisation find where AI earns its cost, then plans, builds, governs or supports the systems that deliver it. Some firms stop at the plan; others build and hand over the software. Ask what exists at the end of the engagement.
How much does AI consulting cost in Singapore? Most larger firms reviewed here publish no rate card (as at 30 September 2026). Some smaller studios publish starting points, such as projects from about S$10,000. Funding can reduce the cost: the Enterprise Compute Initiative co-funds 70% of consulting costs up to S$105,000 per company, and the EDGE Grant supports up to 70% of qualifying costs for SMEs, subject to activity rules and caps.
Which cloud providers take part in the Enterprise Compute Initiative? DISG’s FAQ (last updated 8 September 2026) lists three participating cloud providers: Google Cloud, Microsoft and Amazon Web Services. The earlier ECI factsheet (10 February 2026) also named Oracle, so confirm Oracle’s current status with DISG before relying on it. Each provider nominates consultant partners for its own platform, and the partner is assigned after approval.
Can I still apply for PSG or EDG for an AI project? Not for new applications after 29 September 2026. Enterprise Singapore states that EDG, MRA and PSG cease on that date, with new applications made under the EDGE Grant from 30 September 2026. Projects already under way continue to be processed.
Is AI Verify or ISO/IEC 42001 compulsory in Singapore? No. AI Verify is a voluntary testing framework, and ISO/IEC 42001 is a voluntary management-system standard unless a contract requires it (ISO on certification). The PDPA is law: organisations must assess their PDPA obligations when they collect, use or disclose personal data in Singapore, subject to the Act’s scope and exceptions. According to the PDPC’s overview of the PDPA, its data protection provisions do not apply to individuals acting in a personal or domestic capacity, employees acting in the course of their employment, or public agencies, and they exclude business contact information.
Should I hire a large firm or a small AI studio? Hire a large firm when the work spans many functions or countries and needs a governance programme. Hire a smaller studio when one process needs a working system and you want the same people to scope and build it.
How long does an AI consulting engagement take? It depends on the output. An assessment or roadmap is shorter than a production build, and a multi-country programme runs longest. Ask each firm for the duration of a comparable past engagement, measured to go-live rather than to the end of the proposal.
Before you tender
A short, well-typed shortlist saves more time than a long, mixed one. Decide whether you are buying advice or a working system, settle the funding route, and ask every firm the same questions about production references, evaluation, approvals, data and ownership. The right firm will be the one whose answers match the output you described in your first sentence.
We hope this guide helps you shortlist with confidence. If your priority is a working AI system and you want to talk through a use case, you can start a scoping conversation about AI consulting.
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