10 Best AI Development Companies in Singapore (2026)

Singapore is where much of Southeast Asia buys its AI. Regional headquarters, banks and insurers sit on one island, the government publishes practical AI governance tools instead of only principles, and the talent pool draws from across Asia. The result is a crowded market: AI product companies, enterprise AI studios, global consultancies with regional hubs, and hundreds of agencies that list "AI development" next to web design.

Most published "top AI companies in Singapore" lists are written by vendors that rank themselves first, and several of the companies they include do not deliver from Singapore at all. Buyers need to sort four kinds of supplier: platform companies you license, studios that build custom AI, consultancies that run large programs, and remote specialists. The questions that decide a project, such as whether the team has shipped agents to production, how it handles the PDPA and MAS guidelines, and who owns the evaluation work, are rarely in the pitch.

This guide compares the 10 best AI development companies in Singapore in 2026. Real services, honest pricing where it is publicly known, pros and cons, and a framework to pick the right AI partner.

Disclosure: AY Automate publishes this guide and ranks itself first, because one senior team ships Claude-native agents end to end, evals included. AY Automate is not based in Singapore and works remotely, with partial overlap with Singapore business hours. If a Singapore entity, onshore staff or a government vendor registration is a hard requirement, start your shortlist at #2.

Best AI development companies in Singapore: a brief overview

• AY Automate: Best overall for agentic systems and Claude-native builds: ships production AI agents with Claude Code, the Claude Agent SDK, LangGraph and RAG pipelines.
• Dyna.Ai: Best for enterprise AI agents in financial services: Singapore company selling an "AI workforce" for service, growth and operations.
• Pand.ai: Best for AI in regulated industries: enterprise AI for banks, insurers and law firms across Southeast Asia.
• Fooyo: Best for AI shipped and run for you: Singapore studio that builds and operates enterprise AI products.
• Aicadium: Best for industrial computer vision: Temasek-founded AI company focused on vision for industry.
• Datature: Best for custom computer vision models: platform and services to label, train and deploy vision AI.
• ADVANCE.AI: Best for identity and anti-fraud AI: KYC, document and face verification for Southeast Asia.
• Tookitaki: Best for AML and fraud AI: financial crime prevention platform for APAC banks and fintechs.
• Activate Interactive: Best for enterprise software with AI: Singapore technology consultancy.
• Thoughtworks Singapore: Best for AI-assisted engineering at scale: global consultancy with a Singapore office.

1. AY Automate, best for Claude-native agentic AI systems

AY Automate is an AI agent development studio that builds production agentic systems for B2B teams. The team specializes in Claude Code, the Claude Agent SDK, LangGraph orchestration and retrieval-augmented generation pipelines. It runs senior-only engagements focused on shipping the agent, the evals and the observability stack.

For Singapore buyers the fit is a regional company that wants one agent in production quickly without hiring a consultancy team. Delivery is remote with partial overlap with Singapore hours, so most work runs asynchronously with scheduled reviews. The studio also delivers in English, French and Arabic, which helps companies serving the Middle East from Singapore. Typical builds include customer-support agents, internal copilots over private data, and workflow automation. Its custom AI development company page shows how a build is scoped and tested on real examples.

Key features

• Claude Code and Claude Agent SDK delivery: tool use, sub-agents and skills
• LangGraph and CrewAI orchestration for multi-step workflows
• RAG pipelines with hybrid retrieval
• Eval harnesses and observability in every build
• Delivery in English, French and Arabic

Best for

• Regional headquarters and scale-ups that need one production agent fast
• SaaS companies adding AI features to an existing product

Pricing

• Custom engagements scoped by outcome
• No public hourly rate sheet

Pros

• Production experience with the Claude Agent SDK
• Senior engineers only
• Evals and observability planned before code

Cons

• Partial time-zone overlap with Singapore
• No Singapore entity for GeBIZ or government panels

Scope and process for an agent build are on our AI agent development services page. For automation around the agent, see AI automation agency services.

2. Dyna.Ai, best for enterprise AI agents in financial services

Dyna.Ai is a Singapore company that sells an "AI workforce": enterprise AI agents for customer service, growth and operations. Its platform lets teams build and govern agents, deploy specialised roles and orchestrate workflows, and its voice AI handles outbound and inbound calls, for example a bank agent following up on a card enquiry.

Dyna.Ai suits banks, insurers and large service businesses that want packaged agents, especially voice, with enterprise governance.

Key features

• Voice and chat AI agents
• Agent building, governance and orchestration
• Marketplace of specialised agent roles

Best for

• Banks and financial services
• High-volume customer service and sales

Pricing

• Not published

Pros

• Mature voice agent offering
• Financial services focus

Cons

• Platform-led; deep custom work may be limited
• Less suited to non-customer-facing agents

Website: dyna.ai

3. Pand.ai, best for AI in regulated industries

Pand.ai builds "enterprise AI for regulated industries" for banks, insurers and law firms across Southeast Asia. Its pitch is that foundation models are now the floor, and the advantage comes from engineering AI around what a firm uniquely knows: how underwriters price risk or how lawyers build an argument. It combines a platform with delivery work.

Pand.ai fits regulated firms that want AI grounded in their own expertise, with control over data and behaviour.

Key features

• Enterprise AI platform for regulated sectors
• Knowledge capture from expert workflows
• Production deployment and control

Best for

• Banks, insurers and law firms
• Use cases where proprietary judgement matters

Pricing

• Not published

Pros

• Clear regulated-industry focus
• Builds around client knowledge, not generic chat

Cons

• Narrow sector focus
• Fewer public details on stack and pricing

Website: pand.ai

4. Fooyo, best for AI shipped and run for you

Fooyo is a Singapore applied AI company that "builds and operates AI products enterprise teams actually use". Its products include an AI knowledge base (RAG), Kakis for marketing AI, Fooyo Commerce and smart tourism solutions, deployed in the client's own cloud. It also offers "FDE as a service" (forward-deployed engineers), AI agents and automation, and AI crowd monitoring.

Fooyo suits enterprises and government agencies that want a local partner to build and also run the AI after launch.

Key features

• RAG knowledge base deployed in your cloud
• Marketing, commerce and tourism AI products
• Forward-deployed engineers and operations

Best for

• Tourism, retail and government buyers
• Teams that want a managed AI service

Pricing

• Not published

Pros

• Singapore team that also operates what it builds
• Ready products shorten delivery

Cons

• Product focus in specific sectors
• Custom agent depth less documented

Website: fooyo.sg

5. Aicadium, best for industrial computer vision

Aicadium is an AI company founded by Temasek. It focuses on AI for industrial computer vision, aimed at improving outcomes in sectors such as manufacturing and infrastructure, and publishes AI transformation projects it has delivered for customers and for itself.

Aicadium is a good pick when the AI problem is visual inspection, monitoring or industrial operations rather than language.

Key features

• Industrial computer vision
• AI transformation projects
• Model development and deployment

Best for

• Manufacturing, infrastructure and industrial operators
• Visual inspection and monitoring

Pricing

• Not published

Pros

• Temasek backing
• Clear industrial focus

Cons

• Vision-focused; not for LLM agents
• Enterprise engagements only

Website: aicadium.ai

6. Datature, best for custom computer vision models

Datature offers a computer vision platform to label data with AI-assisted tools, train and evaluate models, and deploy them to edge or cloud with monitoring. It also sells services, from ideation and a tailored proposal to custom model work.

Datature fits teams that want to own their vision models and use a platform rather than outsource everything.

Key features

• AI-assisted labelling
• Model training and evaluation
• Edge and cloud deployment with monitoring

Best for

• Product teams building vision features
• Industrial and healthcare imaging

Pricing

• Platform tiers plus services

Pros

• End-to-end vision workflow
• Lets your team keep control of models

Cons

• Vision only
• Platform learning curve for non-technical teams

Website: datature.io

7. ADVANCE.AI, best for identity and anti-fraud AI

ADVANCE.AI provides digital identity verification, KYC and KYB, AML and risk tools across Southeast Asia. Its products cover document verification with fraud detection, face authentication with liveness checks and business verification, for banks, fintechs, crypto, e-commerce and payments.

ADVANCE.AI is the right pick when the AI you need is onboarding and fraud control, not a custom agent.

Key features

• Identity and document verification
• Face authentication and liveness
• KYB and risk tools

Best for

• Fintechs, banks and payments companies
• Platforms onboarding users across Southeast Asia

Pricing

• Usage-based; quotes on request

Pros

• Regional coverage of ID documents
• Ready APIs, fast to integrate

Cons

• Product, not a development partner
• Narrow use case

Website: advance.ai

8. Tookitaki, best for AML and fraud AI

Tookitaki sells FinCense, an "end-to-end operating system for AML and fraud prevention" for APAC. It covers transaction monitoring, screening, onboarding risk, customer risk scoring and an alert prioritisation AI agent, and runs an anti-financial-crime community network.

Tookitaki suits banks and fintechs that need explainable AML models aligned with MAS expectations.

Key features

• Transaction monitoring and screening
• Alert prioritisation AI agent
• Case management

Best for

• Banks, fintechs and payments firms
• Compliance teams under MAS supervision

Pricing

• Licensing; quotes on request

Pros

• Deep AML focus
• Built for APAC regulators

Cons

• Product, not a custom builder
• Compliance use cases only

Website: tookitaki.com

9. Activate Interactive, best for enterprise software with AI

Activate Interactive is a Singapore technology consultancy offering consultation, software development, UI/UX design, cloud technology, resource augmentation and Microsoft solutions. AI is part of the applications it builds rather than a separate product line.

Activate Interactive suits buyers who need a Singapore software partner for a wider build, with AI as one part of it.

Key features

• Custom software and cloud
• UI/UX design
• Resource augmentation and Microsoft solutions

Best for

• Enterprise applications with AI features
• Buyers who need a local vendor

Pricing

• Not published

Pros

• Singapore-based delivery
• Design, engineering and cloud in one team

Cons

• AI is not the core specialism
• Limited published LLM or agent work

Website: activate.sg

10. Thoughtworks Singapore, best for AI-assisted engineering at scale

Thoughtworks is a global technology consultancy with an office in Singapore. It is known for engineering practices, its Technology Radar, and work on AI-assisted software development, platform engineering and data. Regional teams work with banks, governments and large enterprises.

Thoughtworks fits organisations that want AI built into how their software teams work, not just one feature.

Key features

• Product and platform engineering
• AI-assisted delivery
• Data and AI strategy

Best for

• Large enterprises and regional headquarters
• Engineering modernisation programs

Pricing

• Not published

Pros

• Strong engineering culture
• Global bench

Cons

• Premium pricing
• Heavy for small builds

Website: thoughtworks.com

How to choose the best AI development company in Singapore

1) PDPA, MAS rules and where the model runs

The Personal Data Protection Act 2012 governs how you collect, use and transfer personal data, including data sent to an AI model, and its transfer obligations apply when data leaves Singapore. The PDPC has published advisory guidelines on using personal data in AI recommendation and decision systems. Financial institutions also follow MAS guidance, including the FEAT principles on fairness, ethics, accountability and transparency. Ask each vendor where prompts, documents and logs are stored and who can access them.

2) Use the government's governance tools

Singapore offers practical frameworks: the IMDA Model AI Governance Framework (including a version for generative AI) and the AI Verify testing toolkit. A good vendor will map its evaluation to these without being asked. If a partner has never heard of them, it has probably not worked with regulated Singapore clients.

3) Platform or custom build?

Dyna.Ai, Tookitaki, ADVANCE.AI and Datature are products. They are faster when your problem matches their scope. Pand.ai and Fooyo combine platforms with delivery. A specialist like AY Automate builds custom agents when no product fits. Decide which you need before you compare prices. See hire remote AI developers guide for the hiring checklist.

4) Singapore team or remote delivery?

Singapore talent is expensive. A developer rate card puts local contract ML engineers at about S$60 to S$150 per hour, with architects higher (Second Talent), and one vendor guide puts AI project budgets anywhere from about S$8,000 for a basic chatbot to over S$600,000 for an enterprise platform (Kaopiz). Remote and regional teams cost less. Compare the best AI development companies in India and in Australia.

Common AI projects for Singapore companies in 2026

The projects we see most often from Singapore buyers fall into a few groups:

• Customer service agents for banks and insurers: answering policy and account questions, triaging claims, and handing over to a human with full context. These need strong evaluation and MAS-aligned controls.
• Internal copilots over private documents: legal, compliance and operations teams searching contracts, policies and procedures with RAG, with access controls that match existing permissions.
• Regional operations automation: agents that read invoices, shipping documents or onboarding forms from several Southeast Asian markets and push structured data into ERP or CRM systems.
• Sales and marketing agents: lead qualification, research and personalised outreach for B2B teams selling across APAC.
• Computer vision in industry: inspection, safety and monitoring in manufacturing, ports and infrastructure, where firms like Aicadium and Datature specialise.

Each group needs a different partner. Packaged products fit the first and last; custom builders fit the middle three, where your data and workflows are unique.

Questions to ask an AI development company in Singapore before you sign

Singapore buyers tend to be careful, and with good reason: many projects touch financial data, health data or regional customers across several jurisdictions. These questions surface the risks early.

1. Where will data be stored and processed? Ask for the cloud region, whether prompts or documents are retained by the model provider, and how the build meets PDPA transfer obligations if anything leaves Singapore.
2. Which agent you built is running in production today? Ask for one live reference you can speak to, ideally in a regulated sector.
3. How do you test the system? Look for an evaluation set built from your data, agreed thresholds and regression tests. Ask whether they have used AI Verify or mapped tests to the IMDA Model AI Governance Framework.
4. How do you handle MAS expectations? For banks and insurers, ask how the vendor supports model risk management, the FEAT principles and MAS technology risk guidelines on outsourcing and cloud.
5. Which languages do your users speak? Many Singapore companies serve Malaysia, Indonesia, Thailand or Chinese-speaking customers. Test those languages, not just English.
6. What will it cost to run? Ask for monthly model, hosting and monitoring costs at expected volume, in Singapore dollars.
7. Who owns the code, prompts and evaluations? Make sure the contract gives you everything you need to switch vendors.
8. What happens after launch? Agree on support, monitoring and training for your team.

Singapore's government also offers support for adoption through agencies such as IMDA, Enterprise Singapore and AI Singapore. Ask vendors whether they have delivered projects under any of these programmes, and check eligibility directly with the agency rather than relying on a vendor's summary.

A good first project is narrow and measurable: one workflow, one team, one metric. Regional rollouts come after the first agent proves itself in one market.

Building an AI agent? Where to start

If you are building an AI agent, copilot or LLM-powered product feature in Singapore and want a senior team shipping on Claude Code, the Claude Agent SDK and LangGraph, AY Automate is built for that work. We run small senior engagements, write the evals and observability plan before the first line of code, and work asynchronously across time zones. Start with AI agent development, read how a custom AI development company build is scoped, and when you are ready, book a consultation.

More agency guides

Comparing a different kind of partner? These guides use the same ranking method and disclosure.

• Best AI development companies in Australia for APAC partners
• Best AI development companies in India for cost-effective offshore delivery
• Best AI development companies in the UAE for Gulf partners
• Best AI development companies in the USA for US-based delivery
• Best AI development companies in the UK for UK-based teams
• Best AI agent development agencies for production agents with evals and tool use
• Best machine learning development companies for classical ML and data science

FAQ

Which is the best AI development company in Singapore? For packaged enterprise agents in financial services, Dyna.Ai. For regulated-industry AI built around your expertise, Pand.ai. For AI built and run by a local team, Fooyo. For a single production AI agent shipped fast by a senior team, AY Automate is our pick (we publish this list, see the disclosure above). The right choice depends on whether a product fits or you need a custom build.

What are the top AI companies in Singapore? On this list, Singapore-based AI companies include Dyna.Ai, Pand.ai, Fooyo, Aicadium, ADVANCE.AI and Tookitaki, plus Activate Interactive and Thoughtworks' Singapore office. Datature serves Singapore clients with its computer vision platform.

How much does AI development cost in Singapore in 2026? Local contract ML engineers are quoted at about S$60 to S$150 per hour on one rate card, with architects higher. Project budgets range from about S$8,000 for a simple chatbot to more than S$600,000 for an enterprise platform, according to a vendor guide. Specialists like AY Automate scope by outcome rather than hourly.

Singapore-based or offshore AI development company? Choose a Singapore firm when you need a local entity, MAS-regulated vendor experience, GeBIZ eligibility or on-site work. Choose a remote or offshore team when the scope is clear and cost matters. Either way, check PDPA transfer obligations before personal data leaves Singapore.

What is AI Verify? AI Verify is a testing framework and toolkit backed by IMDA to check AI systems against principles such as transparency, fairness and robustness. Vendors working with regulated Singapore clients should be able to test against it.

Does the PDPA apply to AI chatbots? Yes. If a chatbot collects or processes personal data, the PDPA applies, including consent, purpose limitation, protection and transfer rules. The PDPC's guidelines on AI systems explain how.

How long does an AI project take in Singapore? A focused agent or copilot can ship in 4 to 12 weeks. Bank and insurer programs with model risk reviews often take 6 to 12 months.

Are there grants for AI projects in Singapore? Government support has included schemes through Enterprise Singapore, IMDA and AI Singapore's 100 Experiments programme. Check current eligibility with the agency before planning around a grant.

Can an AI development company in Singapore train our team? Yes. Most firms here offer enablement. AY Automate runs senior-led builds with a structured handover so your team owns the agent after launch.