Top 10 AI Companies in Singapore to Know in 2025

Singapore is now a leading place for practical AI. Local teams build tools that help people move, shop, pay, and work. Global brands also set up labs here to develop new AI products. This mix of homegrown talent and global investment makes the market strong.

This article gives a clear view of the top 10 AI companies in Singapore to know in 2025. It explains what each company does, why it matters, and which use cases they serve. It also shares simple rules for choosing an AI partner, what industries gain most, and how rules shape AI work here.

The goal is to help readers make a simple, useful choice. The writing uses straight words. It avoids heavy jargon. It links each company to real outcomes, like better customer support, safer payments, faster content work, or smarter retail shelves. Each section shows what matters so a team can take the next step with confidence.

Where AI in Singapore Creates Value Today

Mobility and urban services. AI routes drivers, balances demand, and flags risky behavior. City partners use it to study flows and improve safety. This is why large platforms continue to invest in local AI centers; they can test with live, high-volume data. 

Retail and e-commerce. Vision and search AI help shoppers find items fast and help brands track shelves. Retailers lift conversion when images, attributes, and search are in sync. Field reps use store photos and get clear actions from the data. 

Financial risk and compliance. Banks must detect fraud and money laundering without blocking good users. AI models, built with strong governance, reduce false positives, catch new patterns, and support audits. This cuts costs and improves customer trust. 

Customer service. Voice and chat agents now handle many tasks in local languages. Teams see shorter queues and higher satisfaction, while human agents focus on complex cases. AI tools help draft answers and keep the tone on brand. 

Content and merchandising. Product data is often messy. AI fills missing attributes, creates clear titles and bullet points, and edits images. This speeds launch cycles and makes catalogs easier to shop.

The Top 10 AI Companies in Singapore to Know in 2025

Here are some of the leading AI companies in Singapore to watch in 2025:

• Snap Innovations – Rapid applied AI builds and trading automation
• Grab (AI Centre of Excellence) – City-scale AI for mobility, delivery, and payments
• Razer (AI Center of Excellence) – Gaming QA, device intelligence, and player support
• Sea AI Lab (SAIL) – Research that ships to Shopee and Garena products
• ViSenze – Visual search and recommendations for online retail
• Trax – Shelf vision and retail execution analytics for CPGs
• ADVANCE.AI – Identity, KYC/KYB, and risk scoring for finance
• WIZ.AI – Multilingual voice and chat agents at enterprise scale
• Hypotenuse AI – Product content and light image tools for e-commerce
• Tookitaki – AML and fraud monitoring built for banks and regulators

Looking to deploy AI and see real gains in 2025? This article breaks down the Top 10 AI companies in Singapore that are reshaping everyday services and enterprise workflows. Whether the goal is higher conversion, faster support, safer payments, or better compliance, these teams offer the tools, models, and delivery muscle to help. Expect practical use cases, clear pros and cons, and pointers for pilots—so your team can choose with confidence and move from plan to production.

1. Snap Innovations

Snap Innovations builds trading and automation systems that blend software engineering with machine intelligence. The firm is known for fast iteration, custom integrations, and strong local delivery in Singapore. For buyers, the appeal is practical AI: signal detection, workflow automation, and dashboards that ship quickly. Teams also like that Snap will tailor solutions to unique data sources and compliance needs. This makes it a good first partner if you want working prototypes in weeks, not months.

2. Grab (AI Centre of Excellence)

Grab runs one of Southeast Asia’s largest everyday apps for transport, food, and financial services. In May 2025, it launched an AI Centre of Excellence in Singapore to push AI deeper into its stack. The work targets matching, routing, ETA accuracy, and fraud controls in real time. It also supports public-sector goals around Smart Nation and AI jobs. For buyers and partners, this is a hub that blends research, product, and operations on a huge scale.

3. Razer (AI Center of Excellence for Gaming) 

In August 2025, Razer opened its first global AI hub in Singapore. The plan includes hiring 150 AI specialists to speed QA, improve in-game guidance, and tune hardware experiences. Expect tools that shorten game testing cycles and improve support for players. Device intelligence and personalization are also in scope. This places Singapore on the map for AI in entertainment and interactive media.

4. Sea AI Lab (SAIL)

SAIL is Sea Group’s research arm, supporting products like Shopee and Garena. The lab works on language models, trustworthy AI, and scalable systems. It publishes code and research, which helps teams assess rigor and direction. The link to high-traffic apps means findings can ship to production. This is a key node where science meets very large user bases.

5. ViSenze

ViSenze helps shoppers find products with images and improves on-site recommendations. Fashion and lifestyle retailers use it to match fast-moving catalogs with intent. Visual similarity and attribute extraction boost discovery and conversion. It also aids merchandising teams with better tagging and content. For marketplaces, it reduces friction from poor search terms or long product names.

Also Read: Top 10 Blockchain Companies in Singapore (2025 Update)

6. Trax

Trax turns store photos into structured data to fix out-of-stocks and improve display quality. It powers shelf analytics and promotion planning for global CPG brands. The system helps field teams spot gaps and measure compliance. Brands use it to improve sales lift and reduce lost revenue. Trax began in Singapore and now operates worldwide.

7. ADVANCE.AI (Advance Intelligence Group)

ADVANCE.AI provides identity verification and risk engines for banks, fintechs, and platforms. The tools reduce fraud, speed onboarding, and support compliance. Coverage includes KYC/KYB checks, document scans, and liveness checks. Scores and rules can be tuned to local risk profiles. This is the core trust infrastructure for digital services in the region.

8. WIZ.AI 

WIZ.AI builds multilingual voicebots and chatbots for sales, service, and collections. It handles millions of automated calls and messages across Southeast Asia. The goal is higher response rates and shorter wait times at a lower cost. Domain tuning improves recognition in local accents and languages. Enterprises use it to scale outreach without scaling headcount.

9. Hypotenuse AI

Hypotenuse AI helps teams create on-brand product copy at scale. It also supports product data enrichment and light image edits. Merchandisers use it to standardize titles, bullets, and long descriptions. This speeds catalog work across marketplaces and owned sites. It reduces the manual copywriting load while improving consistency.

10. Tookitaki

Tookitaki’s FinCense platform supports transaction monitoring, screening, and case work. Banks use it to cut false positives and meet regulatory standards. Models help detect new patterns while rules keep oversight clear. Case tools give analysts better triage and evidence. It fits teams that want measurable quality gains in compliance.

Singapore’s AI scene now covers real needs across transport, gaming, shopping, identity, customer service, content, and compliance, plus research that turns into usable tools; if you’re choosing a partner, start with your top goal (more sales, fewer fraud losses, faster support, stronger compliance), then confirm three basics, how it integrates with your systems, what data it needs and who controls it, and how you’ll govern model updates and risks, while keeping pilots short (6–10 weeks), tracking one clear success metric, and planning the handover to operations from day one so you see real results this year.

How to Choose the Right AI Company for Your Needs

• Start with the problem, not the model. List the top three tasks you want done. For example, “cut call center wait time,” “reduce AML false positives,” or “grow conversion on product search.” Share data samples if allowed. Ask vendors to show how their product acts on the same task.
• Check the proof on similar data and scale. Ask for case studies from your industry and region. Check whether the data size, channel count, or response time matches your own. If you handle millions of events per hour, pick a vendor with that track record.
• Ask about safety and compliance. In Singapore, many teams must meet rules from MAS, IMDA, and PDPA. Ask how the vendor logs model decisions, handles PII, and supports audits. A good vendor will show both technical and legal controls in plain terms.
• Measure full cost and time to value. Do not look only at license fees. Count data prep, integration, cloud costs, and training. Ask when value shows up: week 2? month 3? Insist on a small pilot with clear KPIs. Tie payment to outcomes when possible.
• Plan for change. AI needs updates. Data shifts over time, and so do attacks and user needs. Check how the vendor handles model drift, new features, and rollback. A simple, well-documented process is better than a flashy tool with no governance.

Hiring, Skills, and the Local Talent Pipeline

Demand is broad. In 2025, new AI hubs in Singapore continue to hire data scientists, ML engineers, and applied researchers. Product managers and QA engineers with AI knowledge are also in demand. This mix reflects how AI now touches many roles, not just research teams. 

What skills matter most? For engineers: Python, data pipelines, vector databases, prompt engineering, and evaluation design. For product and ops: writing clear problem statements, setting KPIs, and designing safe workflows. For governance: model risk, privacy, and audit trails.

How firms build teams. Many companies blend a small “platform” team with embedded specialists in each business area. This keeps a consistent base (data quality, monitoring, security) while letting product teams move fast on use cases.

Where to learn. Singapore has public programs and industry events on AI skills, plus research links with local universities and labs. Company-run showcases and open seminars also help students see real use cases and paths into the field.

Also Read: Top 10 Blockchain Developers in Singapore to Know in 2025

Data, Privacy, and Rules: What Buyers Should Know

• Privacy and PDPA. If your use case touches personal data, confirm how data is stored, masked, and accessed. Ask for data flow diagrams. Request role-based access and clear retention rules. Make sure the vendor supports subject access requests.
• Sector rules. Finance teams should ask about MAS alignment and screening formats. Good AML tools already ship with workflows that fit local rules and reporting needs. Health and public sector buyers should ask for extra audit features, including full decision logs. 
• Model safety and abuse. Ask how the vendor blocks prompt injection, data leaks, and unsafe outputs. For agents that act (not just chat), use strict scopes and human review for risky steps. Make sure the system can turn off features fast if needed.
• Transparency. Push for evaluation reports in plain language. Ask how the model was tested, what edge cases failed, and how fixes roll out. Simple checklists beat vague claims.

Conclusion

Singapore is one of the easiest places to turn AI ideas into working tools. The top 10 AI companies in Singapore in this article show how broad the impact is: from getting a ride faster, to finding products by image, to stopping fraud, to scaling content, to powering games. Buyers can pick a partner that fits their task and budget, and move from pilot to value in weeks.

The best way to choose is to start small and measure. Define a sharp goal, run a short pilot, and track results. Ask for proof on data like yours. Check privacy and compliance from the start. This approach reduces risk and builds trust across teams.

This article hopes to make the next step simple: pick one or two names that match your need, invite a short demo with your data, and compare results. With the right partner, AI can help your team save time, cut risk, and grow faster in 2025.