Overview

T-Up (Technology for Enterprise Capability Upgrading) is a programme jointly administered by A*STAR and AI Singapore, funded via Enterprise Singapore, aimed at helping Singapore local enterprises (especially SMEs) build up their R&D/technical capabilities by seconding scientists, research engineers, and technical experts into the company to work on innovation/technology projects. The idea is that by embedding research/technical staff into the enterprise, knowledge transfer happens, technical capacity is raised, and new/improved products, processes, or capabilities can be developed.

Support Details

Support Rate

Up to 70% support for SMEs helps reduce cost burden on smaller firms, up to 30% for LLEs

Cap

S$250,000 project cap applies regardless of project scale or duration

Support Levels & Internal Caps by Pillar

Overall Support

Support Rate: Up to 70% of qualifying costs for SMEs & startups, up to 30% for Large Local Enterprises (LLEs)

Grant Cap per New Market: Support capped at S$250,000 per project regardless of duration or number of seconded staff

Pillar	Max Grantable Amount
General Secondments	Up to two years duration
AI-specific Secondments (AISG/T-Up)	Typically one year duration
Overseas Components	May include overseas costs (living allowances, airfare) in qualified costs

Note: These are maximum amounts within each pillar for a single new market. Each application must cover only one activity in a single overseas market.

Project Duration & Scope

Up to two years for general secondments, typically one year for AI-specific secondments under AISG/T-Up

Eligibility Criteria

Must be a business entity registered or incorporated in Singapore
Must have at least 30% local equity (held by Singapore Citizens/PRs, direct or indirect)
SME definition: either group annual turnover ≤S$100 million OR group employment ≤200 employees
Financial capacity and commitment to complete project and co-fund as required
Projects eligible include R&D/innovation in AI, materials, microelectronics, automation, process/product innovation
For AI projects: role of seconded AI engineers is to scope new AI/technical innovation, deliver new product/process, transfer skills
AI engineers/seconded staff must not be in conflict/related to applying company
Alignment with commercial/technological growth targets required

Application Process

Preliminary discussion/scoping with A*STAR/AISG/T-Up team to discuss problem statements, technology gaps, capabilities needed

Define business challenge, technical gaps, desired deliverables, and how seconded staff could help

Submit formal application with project proposal, budget, expected technical outcomes, timelines, staffing plan

AISG/A*STAR reviews, picks suitable scientists/engineers/AI experts to second, and aligns with company

Selection/secondment of experts from pool based on project requirements

Project execution with seconded experts collaborating with company's domain/technical teams

Carry out R&D/innovation work: designing prototypes, developing processes, validating experiments, building IP

Knowledge/technology transfer with seconded staff helping upskill in-house engineers

Monitoring, review and evaluation with periodic check-ins by A*STAR/AISG

Project completion and handover with deliverables, documentation, training, IP transfer

Post-project scaling with company continuing development internally

Processing Time

Application processing: 8-10 weeks for matching and approval, Project duration: 1-2 years depending on scope

Project Duration & Completion

Up to two years for general secondments, typically one year for AI-specific secondments under AISG/T-Up

Best Practices for a Successful Application

Start with well-defined technical challenge/pain point - clearer problems get better support and results

Prepare good proposal with clear deliverables, metrics, milestone plan, risk mitigation, team roles

Engage internal staff early - ensure company engineers/domain experts are part of work for knowledge absorption

Ensure data/testbed readiness - have data access, measurement tools, baseline systems in place before secondment

Select right seconded expert(s) with both domain + technical capability for your environment

Manage scope - define what's feasible over 1-2 years and avoid chasing too many objectives

Plan for handover and continuity from Day 1 with documentation, training, maintenance plans

Monitor closely with checkpoints, reviews, stakeholder alignment throughout project

Leverage external grants/stacking - follow up with EDG, PSG, or other innovation grants for next stages

Be realistic about scaling - moving from prototype to production often requires additional investments

Sample Use Cases & Scenarios

Moveon Technologies: Worked with T-Up to develop optical/imaging/AR innovations and system capabilities

Lion TCR: Used T-Up to advance therapy/biotech R&D capabilities

A*STAR's ARTC: Uses T-Up to second technical advisors into member firms for process/product innovation

AI/data science/machine learning projects for building internal capability or prototype solutions

Advanced manufacturing/process optimization/automation projects

Material/chemical/biotech/bioengineering innovations

Microelectronics, sensors, photonics, and other hardware/component R&D

Process innovation in production, quality control, and operational efficiency

Cross-discipline projects combining software + hardware + domain knowledge

Additional Information

Impact and Effectiveness Evidence: MTI Impact Evaluation Results: • Firms participating in T-Up spent 65.4% more on R&D compared to matched firms not in programme • 8.4 percentage points more likely to conduct R&D in a given year • Enjoyed 44.3% higher revenue and 21.9% higher employment compared to matched firms • Demonstrates effectiveness in boosting both innovation effort and business outcomes Key Strengths and Advantages: • Access to high expertise - small companies gain access to scientists, researchers, engineers they may not hire full-time • Knowledge/technology transfer - embedding experts helps transfer methods, practices, deeper technical skills to company staff • Risk mitigation - reduces technical/R&D risk with proven research staff working with you • Catalyst for R&D investment - grant support encourages companies to allocate resources into R&D/innovation • Broader scope - not limited to AI, applies to other deep tech, materials, processes, microelectronics Challenges and Risk Factors: • Scope creep/overambition - companies may propose too large/vague projects and struggle to deliver • Data readiness/feasibility issues can stall technical work • Absorption challenge - weak knowledge transfer if company staff not sufficiently engaged • Sustainability post-secondment - maintaining, scaling, integrating innovation internally is critical but often difficult • Cost control and matching requirements - companies must commit own resources and meet obligations • Grant cap/funding limits - S$250,000 cap may not fully cover very large or long projects Programme Evolution: • Originally launched around 2003 and has evolved over time • Manufacturing domain uses T-Up through A*STAR's ARTC for technical advisor secondments • AI-specific track added through AI Singapore partnership