Assess needs
Role profiles, performance data, and project demand highlight where capability lags hurt delivery.
/ 运营与自动化 /
适合每个人的培训。没有达到平均水平。
人工智能驱动的学习可以个性化内容、跟踪技能差距并让您的员工领先于业务需求，而无需传统学习与发展计划的开销。
The problem
One-size-fits-all training that doesn't stick
-
One-size-fits-all training that doesn't stick
Generic programmes cover what the average employee needs. They miss what each individual actually requires to perform better.
-
Skill gaps identified too late
By the time a capability shortage shows up in performance data, the business has already felt the impact for months.
-
L&D investment without visibility on return
Training programmes consume budget and time. Without data connecting learning activity to performance outcomes, ROI is assumed, not measured.
-
Training disconnected from performance
Courses get completed but on-the-job application is not measured. Skill gaps persist despite L&D spend.
运作方式
Skills gaps identified—learning paths generated—impact measured
Assemble journeys
Micro-learning, labs, and coaching prompts are composed from your catalogue—not generic internet courses.
Prove behaviour change
Completion is tied to downstream KPIs and manager feedback so L&D funds what moves the needle.
SCORM, LMS, and HR systems stay the system of record for credentials.
适合每个人的培训。没有达到平均水平。
包含内容
What you get when you run this with Thinkia
A governed layer across data, workflows, and handoffs—so teams ship safely and scale with metrics.
Personalised learning paths
Adapts content, pace and format to each employee's role, skill level and learning style.
Skill gap detection
Maps current capabilities against role requirements and future business needs.
AI-powered content creation
Generates training materials, assessments and practice scenarios from your internal knowledge.
Learning analytics
Tracks completion, engagement and knowledge retention at individual and team level.
Performance correlation
Connects learning activity to on-the-job performance metrics to measure actual impact.
Continuous skill monitoring
Tracks capability evolution over time, not just at annual review cycles.
技术提供 Thinkia Synapse
成果
What changes when this runs in production
Results vary by workforce size, skill domain and existing L&D infrastructure.
+40%
Improvement with personalised vs. generic training programmes
–30%
Faster skill development with adaptive learning paths
–60%
Reduction using AI-assisted content creation
合作方式
From static courses to adaptive paths tied to skills data
Skills frame
Skills frame
Week 1–2
Competency models, LMS catalogues, and business priorities define what “good” looks like.
Content & assess
Content & assess
Week 3–5
Micro-learning, scenarios, and checks are aligned to roles; accessibility and languages are set.
Cohort pilot
Cohort pilot
Week 6–9
Completion, application on the job, and manager feedback shape the next iteration.
Scale programmes
Scale programmes
Week 10+
Curricula expand by function; analytics tie learning signals to performance conversations.
Union training requirements and vendor content licences affect integration; we phase by audience.
开始
Ready to scope this for your context?
We start with a focused session—no commitment—to map constraints and a sensible path.