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Effortless Process Documentation
Relieve teachers from writing while observing; AI automatically distills structured factual evidence.
Child High-Quality Development
Unifying the AI Smart Observation engine with the Teaching & Research workbench. Starting from multimodal materials in self-directed play, verified by professional educators, automatically compiling traceable portfolios and generating differentiated support strategies.
Making every observation evidence-based; ensuring every child's unique potential is recognized.
- Target Audience
- Principals · Teachers · Researchers
- First Visible Result
- A complete closed-loop sample from raw media upload to verifiable observation reports and action strategies.
- Recommended Starting Point
- Select 1-2 seed classrooms to trial play scenarios before rolling out routine observations campus-wide.
Transforming observation from a cumbersome documentation chore into a professional scaffold that elevates every child's potential.
Current Bottlenecks vs Solution Breakthroughs
From Traditional Documentation Pain to AI Evidence-Based Support
Tackling the pain points of time-consuming logging, ungrounded judgments, and shelfware records with AI evidence technology.
Observation Efficiency
Post-Class Memory Logging, Heavy Burden
Teachers must handwrite notes while supervising or reconstruct fuzzy memory forms after class, taking heavy overtime and easily missing critical nuances.
Spontaneous Capture · AI Auto-Drafted Facts
Educators capture quick videos or voice clips on mobile; AI automatically drafts structured behavioral facts and verbal clues, reducing administrative burden by over 70%.
Objective Evidence
Subjective Impressions, Thin Evidence
Evaluations rely largely on subjective impressions or generic templates, lacking objective process evidence to back up parent and research discussions.
Fact-Anchored · Traceable Developmental Insights
Every evaluation conclusion is 1:1 anchored to exact behavioral clips, child quotes, and artifacts; every growth judgment is verifiable anytime.
Follow-Up Conversion
Dormant Folders, Seldom Applied
Observation notes remain stored in static paper binders for inspection, rarely feeding back into curriculum adjustments or child growth.
Intelligent Matching · Continuous Support
The system intelligently matches targeted support strategies across five domains, seamlessly bridging into lesson design and differentiated care.
Core Outcomes
Returning Child Developmental Support to Authentic Educational Contexts
Centering on authentic child activity processes to achieve a professional closed-loop: retain materials, articulate conclusions clearly, and provide continuous developmental support.
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Evidence-Based Growth Assessment
Every developmental conclusion traces back to specific behavioral clips and exact child quotes.
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Continuous Care & Education Follow-Up
Intelligently suggest differentiated support strategies based on observations, seamlessly informing subsequent curriculum.
Solution Overview
Child High-Quality Development
Layered view across product form, business domain, core AI engines, and implementation services.
Tier 1
Platform Foundation
Tier 2
Business Domain
Tier 3
Core AI Engine
Tier 4
Companion Services
Observations, listening, and PBL projects are unified into child growth portfolios under privacy governance.
Objective Data Sources
Consolidating Objective Evidence from Authentic Activity Processes
Supports multi-source process material input. Campuses can enter flexibly according to current pedagogical research priorities, gradually accumulating individual child growth portfolios.
Activity Short Videos & On-Site Media
Record gameplay and learning zone activity clips via phones or tablets to extract typical behavioral facts and developmental clues.
Original Child Audio & Verbal Materials
Record children's spontaneous storytelling, peer dialogues, and artwork descriptions with high-accuracy transcription to interpret underlying cognitive reasoning.
PBL Inquiry Process Artifacts
Collect longitudinal inquiry plans, representational drawings, and milestone artifacts to document project progression from initiation to in-depth exploration.
Implementation Roadmap
Multimodal Capture — AI Distillation — Educator Verification
Every step tightly links with the core educational process, ensuring AI outputs are verifiable, explainable, and directly serve instructional support.
- 01
01 · Multimodal Capture
Capture activity video clips or audio, preserving rich on-site details of play and inquiry.
- 02
02 · AI Smart Distillation
AI structures behavioral factual drafts and support recommendations against core developmental domains.
- 03
03 · Teacher Verification & Application
Teachers professionally review and refine drafts, applying results to care plans and growth portfolios with one click.
Roles & Collaboration
Making every observation an objective foundation for child development support.
Starting from one authentic scenario, running through the 'Capture — AI Structuring — Verification — Action' workflow so process evidence empowers practice.
AI
Child High-Quality Development
Multimodal parsing of activity footage, child dialogues, and inquiry artifacts to distill structured growth clues and match support strategies.
Educator
Principals · Teachers · Researchers
Teachers add contextual background, verify factual accuracy, and hold final authority over modifications and care decisions.
Educator Core Authority
Capturing authentic media, verifying AI-extracted clues with contextual background, and deciding pedagogical actions.
Principals & Research Leads
Conducting targeted research based on campus-wide observation dashboards to optimize resource allocation and training.
PalmBaby Expert Team
Providing system configuration, practical onboarding, joint research workshops, and milestone review services.
Implementation Roadmap
Tailoring Implementation Roadmaps to Organizational Scale
From single-campus pilots to regional scaled deployment, flexibly matching the digital progression rhythms of different organizations.
Public & Flagship Campuses
Starting with 1-2 pilot classrooms to establish standardized observation, verification, and support workflows for easy teacher adoption.
Group Kindergarten Networks
After validating workflows in benchmark campuses, sharing outstanding case libraries across branches to unify group care standards.
Regional Demonstration Projects
Building regional preschool quality monitoring and data infrastructure to empower balanced, high-quality regional education.
Implementation & Phased Acceptance
Select 1-2 seed classrooms to trial play scenarios before rolling out routine observations campus-wide.
A complete closed-loop sample from raw media upload to verifiable observation reports and action strategies.
- 01
3 Days · Scenario Experience
Confirm pilot classrooms, authorization boundaries, and seed teachers; experience the full flow from media input to report output 1-on-1.
- 02
7 Days · Workflow Run-Through
Run through the routine cycle of 'Capture — AI Structuring — Teacher Verification — Action Plan' in representative classrooms.
- 03
30 Days · Stage Acceptance
Review observation quality, teacher workload reduction, and research depth; generate a customized campus outcome analysis report.
Security, Compliance & Ethics
Child Data Security & Educational Ethics Boundaries
Audio/video media capture strictly adheres to minor protection laws and parental consent systems, with end-to-end encryption and tiered isolation.
Informed Consent & Purpose Limitation
Strictly defining capture objectives, media boundaries, visible roles, and retention periods, ensuring compliance first.
Final Human Verification by Educators
AI serves solely as an assistant; teachers retain 100% editing, supplementing, and veto authority over all findings.
Fine-Grained Role Permission Isolation
Tiered role permissions for teachers, researchers, and principals prevent unauthorized access and data leakage.
Solution & Implementation FAQ
Verifying Solution Value Through Authentic Product Workflows
Behavioral observations, child listening, and PBL projects are unified into child growth portfolios under strict privacy and consent governance.
Does AI directly replace teachers in making subjective assessments of children?
Absolutely not. AI is solely responsible for transcription, structural summarization, and generating editable drafts. All evaluative conclusions and support strategies must be reviewed and confirmed by teachers in real context. Teachers retain 100% authority and veto power.
Is additional hardware mandatory to get started?
Not at all. Existing campus phones or tablets are sufficient for recording; if fixed environmental capture is desired later, optional smart hardware can be integrated on demand.
Are activity observation, child listening, and PBL isolated systems?
The three scenarios are deeply unified within a single care & education workbench. All records flow automatically into child portfolios without manual switching between systems.
What scale should our campus start with?
We recommend starting with 1-2 representative classrooms and one typical activity (such as self-directed center play) to smooth the closed-loop workflow before scaling campus-wide.
Making every observation evidence-based; ensuring every child's unique potential is recognized.
Unifying the AI Smart Observation engine with the Teaching & Research workbench. Starting from multimodal materials in self-directed play, verified by professional educators, automatically compiling traceable portfolios and generating differentiated support strategies.