
AI Decision Support, powered by Dhisha.ai, helps educators identify student needs earlier, understand the full picture behind performance challenges, and select the right interventions with confidence. By analyzing academic performance, attendance, behavior patterns, and wellbeing indicators, the platform delivers actionable insights that help MTSS teams move from reactive decisions to proactive support. Instead of grouping students into broad categories, AI Decision Support enables true individualized support—treating every student as a unique learner with different needs, strengths, and pathways to success.
AI Decision Support analyzes multiple student data points to generate clear, easy-to-understand summaries that highlight risk factors, strengths, and emerging needs.
Key insights include:
● Academic performance trends
● Attendance patterns
● Behavior indicators
● Social-emotional wellbeing signals
● Historical intervention outcomes
This allows teams to quickly understand what is happening and why.


Stop guessing which intervention might work. AI Decision Support recommends evidence-aligned interventions based on each student's academic, behavioral, and attendance profile.
Benefits include:
● Intervention recommendations based on real data
● Clear rationale for each recommendation
● Tier alignment for MTSS frameworks
● Faster decision making for support teams
● Reduced time spent researching options
AI continuously analyzes patterns across referrals, screening results, and performance data to help schools detect students who may need additional support earlier.
This helps schools:
● Detect risk patterns sooner
● Reduce intervention delays
● Improve student outcomes
● Support proactive MTSS workflows
● Prioritize students based on need


AI Decision Support transforms complex datasets into clear recommendations and summaries so educators can focus on helping students instead of interpreting spreadsheets.
The platform helps teams:
● Quickly review student cases
● Understand contributing factors
● Align on intervention plans
● Document decision rationale
● Improve collaboration across teams
Unlike traditional MTSS tools that group students into static categories, AI Decision Support enables true N=1 personalization by modeling each learner as an individual with unique needs, strengths, and learning contexts.
This enables:
● More precise interventions
● Better student engagement
● Stronger outcomes
● More equitable support decisions
