How to Create an Autism Screening Tool Like EarliTec

Key Takeaways

• Autism screening tools enhance early detection and provide valuable data for clinicians, improving assessment accuracy.
• AI-powered platforms like EarliTec leverage eye-tracking technology to streamline autism evaluations and reduce biases.
• The growing demand for early autism diagnoses drives opportunities in the autism screening tool market, projected to grow significantly by 2036.
• Building an effective autism screening tool requires careful planning, regulatory compliance, and integration of advanced AI technology.
• Revenue models include SaaS subscriptions, per-assessment fees, and insurance reimbursement pathways for increased accessibility.

For decades, autism assessments have relied on what clinicians could observe during a short appointment and what parents remembered about their child’s development. Although this approach is still important, many early behavioral signs develop gradually and may not be obvious during a single visit. As more families seek answers sooner, autism screening tools are becoming a valuable first step before a formal diagnosis. They help track a child’s development over time and give clinicians more meaningful information to support their evaluation. Instead of replacing specialists, these platforms make early screening more consistent and easier to access. 

We’ve built numerous autism screening tools that leverage AI-powered computer vision and behavioral data analysis to support early developmental assessments and improve clinical decision-making. As we have this expertise, we’re writing this guide to walk you through the complete process of creating an autism screening tool like EarliTe. 

Market Opportunity for AI-Powered Autism Screening Tools

According to FactMR, the autism diagnostics market is projected to grow from USD 4.40 billion in 2026 to USD 13.5 billion by 2036, at a CAGR of 11.9%. The market is expanding as more families look for earlier autism screening and healthcare providers adopt faster, more objective ways to identify developmental concerns. This shift is creating strong demand for digital autism screening platforms that support timely intervention. 

Source: FactMR

Key market drivers:

• Critical Early Intervention: Brain plasticity makes intervention before age three far more effective than treatment starting at age five or six.
• Systemic Wait Times: Families wait an average of two years between their first concern and a formal diagnosis.
• Mandated Milestones: Insurers and health systems increasingly require developmental checks at 18 and 24 months.

These factors create guaranteed recurring demand for software that speeds up early triaging.

AI Accelerates Diagnostic Accuracy

Traditional ASD diagnostics rely on manual observation. A specialist tracks social interactions using standard scoring rubrics. This process takes hours, costs thousands of dollars, and introduces personal bias. AI diagnostics replace subjective checks with precise digital biomarkers. Algorithms analyze micro-behaviors that human eyes miss during standard exams.

A prime commercial example is EarliPoint Health. Their platform tracks eye gaze 120 times per second while a child watches social videos, detecting subtle shifts in visual attention. Supported by clinical data in JAMA, parent firm EarliTec Diagnostics secured $21.5 million in Series B funding and generates an estimated $5 million to $8 million in annual revenue as healthcare networks adopt the device.

Clinicians adopt these systems to standardize checks, boost patient throughput, and cut friction in overloaded clinics.

Capital Flows to Digital Diagnostics

Venture firms are shifting capital toward platforms with clear FDA clearance, defensible IP, and scalable billing models. Digital tools lower labor costs while tapping direct reimbursement via standard CPT medical codes. Investments in pediatric AI scale because health payors see long-term cost benefits. Early identification reduces lifelong costs for special education and therapy by hundreds of thousands of dollars per child.

Another company proving this path is Cognoa with its Canvas Dx platform. As the first FDA-authorized AI diagnostic tool for autism, Canvas Dx uses parent questionnaires and short videos to deliver a diagnosis or rule-out recommendation within days. Cognoa has raised over $50 million in funding and generates an estimated $10 million to $15 million in annual revenue through expanding insurance and Medicaid coverage.

What Is the EarliTec System and Why Was It Developed?

EarliTec Diagnostics launched to solve a major bottleneck in pediatric medicine: delayed autism assessment. The company originally developed its signature eye-tracking hardware under its original corporate name before formally rebranding as EarliPoint Health. This pivot signaled a broader commercial mission to expand from a pure hardware maker into an end-to-end clinical network.

By transitioning to EarliPoint Health, the venture aligned its brand directly with its primary asset, the FDA-cleared EarliPoint Evaluation. The company operates a high-growth model backed by over $41 million in total venture funding, generating an estimated $5 million to $8 million in annual software subscription and hardware device revenues as state Medicaid policies and private payors expand coverage.

The Need for Earlier Diagnosis

Families routinely encounter systemic delays when seeking developmental assessments for young children. The path from an initial parental concern to a final diagnosis frequently takes over two years.

• Specialist Shortages: Developmental pediatricians are heavily backlogged, causing waiting lists that range from 9 to 18 months in most regions.
• Subjective Assessments: Traditional observation methods rely on human scoring, which can lead to variable results depending on clinician experience.
• Missed Intervention Windows: Critical neural plasticity occurs before age three, yet most children receive an official diagnosis well after their fourth birthday.

Early detection gives children access to speech, occupational, and behavioral therapy when their brain adaptability is highest. Healthcare providers need efficient, objective tools to screen toddlers accurately without creating multi-year waiting queues.

How EarliPoint Supports Clinicians

The EarliPoint System functions as a diagnostic aid designed to fit into standard clinical environments. It uses a specialized tablet platform equipped with precision eye-tracking sensors to monitor a child’s visual attention.

• Passive Video Engagement: The child sits in front of a screen and watches short video scenes depicting natural social interactions between children.
• High-Speed Data Capture: Integrated sensors track eye movements 120 times per second to capture social fixation patterns that are invisible to the naked human eye.
• Automated Data Processing: The software compares the child’s looking behavior against established neurotypical developmental benchmarks.

The system produces detailed diagnostic metrics on social disability, verbal ability, and non-verbal learning. It does not replace the physician. Instead, it provides objective behavioral metrics that complement standard diagnostic interviews, giving clinicians clear data to make confident diagnostic decisions in a fraction of the usual time.

The Science Behind FDA Clearance

EarliPoint was built on more than two decades of clinical research conducted by Marcus Autism Center, Children’s Healthcare of Atlanta, and Emory University School of Medicine. The research showed that how young children visually engage with social scenes can serve as a reliable digital biomarker for identifying early signs of autism, forming the foundation of the platform’s eye-tracking technology.

Its accuracy was validated through large multi-site clinical studies, leading to FDA 510(k) clearance. The findings, published in the Journal of the American Medical Association (JAMA), demonstrated strong agreement between EarliPoint’s automated eye-tracking analysis and expert clinical evaluations. This gave healthcare providers greater confidence in using AI-assisted tools to support early autism assessment.

The Science Behind EarliTec’s Eye-Tracking Technology

EarliTec’s technology shifts autism screening from subjective clinical observation to quantifiable biological data. Instead of relying on manual checklists, the platform uses precision eye tracking paired with AI algorithms to capture micro-behaviors that human eyes miss.

From a commercial standpoint, EarliTec monetizes this solution through a hybrid medtech hardware-and-software model. Clinics pay an upfront device fee or lease rate for the specialized tablet hardware, paired with recurring per-test platform fees or software subscription tiers ranging from $150 to $350 per evaluated patient, which healthcare providers bill directly to commercial payors and Medicaid using established CPT medical codes.

Measuring Visual Attention

The EarliPoint System presents young children with brief video clips showing natural social interaction. As the child watches, high-speed infrared sensors embedded in the device record visual fixation points 120 times per second. These sensors track exact coordinates on the screen to establish what captures the child’s attention:

• Social vs. Non-Social Focus: Comparing time spent looking at human eyes and facial expressions versus background objects or movement.
• Gaze Latency: Tracking how quickly a child shifts visual attention when a speaker begins talking or changing gestures.
• Fixation Duration: Measuring the stability of a child’s focus during key moments of social cueing.

These gaze patterns act as objective digital biomarkers. They show how a child processes social information long before complex verbal or motor behaviors fully develop.

Turning Gaze Data into Insights

Collecting raw gaze coordinates is only the first step. EarliTec’s AI engine analyzes millions of individual data points collected during a single 12-minute video session. The machine learning model cross-references a child’s looking patterns against vast normative datasets gathered from neurotypical children and children diagnosed with autism. 

The system does not issue an automated diagnosis. Instead, it outputs a standardized report detailing percentile scores across social disability, verbal ability, and non-verbal learning. Clinicians use this report alongside traditional interviews to confirm diagnoses faster.

The Value of Objective Data

For decades, clinicians relied entirely on qualitative behavior checks. These assessments often led to inconsistent results based on a clinician’s experience level or a child’s mood during a single clinic visit. Objective eye-tracking solves these friction points:

• Bias Reduction: Data measurements remain consistent regardless of patient background or clinician experience.
• Transparent AI: The platform uses explainable models rather than black-box algorithms, showing physicians exactly which gaze behaviors influenced the summary score.
• Clinical Trust: FDA clearance confirms that automated biomarkers closely mirror consensus decisions made by expert panels.

Combining clinical oversight with objective AI validation reduces evaluation times from hours to minutes, unlocking higher patient capacity for developmental clinics.

Key Features of an Autism Screening Tool Like EarliTec

Digital autism diagnostic tools are making early screening more practical for pediatric clinics. They help clinicians assess children more consistently using objective data while reducing the time and effort involved in traditional evaluations. For founders, they also present a growing opportunity to build scalable healthcare platforms that improve care delivery.

1. AI Eye-Tracking Assessment

EarliTec uses tablet-based sensors to turn eye movements into objective developmental data. While a toddler sits in front of the device, high-speed infrared cameras track point-of-gaze coordinates 120 times every second. Users inside the clinic simply place the child comfortably in front of the EarliTec display. The system calibrates automatically without requiring physical contact or restrictive headwear, capturing visual attention data in controlled or semi-controlled rooms.

2. Automated Social Engagement Analysis

The platform processes thousands of visual data points to spot social attention patterns. EarliTec algorithms evaluate whether a child focuses on social cues, like human eyes and facial expressions, or shifts attention toward non-social background elements. Clinical staff monitor the live feed on a supervisor dashboard to ensure the child stays engaged throughout the video playback.

3. Objective Developmental Scoring

Rather than relying on qualitative memory, EarliTec automatically converts gaze records into standardized index scores. The software compares a child’s visual metrics against large clinical control datasets.

• Social Disability Index: Measures deviations in expected social gaze focus.
• Verbal & Non-Verbal Metrics: Evaluates visual processing patterns linked with cognitive milestone tracking.

Clinicians access these metrics directly inside the EarliTec application interface immediately after testing finishes.

4. Clinician-Friendly Diagnostic Reports

Once testing concludes, EarliTec automatically generates a concise PDF diagnostic summary. The report presents clear visual charts and percentile scores designed for quick physician review. Doctors open the generated report during parent consultations to explain findings using objective visual charts rather than abstract medical jargon.

5. Longitudinal Progress Tracking

EarliTec allows healthcare providers to run repeated screenings over time to observe a child’s developmental trajectory. The platform stores past evaluation records side by side in the patient portal.

• Baseline Assessment: Establishes initial social attention scores before starting therapy.
• Intervention Monitoring: Tracks shifts in social gaze after six to twelve months of targeted speech or behavioral therapy.
• Treatment Adjustment: Helps care teams refine therapy plans based on objective behavioral changes.

Therapists and pediatricians use these historical trendlines to verify if early intervention strategies are producing measurable results.

6. Quick Non-Invasive Assessment Workflow

EarliTec streamlines testing into a single 12-minute session. A medical assistant or nurse can launch the program, guide the family into the room, and complete the test without needing specialized diagnostic training.

The workflow operates effortlessly inside standard clinical rooms:

• Minimal Setup: Launch the EarliTec app on the dedicated tablet.
• Child Engagement: The child watches short, age-appropriate video clips showing real children playing.
• Instant Results: The device processes all gaze metrics locally or via secure cloud servers as soon as the video finishes.

This rapid process lets busy clinics evaluate multiple toddlers every day without creating long patient wait lists.

7. FDA-Cleared And EHR-Ready Platform

EarliTec built its software architecture to meet strict regulatory and technical standards for healthcare deployment. The 510(k) FDA clearance gives pediatric practices confidence in the platform’s diagnostic validity. The system connects directly to EHR platforms like Epic or Cerner using standard HL7 and FHIR protocols. Medical staff order the EarliTec evaluation inside their existing patient chart software, and the final diagnostic report auto-populates back into the patient’s permanent record for streamlined billing and documentation.

How to Create an Autism Screening Tool Like EarliTec?

Building a regulated autism screening tool requires balancing deep clinical science with flexible software architecture. At IdeaUsher, we help healthtech innovators and investors turn complex clinical requirements into market-ready platforms. By engineering custom software architectures, our teams accelerate development timelines while maintaining strict adherence to regulatory standards.

1. Defining Use Cases And Users

Before writing code, we establish the exact clinical footprint for your diagnostic tool. A platform built for high-throughput pediatric clinics requires a vastly different user experience than software created for specialized hospital networks or remote telehealth settings.

• Care Settings: Pediatric primary care, developmental clinics, or hospital networks.
• Target Patient Profile: Specific age windows, such as toddlers aged 16 to 30 months.
• Clinical Role: Triaging tool, screening aid, or FDA-cleared diagnostic support software.

We map your target workflows early to ensure the software seamlessly aligns with daily clinical operations.

2. Building The AI Assessment Engine

Our development teams engineer custom AI algorithms designed to detect subtle behavioral indicators. We train computer vision models to identify patterns that clinicians might miss during standard physical exams. Rather than replacing human judgment, we design our software engines to act as intelligent co-pilots for physicians, providing objective risk probabilities alongside traditional clinical evaluations.

3. Integrating Eye-Tracking Sensors

Capturing reliable gaze metrics requires precise computer vision pipelines. We integrate high-speed tracking software into standard tablets and custom camera setups to monitor visual attention in real time.

• Gaze Coordinate Capture: Tracking eye movements at 60Hz to 120Hz while a child watches short videos.
• Feature Extraction: Identifying visual fixation shifts between social cues and background objects.
• Biomarker Mapping: Converting raw positional data into standardized percentile scores for language and cognition.

Our engineers ensure these algorithms process spatial inputs smoothly across consumer hardware platforms without latency.

4. Designing Clinician Workflows

Healthcare software must reduce administrative friction, not add to it. We build intuitive interfaces that guide clinical staff through every phase of the patient assessment process. By combining caregiver questionnaires, real-time video analytics, and automated report generation into one unified application, we help clinics process more evaluations per day.

5. Ensuring Regulatory Compliance

Security and regulatory readiness are built into our codebase from day one. When developing Software as a Medical Device (SaMD), we enforce strict end-to-end data encryption and complete regulatory compliance.

• HIPAA Compliance: Secure data storage using encrypted cloud infrastructure.
• FDA SaMD Readiness: Full software documentation for 510(k) or De Novo regulatory submissions.
• Interop Standards: Native support for HL7 and FHIR protocols to sync directly with major Electronic Health Record systems.

Our engineering protocols protect sensitive patient health data while maintaining full auditability for medical authorities.

6. Clinical Data Validation

AI diagnostic models depend heavily on the quality of their training data. We assist partner teams by building robust data collection frameworks that maintain model fairness and performance across diverse patient populations. We design your software infrastructure to record structured, double-blind testing data during prospective clinical validation trials. Generating verified clinical evidence builds essential trust with pediatricians, healthcare systems, and insurance payors.

7. Launching And Scaling Platforms

Deployment is only the beginning of a medtech platform’s lifecycle. We build modular software architectures that allow your engineering team to update algorithms and scale infrastructure smoothly post-launch.

• Model Refinement: Continuously update machine learning weights using secure federated learning loops.
• Feature Expansion: Introduce longitudinal developmental tracking modules over time.
• EHR Scale: Expand direct integration hooks to connect with regional healthcare databases.

At IdeaUsher, we act as an extension of your technical team, helping you build, launch, and scale clinically validated AI platforms that capture significant market share.

Cost to Create an Autism Screening Tool Like EarliTec

Building an autism screening tool takes more than great software. It requires accurate AI models, reliable performance, and compliance with healthcare regulations. At IdeaUsher, we follow a phased development approach that helps founders validate their product early and scale with confidence while keeping development costs under control.

Costs By Development Stage

Dividing product creation into distinct phases aligns spending directly with your commercial milestones. We partner with teams at each stage, engineering scalable codebases that transition smoothly from an early MVP into a fully compliant medical platform.

Cost Factors To Consider

Building healthtech software requires specialized engineering choices that directly affect your total budget:

• AI Model Complexity: Training machine learning algorithms to evaluate subtle eye movements, gaze latency, and non-verbal cues requires extensive data processing pipelines.
• Hardware Interoperability: Integrating tablet cameras or custom eye-tracking hardware mandates specialized hardware abstraction layers.
• EHR & Workflow Integration: Linking your platform to systems like Epic, Cerner, or Netsmart using FHIR protocols increases engineering scope but accelerates clinical adoption.
• Regulatory Track (SaMD): Software designed for FDA 510(k) clearance demands comprehensive design history files (DHF), verification testing, and quality management protocols (ISO 13485).

At IdeaUsher, we simplify these decisions, providing clear technical choices that protect your runway while maintaining high software standards.

Hidden Operational Costs

Beyond initial software development, long-term commercialization involves ongoing operational expenditures.

• Clinical Validation Trials: Gathering double-blind trial data to prove algorithmic accuracy requires funding institutional review board (IRB) studies and research site partnerships.
• Cloud Infrastructure & AI Compute: High-volume video analytics and HIPAA-compliant cloud storage incur recurring monthly infrastructure costs ($2,500 – $8,000/month as patient volume grows).
• Regulatory & Audit Fees: FDA submission fees, annual quality audits, and specialized cybersecurity penetration testing require dedicated annual reserves ($30,000 – $75,000/year).
• Maintenance & Algorithm Tuning: AI models require continuous retrain loops using new clinical data to prevent drift and maintain high diagnostic sensitivity.

Revenue Opportunities for Autism Screening Platforms

Building a digital autism diagnostic platform takes more than AI development. Clinical validation, regulatory compliance, and accurate screening technology all shape the overall cost. Below, we break down the main development expenses and the factors that influence your investment. 

1. SaaS Subscriptions For Clinics

Subscription licensing gives autism screening platforms a steady source of recurring revenue. Healthcare providers pay monthly or annual fees to access the software, with plans that scale based on clinic size, the number of users, or the features included. This model makes it easier for organizations to expand their usage as they grow.

Linus Health follows a similar approach by offering its digital cognitive screening platform through subscription plans. The company has raised nearly $65 million in funding and is estimated to generate $10–15 million in annual subscription revenue. Its pricing is designed to serve everyone from small clinics to large healthcare networks with more advanced reporting and analytics.

2. Per-Assessment Usage Fees

A usage-based transaction model removes upfront cost barriers for smaller clinics or practices with irregular patient traffic. Providers pay a set fee only when they run an evaluation or generate an AI diagnostic report. This pay-as-you-go approach mirrors traditional medical supplies, allowing providers to treat software as a variable cost directly tied to patient visits.

A tool demonstrating this operational model is Autism 360. The platform offers specialized developmental tracking tools alongside direct per-assessment evaluation fees for parents and clinicians. Operating across international markets, Autism 360 generates an estimated $1 million to $5 million in annual revenue by capturing micro-transactions across thousands of individual user screenings.

3. Hospital Enterprise Licensing

Health networks, regional children’s hospitals, and public health programs require robust software deployments. Enterprise licensing agreements unlock large contract values by packaging customized platform instances with dedicated infrastructure, system integrations, and ongoing technical support.

A prominent commercial benchmark for enterprise-level scale is Cortica, an integrated neurodevelopmental health network that acquired platforms like Springtide Child Development to expand its tech-enabled clinical infrastructure. Cortica integrates diagnostic software across whole health systems, driving company revenues past $100 million through large-scale provider contracts, value-based care programs, and multi-site care delivery.

4. Insurance Reimbursement Pathways

Insurance reimbursement helps autism screening platforms grow by making AI-assisted assessments easier for providers to offer. When screenings are covered by insurers, clinics are more likely to use the platform as part of everyday care. Cognoa’s Canvas Dx follows this model. 

It is an FDA-authorized AI diagnostic tool that supports reimbursement through existing billing codes and has coverage from Highmark Health and several state Medicaid programs. The company is estimated to generate $10–25 million in annual revenue.

Build an Autism Screening Tool with IdeaUsher

Developing a high-impact digital diagnostic platform requires combining advanced computer vision with medical-grade software standards. At IdeaUsher, we partner with healthcare founders and investors to build AI-driven platforms that streamline pediatric workflows and accelerate early detection.

Experienced Healthcare AI Engineers

We bring deep technical expertise across medical computer vision, predictive analytics, and secure cloud infrastructure. Our engineering teams build software that connects directly into clinical settings, turning raw gaze tracking and behavioral data into actionable insights for pediatric teams. By engineering software that complies with strict healthcare standards, we ensure your application delivers high clinical utility alongside robust data privacy.

Strategy To Regulatory Deployment

We guide your project through every phase of the engineering lifecycle. From initial concept discovery to production deployment, our end-to-end development services ensure your platform is built correctly from day one. Our full-stack development covers:

• Product Strategy & Design: Building intuitive interfaces tailored for clinicians, parents, and young patients.
• AI & Computer Vision: Training machine learning algorithms on high-speed gaze tracking and behavioral biomarkers.
• System Interoperability: Integrating HL7 and FHIR standards for smooth data exchange with hospital EHR networks.
• Compliance Engineering: Enforcing HIPAA controls and preparing software documentation for FDA SaMD pathways.

Whether you need a lean MVP to validate early clinical concepts or an enterprise-grade platform ready for multi-center trials, we accelerate your timeline to market.

Architecture Built For Growth

A scalable architecture is essential for any digital health platform that plans to grow over time. We build modular software that makes it easy to add new clinical features and support more users without rebuilding the platform, helping your business expand from autism screening into broader neurodevelopmental care.

Conclusion

Building an autism screening tool like EarliTec is an opportunity to improve early autism detection while addressing a growing need in healthcare. Success depends on combining reliable AI, clinical validation, and a scalable platform that fits into real clinical workflows. With the right development approach, founders can build a solution that delivers value to both healthcare providers and families.

Things to Know About Autism Screening Tools