DataFinch API
DataFinch provides ABA practice software centered on clinical data collection and oversight. This page is an independent design exercise that asks what a well-designed DataFinch API could look like: the resources it would expose, the authentication it would need, and the workflows it could unlock. Below: a hypothetical endpoint design, the technical requirements a production implementation would face, the use cases programmatic access could serve, and where to start if your team needs this kind of access today.
This page is an independent analysis by Supergood of what a well-designed DataFinch API could look like. It draws on publicly available information, vendor materials, and general integration experience in this category. Nothing on this page describes an existing DataFinch product, and Supergood is not affiliated with or endorsed by the vendor. If the vendor offers an official API, we highly recommend it.
What is DataFinch?
DataFinch provides ABA practice software centered on clinical data collection and oversight. Its flagship product (Catalyst) helps BCBAs and technicians run treatment programs, capture trial-level data, log behaviors, visualize progress, and produce documentation that supports supervision and payer requirements. Common workflows include configuring skill acquisition and behavior reduction programs, collecting trials/probes at the point of care, monitoring mastery status against criteria, and generating session notes and reports.
Core product areas include:
- ABA Data Collection (skill acquisition programs, targets, trials/probes)
- Behavior Tracking (definitions, events, intensity/duration, ABC notes)
- Session Management and Notes (start/end times, activities, SOAP/encounter notes)
- Progress Visualization and Reporting (graphs, mastery status, trend analytics)
- Rosters and Permissions (learners, technicians, supervisors)
An API for a platform like this would naturally organize around its core data entities:
- Learners (clients/patients receiving ABA services)
- Staff (technicians/RBTs, BCBAs/supervisors)
- Programs (skill acquisition and behavior reduction)
- Targets (individual skills with phases like Baseline, Acquisition, Maintenance)
- Data Points (trial/probe results, prompt level, response correctness)
- Behaviors (definitions, functions, severity scales)
- Behavior Events (occurrences with timestamps, duration, intensity, ABC context)
- Sessions (scheduled or ad hoc encounters with notes and activities)
- Notes and Reports (SOAP, supervision notes, progress summaries)
The DataFinch Integration Challenge
Organizations rely on DataFinch daily, but turning portal-based ABA workflows into automated pipelines is hard:
- Limited official API access: Many users report a lack of open, public APIs; exports and reporting often happen via portal pages or batch files
- Portal-first data capture: Trial-level data, graphs, and behavior events live behind web UIs, making headless automation brittle without careful reverse engineering
- Complex permissions: Role-based access (technicians vs supervisors) and learner assignment rules require careful session handling
- Data granularity: Trial/probe records, prompt hierarchies, and mastery criteria must be preserved precisely for clinical integrity
- Scheduling and EHR silos: Clinics frequently request tighter scheduling, authorization, and billing integrations to eliminate double entry
What a DataFinch API Could Look Like
If DataFinch exposed a modern, general-purpose API, the integration challenges above suggest what it would need to get right. This is a design sketch, not documentation of anything that exists today:
- First-class authentication: session handling with support for MFA and enterprise sign-on where the platform uses them
- Consistent resources: normalized JSON schemas and pagination across the platform's core objects
- Reliable writes: idempotency keys and validation that mirrors the platform's own workflow rules
- Entitlement awareness: endpoints scoped to what each customer's licensing actually permits
The endpoint sketches, technical requirements, and use cases below flesh out this hypothetical design.
How AI agents could connect to software like DataFinch: MCP servers for software without a public API →
Need This Kind of Access Today?
If your team needs this kind of access today, Supergood builds integrations on request, one customer at a time. We act at the direction of our customers, within the access they already hold. Customers bring their own accounts, licenses, and entitlements. If the vendor offers an official API, we highly recommend it.
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Potential API Endpoints
Authentication
/sessionsWould establish a session using credentials. MFA challenges (SMS, email, TOTP) would need first-class support. Would return a short-lived auth token.
Learners
/learnersWould retrieve learner profiles with demographics, assignments, and basic clinical context. Use filters to scope to subsets.
Skill Targets and Data Points
/targetsWould list skill acquisition targets and their current phase, mastery criteria, and performance summary.
Skill Targets and Data Points
/targets/{targetId}/data-pointsWould create a trial/probe record for a target. Supports prompt level, correctness, and notes with audit trails.
Sessions and Notes
/sessionsWould create or update an ABA session with assigned staff, timing, activities, and note content. Attachments and location metadata are supported.
Use Cases
EHR-to-ABA Data Synchronization
- Push learner and staff rosters from your EHR/HRIS into DataFinch - Create sessions automatically from your scheduling system with assigned technician and location - Maintain a single source of truth for demographics and care team assignments
Target and Behavior Lifecycle Management
- Pull program and target catalogs with mastery criteria and current phase - Post trial/probe data points programmatically from mobile or custom workflows - Track behavior events and surface trends for supervisor review
Automated Notes and QA
- Assemble session notes based on collected data and activities - Flag missing trials, inconsistent prompts, or outlier behavior events - Route QA tasks to supervisors with linked evidence and audit trails
Outcomes and Reporting
- Retrieve graph-ready aggregates for targets and behaviors - Feed BI tools with near real-time data for cohort KPIs, mastery velocity, and intervention effectiveness - Align reporting with payer and supervision documentation requirements
Connect via No-Code Tools
Automate this platform from the no-code stack you already use.
Technical Requirements
Authentication
Would require username/password with MFA (SMS, email, TOTP); supports service accounts or customer-managed credentials
Response format
JSON with consistent resource schemas and pagination
Rate limits
Tuned for enterprise throughput while honoring licensing and usage controls
Session management
Would need automatic reauth and cookie/session rotation with health checks
Data freshness
Near real-time retrieval of sessions, targets, behavior events, and graph artifacts
Security
Encrypted transport, scoped tokens, and audit logging; respects DataFinch entitlements and compliance requirements
Webhooks
Optional asynchronous delivery for session saves, target updates, and behavior event notifications
Latency
Design target: sub-second responses for list/detail queries
Throughput
Design target: designed for high-volume trial/behavior event pipelines and reporting extracts
Reliability
Retry logic, backoff, and idempotency keys minimize duplicate actions
Versioning
Clear versioning and change management would matter as DataFinch evolves
Frequently asked questions
Availability of official interfaces varies by product, plan, and licensing. Many platforms in this category gate access behind partner programs or paid modules, and there is often no broadly available, self-serve public API. Check the vendor's developer resources for current offerings.
The hard parts would be authentication (MFA, session management, enterprise controls), consistent schemas across the platform's products, and write semantics that reconcile the way the platform's own workflows do.
No. This page is an independent analysis by Supergood and is not affiliated with, sponsored by, or endorsed by the vendor. All product names and trademarks belong to their respective owners and are used for identification only. Nothing here documents an actual DataFinch product or service.
Supergood acts at the direction of its customers, within the access those customers already have. We respect each customer's agreements with their software vendors, and how those agreements apply to a customer's use is a determination the customer makes. If the vendor offers an official API, we highly recommend it.
Supergood builds managed API access to enterprise software for customers on request, scoped to each customer's own licensing and entitlements. If your team needs programmatic access to a platform like this, schedule an integration assessment to discuss options.