Forward deployed engineering for ABA

AI, built intoyour operations.

Forward deployed engineering means working directly with the engineer who builds your software: inside your workflows, connected to your systems, and improved as your team uses it. Start with one focused build.

Building across the operations of a top 5 ABA provider nationally.

The opportunity · Illustrative project targets

30%less intake administrationINTAKE & ACCESS
20%fewer uncovered sessionsSTAFFING & CAPACITY
40%less documentation timeCLINICAL WORKFLOWS
2×faster access to answersKNOWLEDGE & OPERATIONS
OUR CAPABILITIES

Less friction.
More room for care.

We work alongside your operators to build the intelligence behind intake, capacity, and clinical work. Connected to your systems. Useful to your people.

INTAKE & ACCESS

A clearer path into care.

Connect document collection, insurance, clinical review, consent, and scheduling. Give families a clearer next step and staff a workflow they can follow through.

Document intelligence · Review routing · Systems integration

STAFFING & CAPACITY

Make capacity actionable.

Bring clinical policy, schedules, space, and staffing into the same decision. Explore feasible options, understand the constraints, and give operators a useful place to act.

Constraint optimization · Session coverage · Growth scenarios

CLINICAL WORKFLOWS

Support the work around care.

Prepare source data, assist with documentation, and build structured checks into existing tools. Keep clinical judgment and final review with the people responsible for care.

Source-informed drafting · Quality checks · In-workflow assistance

Beyond these three: knowledge assistants, workforce intelligence, and data and legacy-system modernization.

Explore selected work

SELECTED WORK

Built for complexity.
Used by people.

An inside view of our work with a top 5 ABA provider nationally. Three workflow studies show where software meets the decisions people make.

01 / Staffing & capacity

Turn capacity into possibility.

Optimization and operational intelligence that connect clinician capacity, technician coverage, and center growth.

Weekly capacity

Sample scenario

See where the week gets tight.

Planned seat occupancy · 2-hour blocks

Illustrative occupancy of planned seats in a sample week, in percent. Rows are 2-hour blocks starting at the listed time. The outlined 2 pm row is the staffing-review band, with 90 to 100 percent occupancy.
Start timeMonTueWedThuFri
8 am20%35%40%25%30%
10 am65%75%85%80%70%
Noon70%80%90%85%75%
2 pm90%95%100%95%90%
4 pm80%90%95%90%85%
6 pm35%45%50%40%30%

Occupancy (%) Low → high

  1. 0–24 percent
  2. 25–49 percent
  3. 50–74 percent
  4. 75–89 percent
  5. 90–100 percent
Center Capacity · A week in the buildingIllustrative UI study. Occupancy values are a sample scenario, not a staffing plan or client result.

02 / Intake & access

A better front door to care.

An intelligent intake journey connecting families, clinical teams, and the systems behind access to care.

Family intake

Sample scenario

Where the intake path narrows.

Four selected checkpoints · families reaching each stage

Two illustrative intake paths. Path A starts with 36 families, then 27 reach context, 6 reach documents and 2 reach scheduled. Path B starts with 20, then 16, 2 and 0. Bar lengths show the share of each path’s starting cohort. The largest decrease in the number of families between adjacent selected stages occurs between context and documents in both paths.
Selected stagePath A36 at startPath B20 at start
01Started
36
20
02Context
27
16
03Documents
6
2
04Scheduled
2
0

Bars show the share of each path’s starting cohort.

Look closer at the document handoff.

Context → documents: 27 → 6 on Path A; 16 → 2 on Path B.

Family Connect · Intake pathsIllustrative UI study. Selected stages and sample counts explain the workflow; they are not client results.

03 / Clinical workflows

Give clinicians their focus back.

Source-informed AI assistance for clinical documentation, structured quality checks, and everyday clinical workflows.

Clinical review

Sample scenario

Keep the source in view.

Source excerpt

“A visual prompt was provided to begin the task.”

Fictional session note · p. 2

Source-linked comparison

Current wording

The task began independently.

Suggested wording

The task began with a visual prompt.

The clinician decides.

Check the source. Keep, revise or reject the suggestion.

Fictional wording change. The final note remains a clinical judgment.

Clinical Assistant · Source to suggestionIllustrative UI study with fictional wording. It explains a review pattern, not clinical validity or an automated decision.

CONNECTED TO YOUR EXISTING WORLD

Azure AI. Salesforce. Google Workspace. Care platforms. We connect intelligence to the systems your team already runs on.

HOW WE WORK

Start focused.
Stay close to the work.

Begin with a focused build. Continue working directly with Jay as your workflows, systems, and priorities evolve.

01–03 · FIRST BUILD

Scope. Build. Pilot.

04 · ONGOING

Embedded engineering.

Feedback from use shapes what we build next.

FOCUSED FIRST BUILD

01 / 04

A focused place to start.

We map the workflow, data, and integration boundaries with the people doing the work. Together, we define the first build and how to evaluate it.

  • Workflow map

    Handoffs, exceptions, and points of friction

  • Data and integration review

    Available context, system boundaries, and access

  • A focused starting point

    A practical scope and a way to judge its value

Agree on the problem and the decisions people need to retain.

ABOUT NEUROMNIA

Built around ABA.
Designed with people.

Neuromnia brings forward deployed AI engineering to ABA organizations: direct collaboration with the engineer building and improving your software, from a focused first build to ongoing engineering.

The work spans family intake, clinician capacity, technician coverage, clinical documentation, and organizational knowledge. Each workflow fits into the systems and decisions your organization already depends on.

PRACTICAL BY DESIGN

Start with the operating context.

Understand the workflow, the available data, and the rules people already work within.

Make the reasoning clear.

Use source context, explicit constraints, and meaningful evaluations so teams can question an output.

Keep people in the decisions.

Define review points, exception handling, and clear ownership around consequential actions.

THE ENGINEER BEHIND NEUROMNIA

Portrait of Jay Gupta

Jay Gupta

Co-founder & Principal Engineer

Forward deployed AI engineering for ABA

Work directly with Jay.

Jay brings enterprise AI and mathematical optimization experience to ABA operations. Before Neuromnia, he led client data science and AI for pricing at JPMorgan Chase. His earlier work at Citi spanned decision science and digital analytics. Today, he works directly with ABA teams to build and integrate software around their workflows and existing systems.

Master of Science in Financial Mathematics University of Edinburgh

For a first conversation, bring one workflow bottleneck, the systems involved and the change you want to make.

Neuromnia’s earlier ABA AI work · Meta, October 2024 (opens in a new tab)

“I wish more Product Leaders possessed Jay's hybrid skill set of business strategy, data science and people management.”

FROM PRIOR COLLABORATION

Joseph R. Zweier, FRM

VP, Area Product Owner
JPMorgan Chase & Co

Read the LinkedIn recommendation (opens in a new tab)

LET’S FIND THE NEXT STEP

What is slowing
your team down?

Talk directly with Jay about a workflow bottleneck, the people involved, and the systems you use. Explore a focused first build and how ongoing engineering could support what follows.

A 30-minute conversation about the workflow and a possible starting point. Bring the operational context; keep patient-identifying or sensitive clinical information out of the initial booking and email.

BEFORE YOU BOOK

Good questions, clear starting points.

Do we need to replace our existing systems?

Usually, the best starting point is connecting what you already have. We build around your care platform, CRM, documents, and staff workflows, then modernize the parts that create the most friction.

Where should an ABA organization start with AI?

Start with an expensive, repeated operational problem: intake coordination, staffing coverage, documentation, or finding reliable answers. We help identify a focused use case, define the right success measures, and get a working solution into your team's hands.

What does forward deployed engineering mean?

You work directly with the engineer building the software. At Neuromnia, that is Jay—from understanding the workflow to building, integrating, deploying, and improving it. The work connects AI to the systems, constraints, and decisions already in use at your organization.

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