Hekavor

Taking the Patient History With AI, Before the Visit Begins

AI Patient Intake
Working Differential
Chart-Ready Notes
Patient & Provider Apps
HIPAA Compliance
Mari is Hekavor’s AI medical assistant. It runs a physician-level patient history before the visit begins, builds a working differential, and hands the doctor a chart-ready note. Everything that follows rests on that detail.
Topflight took Hekavor’s working prototype to production across two apps, a patient intake and a provider portal, on a HIPAA-compliant backend, in time for the founder’s first conference.

By the Numbers

2 apps
A patient intake and a provider portal in one system
On time
Delivered for the founder’s first conference
5.0
Clutch review rating across quality and schedule
~80%
Of a diagnosis rests on the patient history Mari automates
Where Mari Fits

Building Primary Care’s Pre-Encounter Layer

Hekavor is developing AI-assisted tools for primary care. Founded by Adrit Lath and Dr. Sara Rotner in Mountain View, California, the company is building the pre-encounter clinical intelligence layer. Its assistant, Mari, handles the opening conversation of a visit.
Asks what is wrong and what else is going on
Returns the first ten minutes of each appointment
Feeds diagnosis decision support
Validated on hundreds of physician-developed cases
Adrit had already built a working prototype for specific chief complaints. To reach the general population, he needed a partner who had shipped HIPAA-compliant healthcare apps before.

Four Problems Between Prototype and Production

01

Productionize a Working Prototype

Move from a prototype built for a handful of chief complaints to a production-grade app ready for the general population.
02

HIPAA With LLMs in the Loop

Patient data flows to and from large language models, which meant business associate agreements and secure data handling.
03

Two Apps, One System

A patient-facing intake named Mari and a provider portal, both built around the core LLM logic that Hekavor owns and manages.
04

Groundwork for EHR Integration

Lay the technical and compliance foundation for integrating with major systems like Epic and Cerner, central to the long-term plan.

Solution: From Patient Intake to a Chart-Ready Note

Six pieces move a patient from the first question to a note the physician can chart, across two apps.
01

Mari AI Patient Intake

A physician-level history across a widening set of chief complaints, asked as grouped multiple-choice questions.
02

Provider Portal

Providers manage patients, schedule Mari links, review summaries, and track usage from one back office.
03

Working Differential and Note

Mari mirrors how physicians document: present illness, review of systems, past history, a differential, and next steps.
04

Roles and Permissions

Distinct roles for providers and assistants, with granular control over links, records, and case details.
05

Customizable Notifications

Per-patient control over Mari email content and notification channels, across both SMS and email.
06

Usage Tracking and Error Logs

An admin view into system health, user interactions, and technical errors, so issues surface before users feel them.

Under the Hood

Engineering an LLM Intake That Doesn’t Skip a Question

Challenge

The core IP, the physician-developed question logic, stays with Hekavor. Mari runs a hybrid design: deterministic question pathways the conversation follows reliably, with a large language model layered on for natural-language flexibility.
1
Patient Intake
A physician-level history, one grouped question at a time.
2
Defensive Handling
Patches catch skipped questions and hallucinated facts.
3
HIPAA-Compliant LLM Pass
Patient data moves through Azure OpenAI under a BAA.
4
Structured Note Output
A chart-ready note with a working differential and next steps.

Running an LLM on Patient Data, the Compliant Way

Patient data moves to and from an LLM here, so every tool in the stack had to handle PHI under a BAA and still let a small team ship fast.
React
Patient and provider web apps
FastAPI
Backend API
Azure OpenAI
LLM engine, BAA in place
Supabase
HIPAA-compliant Postgres
Twilio + SendGrid
Patient SMS and email
Render
Dev, staging, production

On Time for the Conference

Hekavor is an early-stage company, so the early wins matter: a clean launch, a first set of interested users, and a partnership that kept going.
On-time delivery

Conference-ready

The production app was finished in time for the founder’s first conference, and the demo’s opening day ran flawlessly.
Pipeline started

~10 prospects

Around ten people asked to learn more before signing up, with trial calls scheduled over the following weeks.
Ongoing partnership

Phase 2

The engagement moved into a maintenance phase and a planned Phase 2, after the team hit a deadline that triggered a delivery bonus.
5.0
Quality
5.0
Schedule
4.5
Cost
5.0
Willing to Refer

Turning an AI Prototype Into a Compliant Product?

We turn healthcare AI prototypes into production-grade, compliant apps, from your core IP to launch, in a single quarter or two.
Rapid Prototyping vs Standard Development Timeline
Phase
Standard Process
AI Rapid Prototyping
Discovery
2-4 weeks
1 week
Design
4-8 weeks
1 week
Development
12-20 weeks
2 weeks
Testing & Polish
4-6 weeks
1 week
Total
22-38 weeks
4 weeks
85%
Faster to market
$135M+
Raised by clients
Zero
Rebuild required
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