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Software · AI · Healthcare operations

Engineering intelligent systems for the real world.

We design and build the web, mobile, cloud and AI software that turns complex operations — from customer support to the healthcare revenue cycle — into reliable digital workflows.

One team
Product, web, mobile, cloud and AI engineering
Healthcare depth
Front office through the full revenue cycle
Human in the loop
Review built into every AI workflow we ship
You own it
Documented architecture, code and infrastructure

Zoom into the system

Demo data

Northbridge Family & Orthopedic Care · Main St.

Thu 08:52 · 42 visits today

3 checking in

Front desk

Kiosk + two staff

8 waiting

Waiting room

Average wait 11 min

In visit

Exam 1

Dr. Okafor

In visit

Exam 2

Dr. Reyes · knee

Roomed

Exam 3

P. Shah

1 queued

Imaging

X-ray

Charting

Records

EHR · visit notes

Billing office

Two billers · claims, eligibility, denials

Practice OS

Level 01 / 05 · Clinic

A clinic on a Thursday morning

Two locations, 42 visits today. Every room produces work that ends up as a claim.

What we do

We don’t just build software. We engineer the systems your operations run on.

One partner from the first conversation about the problem to the system that keeps improving in production. No hand-offs between an agency, a cloud vendor and an AI consultancy.

See how we work

  1. Step 01

    Problem

    What is slow, manual, error-prone or impossible today — measured, not assumed.

  2. Step 02

    Strategy

    Where software, automation or AI actually moves the needle, and in what order.

  3. Step 03

    Product design

    Workflows and interfaces designed with the people who will use them.

  4. Step 04

    Engineering

    Web, mobile and backend built to be maintained, not just demoed.

  5. Step 05

    AI integration

    Models connected to your data, your rules and a human checkpoint.

  6. Step 06

    Cloud

    Infrastructure as code on AWS, sized for the workload.

  7. Step 07

    Deployment

    Automated releases with health checks and a rollback path.

  8. Step 08

    Automation

    Events trigger work; people handle the exceptions.

  9. Step 09

    Optimization

    Monitoring and usage data drive the next iteration.

Capabilities

One technology partner. Six engineering disciplines.

Complex systems fail at the seams between teams. We keep product, web, mobile, cloud, DevOps and AI under one roof — so the seams are our problem, not yours. Hover the system to see what sits behind each node.

CoreYour business system

› system.inspect("ai")

01/08

AI — Models wired into real workflows

LLMs · AI agents · Intelligent automation · AI copilots

Product engineering

From problem statement to a shipped, supported product.

  • Product strategy
  • UX / UI design
  • Architecture
  • Full-stack development
  • QA & test automation
  • Deployment & support
decisions/0007-claims-queue.mdexample
1## Context2Billers work denials from 3 portals + a spreadsheet.3## Decision4One queue, ordered by $ at risk × days to filing limit.5## Consequences6+ single source of truth  − needs 835 parsing first

AI that actually does something

AI isn’t the product. It’s the intelligence inside the product.

AI becomes valuable when it is connected to the systems your business already uses — reading the input, reasoning over your data, acting through your software, and asking a person when it should.

workflow-runner

Event log

step 1/6

An inbound message becomes a resolved ticket without anyone copy-pasting between tools.

  1. 09:41:12inbox.received msg_7Hq2 from j.alvarez@…
Interactive demo · fictional data

AI in real businesses

The same pattern, different operations.

Find the manual workflow, connect AI to the data it needs, automate what's predictable and route the rest to a person. Pick an industry.

  1. 01 · Problem

    Front-office and billing staff spend hours on eligibility checks, faxed referrals and denial rework.

  2. 02 · Existing workflow

    Staff re-key data from faxes and portals into the PMS; denials are worked from spreadsheets.

  3. 03 · AI integration

    Document intelligence reads referrals and remits; denial reasons are categorized from CARC/RARC codes and claim context.

  4. 04 · Automation

    Eligibility runs before every visit; denials become routed tasks with the fix and deadline attached.

  5. 05 · Business outcome

    Less re-keying and fewer avoidable resubmissions, with staff time moved to exceptions.

Illustrative patterns. Outcomes describe potential operational benefit and depend on your data, systems and process.

Healthcare technology

Technology for the business of healthcare.

We build intelligent systems that connect clinical, administrative and financial workflows — from the first phone call to the final payment and the report that explains it.

Front desk · 08:52

Eligibility checked for 36 of 42 visits before patients arrived.

fictional demo data

01Front office

Patient

A patient reaches out by phone, portal, referral or text.

Where it breaks

Requests scattered across channels; callbacks missed.

What we build

  • Unified intake inbox
  • Online self-scheduling
  • Referral document intelligence
Healthcare technology

Practice management

One operational system for the practice.

Schedule, eligibility, claims and tasks in one place — with AI preparing the work and staff making the calls. Click through the screens.

Practice management systems
Northbridge Family & Orthopedic Care — Practice OS

Today

Thursday, September 12 · Main St. clinic

simulated activity

Appointments today

42

88% of capacity · 3 providers

Eligibility verified

36/42

2 need review · 1 inactive

Claims awaiting submission

18

4 flagged by scrubber

Outstanding A/R

$184,250

$19,700 over 90 days

Schedule

next 2h

  • 08:00Harper, Lena · Annual wellnessCompleted
  • 08:20Morales, Evan · Knee pain — newWith provider
  • 08:40Chen, Margaret · Follow-upRoomed
  • 09:00Novak, Daniel · Sick visitChecked in
  • 09:20Brooks, Tamara · Post-op checkScheduled
  • 09:40Singh, Arjun · TelehealthScheduled
  • 10:00Walker, June · Chronic careScheduled

AI review queue

  • Draft noteVisit summary drafted from structured intake — awaiting provider sign-off3
  • Claim checkDrug line without NDC detected before submission1
  • Denial triageDenials grouped by likely cause with suggested next step7

A/R aging

0–30
31–60
61–90
91–120
120+

Activity

  • Waiting for events…
Interactive demo · fictional data

Revenue cycle management

From patient encounter to payment.

Follow one $1,250 claim through eligibility, coding, submission, a partial payment, an AI-triaged denial, a staff correction and the final payment. Pause it, step through it, or click any stage.

RCM & medical billing
Claim CLM-24-08817

Morales, Evan · DOS 09/12 · Dr. Daniel Reyes

Crestline BCBS

Pre-visit
CodeServiceChargePaidStatus
No charges yet — the visit hasn’t happened.
Charged
$0.00
Paid
$0.00
Adjusted
$0.00
Patient
$0.00
Open
$0.00

Claim history · event 1/14

  1. System · Sep 11 · 16:02

    Eligibility verified

    270/271 returned active coverage. Copay $40 collected at check-in.

Interactive demo · fictional data

AI + medical billing

Practical AI for the billing office.

Not a promise of higher collections — specific capabilities that take repetitive work off your team's plate and put the right work in front of them first.

pre-submission review · CLM-24-08817

Patient demographics match 271
Diagnosis linked to every line
Modifier 25 supported by documentation
J1030 — NDC missing for this payer

Intelligent claim review

Flags potentially incomplete or inconsistent claim information before submission, so it's fixed once rather than reworked after a denial.

Missing info (CO-16)34
Authorization (CO-197)22
Eligibility (CO-27)18
Coding (CO-11)14
Timely filing (CO-29)6

sample distribution · fictional

Denial intelligence

Groups denials by likely cause using CARC/RARC codes and claim context, and surfaces patterns by payer and service.

  1. 1CLM-24-07702$2,140— 12 days to filing limit
  2. 2CLM-24-07415$1,380— payer usually pays by day 30
  3. 3CLM-24-06988$960— no response since submission
  4. rule: $ at risk × days to limit × payer lag

A/R prioritization

Orders open accounts by configurable rules — balance, age, payer behaviour, filing deadlines — using the data you have.

Document
EOB
Payer
Crestline BCBS
Claim #
CLM-24-08817
Paid
$540.00
Remark
M119

Document processing

Extracts relevant fields from EOBs, referrals, authorizations and correspondence, and routes them into the right workflow.

whenERA posted with denial
andamount > $250
thencreate task → billing queue
thenattach remark + suggested fix

Automated workflows

Predefined actions triggered by operational events: an ERA posts, a denial arrives, a claim ages past a threshold.

Why was Morales’ claim partially paid?

Three lines paid ($540.00). J1030 was denied with CO-16 / M119 — the drug line had no NDC. A correction task is assigned to R. Diaz, due today.source: ERA 0927-Asource: task T-3310

Staff copilot

Helps billing staff find information, summarize account history and navigate workflows — with sources shown.

weekly summary · Collections trended up across the quarter. Most new denials this month were CO-16 on drug lines for one payer; a scrubber rule was added on Sep 27.

Reporting intelligence

Turns large operational datasets into readable summaries and trends leaders can question.

Visuals use fictional sample data. Actual impact depends on your payer mix, data quality and workflows.

Case studies

What this looks like in practice.

Illustrative scenarios built from the kind of work we do — each with the problem, environment, architecture, AI and workflow. Clearly labelled; real, client-approved studies will replace them.

All case studies

Architecture

Under the interface, there's an engineered system.

Trace a request through clients, edge, services, data, AI and integrations. Hover any component to see what it does.

See the full technology picture

  1. Users

  2. Clients

  3. Edge

  4. Services

  5. Data

  6. AI services

  7. Integrations

  8. Cloud infrastructure

Mobile engineering

Apps that keep working when the signal doesn't.

A field app goes offline, keeps saving, reconnects and syncs — and the coordinator's screen updates. That's the engineering, not a paragraph about it.

Mobile development
9:41

Thursday

Today’s visits

Offline — working from device

  • R. Patel

    08:30

    14 Alder Ct

    ● pending upload

  • M. Okonkwo

    10:00

    221 Birch Rd

    ● pending upload

  • S. Lindqvist

    11:45

    9 Harbor Ln

Voice note → summary

BP 128/82, wound healing, no new meds. Follow-up in 7 days.

on-device draft · nurse reviews

Interactive demo · fictional app & data
  • Offline-firstLocal database; the app never waits for the network.
  • Realtime syncConflict-aware sync when the connection returns.
  • Push notificationsTargeted, actionable, and quiet by default.
  • AuthenticationBiometric unlock over secure, short-lived sessions.
  • AI featuresVoice notes summarized into structured fields.
  • Native integrationsCamera, documents, location — through native modules.
  • Background processingUploads and sync continue when the app is closed.

Web engineering

Web applications people run their day in.

Operational dashboards, customer portals and admin systems — built responsive from the component up. Resize the frame.

Web development
SaaS operations dashboard

Active users

1,284

last 24h

API p95 latency

182 ms

target < 300 ms

Workflow runs

9,410

37 need review

Deployment

v2.14.0

12 min ago · healthy

Shipments processed

12 weeks

Service health

  • apioperational
  • workersoperational
  • carrier-syncdegraded · retrying
  • notificationsoperational
Interactive demo · fictional data

Enterprise inventory

One stock figure across every warehouse and channel.

A stock ledger behind every number, scanners at every physical step, and replenishment suggestions a buyer approves — connected to the ERP, WMS, storefronts and carriers you already run. Click through it.

Inventory management systems
Harbor & Pine Industrial Supply — Inventory

Network overview

3 warehouses · 6 SKUs shown · Thursday, September 12

simulated activity

Inventory value

$64,632

8,113 units on hand

Reserved for orders

1,791

22% of on-hand

Stock alerts

4

1 out · 2 low · 1 excess

Inbound on POs

648

2 open purchase orders

Needs attention

by warehouse

  • BRG-6204Low
  • HOS-12GExcess
  • HOS-12GOut
  • GLV-N100Low

Live activity

events

  • Waiting for events…
Interactive demo · fictional data

Cloud & DevOps

From commit to production, visibly.

Automated builds, tests, security checks, canary deploys, health monitoring and automatic rollback. Switch scenarios to watch a bad release get caught.

Cloud & DevOps
Release pipeline
  1. DeveloperPR #412 approved
  2. Gitmerge → main
  3. CI/CDpipeline #2291
  4. Buildimage api:3f9c2e1
  5. Tests412 unit · 38 e2e
  6. Securitydeps + image scan
  7. Deploycanary 10%
  8. Cloudhealth /readyz
  9. Monitoringp95, errors
  10. Logsstructured
  11. Alertson-call

Logs

    Health · p95 latency

    Live version

    v2.13.2

    Status

    releasing

    Interactive demo · fictional data

    Integrations

    Built to connect with what you already run.

    CRM, ERP, WMS, accounting, payments, e-commerce, carriers, EHR, PMS, clearinghouses, messaging and AI providers — through the interfaces each system supports.

    Your systemAPIs · events · adapters

    • Business

      • CRM
      • ERP
      • Accounting
      • Payments

      Keep the systems of record you already trust; we sync to them.

    • Healthcare

      • EHR
      • PMS
      • Clearinghouses
      • Eligibility (270/271)
      • Payers

      Through supported interfaces — HL7 v2, FHIR, X12, vendor APIs, SFTP.

    • Supply chain

      • WMS
      • E-commerce & marketplaces
      • Carriers & 3PL
      • Barcode & RFID
      • Supplier EDI

      Stock, orders and shipments kept in step across every system.

    • Communication

      • Email
      • SMS
      • Voice
      • Chat

      Messages as workflow events, not just notifications.

    • AI

      • LLM providers
      • Speech
      • OCR
      • Embeddings
      • Vector databases

      Provider-agnostic, so models can change without rewrites.

    • Infrastructure

      • Cloud
      • Storage
      • Monitoring
      • Analytics

      Observable from the first deploy.

    • REST
    • GraphQL
    • Webhooks
    • Event queues
    • SFTP
    • HL7 v2
    • FHIR
    • X12 837 / 835
    • X12 270 / 271
    • X12 276 / 277
    • EDI 850 / 856 / 810

    Integration categories we build for — not vendor partnerships. What’s possible with a given product depends on the interfaces its vendor supports.

    How we work

    A process with something to show at every step.

    Each step ends with an artifact you keep and a decision point where you can stop, adjust or continue.

    Idea to production

    01

    Discover

    Understand the business problem before proposing software.

    • Stakeholder and user interviews
    • Workflow and data mapping
    • Constraints: systems, compliance, budget

    You receive

    Problem brief + current-state workflow map

    Technology stack

    A focused stack, used deeply.

    Only what we genuinely build with. Pick a layer or hover a technology to see where it fits.

    Frontend

    Mobile

    Backend

    AI

    Cloud

    Infrastructure

    Databases

    Hover or focus a technology to see what we use it for.

    What can we build?

    Sketch your system in thirty seconds.

    Choose what you're building and what it needs. We'll assemble a conceptual architecture — then turn it into a real one with you.

    01What are you trying to build?
    02What does your system need?

    System blueprint

    Choose a project type to start assembling a system.

    Let’s turn this into an actual system.

    A conceptual starting point — we’ll refine it with you in discovery.

    Discuss your project

    Questions

    Common questions

    The things people usually ask before a first call.

    What does Revotech Labs build?

    Web platforms, mobile apps, cloud infrastructure and AI-powered systems — from SaaS products and internal business tools to practice management and revenue cycle software for healthcare. One team covers product, engineering, AI, cloud and DevOps.

    Do you only work in healthcare?

    No. Healthcare operations and RCM are a deep specialty, but we build for startups, SaaS companies and established businesses in finance, logistics, distribution and manufacturing, real estate, professional services and more.

    How do you integrate AI into an existing business?

    We start from a workflow, not a model: identify the manual step, connect AI to the data and systems it needs, automate what's predictable, and route exceptions to a person. Every AI feature ships with an evaluation set, monitoring and cost tracking.

    Can you integrate with our existing systems?

    Usually. We integrate through whatever each system supports — REST or GraphQL APIs, webhooks, file exchange, HL7 v2, FHIR or X12 for healthcare. We confirm what's available during discovery before committing to a timeline.

    Is your healthcare software HIPAA compliant?

    Healthcare systems we build are architected with privacy, access control, auditability and applicable regulatory requirements in mind, and we document data flows for your compliance team. We don't claim certifications we don't hold, and compliance also depends on how a system is operated.

    How do engagements work?

    Discovery first, then a narrow first release, then iterative delivery and ongoing improvement. Each stage ends with something you keep and a decision point to stop, adjust or continue.

    Who owns the code and infrastructure?

    You do. Code, infrastructure definitions and documentation live in your repositories and cloud accounts.

    Technical consultation

    Have a complex problem?

    Tell us what you’re trying to build, automate or improve. We’ll help you map the technology, architecture and execution path.

    Start a conversationExplore our work
    hello@revotechlabs.org

    1. 01

      You tell us the problem

      A few sentences about what you're building, automating or fixing.

    2. 02

      We map the system

      A working session on workflows, data, integrations and constraints.

    3. 03

      You get an execution path

      Architecture, phased scope and a realistic estimate — yours to keep.