Otax
Case studies

Systems in production. Numbers we can defend.

A selection of engagements — the challenge, the system we shipped, and what changed in the business.

Healthcare·Case study · 01
Northwind Health

Automated intake and triage for a 12-clinic network.

Challenge

Front-desk staff spent 60% of their time on paper intake, insurance verification and appointment routing — creating 40+ minute wait times and burning out the team.

Solution

Deployed a voice AI intake agent integrated with the EHR, plus an automated triage workflow that scored each patient interaction and routed to the right specialist queue.

Technology used
OpenAIElevenLabsTwilion8nSupabase
Business impact
-71%
Wait time
218
Staff hours saved / week
+34pt
Patient satisfaction
Logistics·Case study · 02
Loop Logistics

AI dispatch and shipment-exception automation.

Challenge

Dispatch team drowned in 800+ daily shipment exceptions across 14 carriers, each requiring judgment and manual follow-up.

Solution

Custom AI classification pipeline that reads exception events, decides remediation, and executes carrier-specific workflows automatically — with human escalation only for edge cases.

Technology used
AnthropicPythonPostgreSQLn8n
Business impact
68%
Exceptions auto-resolved
-22%
Cost per shipment
3x volume
Dispatcher headcount held flat while
Financial Services·Case study · 03
Meridian Advisory

Compliant document AI for a wealth advisory firm.

Challenge

Onboarding a new client required 6–9 days of manual document processing — statements, KYC, custody forms — with strict regulatory review.

Solution

A private document AI pipeline with role-based review queues, full audit trail and compliant handoff to the client relationship team.

Technology used
OpenAI VisionPythonPostgreSQLAWS
Business impact
6 days → 11 hours
Onboarding time
92%
Straight-through processing
-78%
Manual review load
Real Estate·Case study · 04
Arbor & Co.

24/7 lead qualification and appointment booking.

Challenge

A high-volume brokerage was losing 30%+ of after-hours leads because there was no one to respond and qualify them in time.

Solution

A conversational agent trained on their listings, integrated with the CRM and calendar — qualifying every inbound lead and booking showings the moment they came in.

Technology used
OpenAIHubSpotCal.comNext.js
Business impact
+3.4x
After-hours conversions
8 min → 12 sec
Speed-to-first-response
+412
Booked showings / month
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