Our Work

Live demos and case studies showing how we build production AI systems — from document intelligence to operational diagnostics.

Live DemoNew

Regulatory Gap Analysis

Regulated teams spend weeks manually reviewing controlled documents against FDA 21 CFR Part 11. This system delivers evidence-backed regulatory gap analysis with specific remediation guidance — not a chat response.

What This Demonstrates

37-requirement regulatory checklist (FDA Part 11)
Evidence-backed gap analysis of controlled documents
Cross-document contradiction detection
Batched LLM assessment with structured output
Real-time SSE progress streaming
Specific remediation guidance for every finding
Follow-up chat grounded in analysis context
Production architecture, not a mockup
Compliance Copilot — Analysis Dashboard
Coverage Overview
17 Met9 Partial8 Gap3 N/A
Gap§11.10(k)(2) — No open system controls documented
Partial§11.10(e) — Audit trail covers records but not signatures
CriticalContradiction: annual vs. semi-annual access reviews
Pharma Intelligence — Risk Scan
Research signals

Data Integrity

Audit trail language cited in 14 recent letters

OOS Investigations

Phase 2 investigation criteria not defined

Lab Controls

Reference standard procedures appear current

CAPA

No CAPA SOP retrieved for this category

Live DemoPharma

Pharma Intelligence Copilot

Cross-references 870+ FDA warning letters against a company's internal quality documents using two-corpus RAG. Surfaces enforcement risk signals across 10 violation categories — with a live Box integration for the internal document corpus.

What This Demonstrates

Two-corpus RAG: enforcement data vs. internal docs
870+ FDA warning letters (CDER/CBER, 2019–present)
Live Box JWT integration — documents stay in Box
10 violation categories scanned in parallel
SSE streaming — signals appear as they complete
Context-aware follow-up chat on each signal
Box webhook re-ingestion when documents change
Research signals only — enforces human review posture
Live DemoGolf / Sports

USGA Rules Expert

A cited AI assistant built on the 2023 Rules of Golf — the official USGA rulebook. Ask any rules question and get an accurate answer with specific rule citations.

What This Demonstrates

Cited answers from 469 document chunks
Retrieval-augmented generation (RAG)
Semantic + hybrid search
Source transparency on every response
Streaming responses for fast UX
Rate limiting and usage controls
Evaluation suite for quality assurance
Production deployment on Vercel
USGA Rules Expert — Live
Q
Can I remove loose impediments in a bunker before my shot?
AI

Yes. Under Rule 12.2a, you may remove loose impediments in a bunker without penalty. However, under Rule 12.2b, you must not deliberately touch sand to test its condition...

Sources: Rule 12.2a, Rule 12.2b, Definition of "Loose Impediments"

Industrial Asset Health — Fleet Dashboard
Engine 39Critical

10 cycles remaining

Engine 13Warning

41 cycles remaining

Engine 23Watch

76 cycles remaining

Engine 46Healthy

179 cycles remaining

Live DemoIndustrial

Industrial Asset Health Copilot

Fleet-level health monitoring and AI-assisted diagnostics for rotating machinery — demonstrated on NASA's C-MAPSS turbofan engine degradation dataset. Sensor trend analysis, anomaly detection, remaining useful life estimation, and evidence-backed diagnosis.

What This Demonstrates

Fleet-level health monitoring with risk-sorted dashboard
21-channel sensor trend analysis with anomaly detection
Remaining useful life estimation with fleet comparison
AI diagnostic copilot citing specific sensor readings
Historical case matching across the engine fleet
Public NASA C-MAPSS benchmark data — fully reproducible
Same data-to-diagnosis architecture as client engagements
Production-grade streaming UI with rate limiting
Live DemoOperationsNew

AI Triage Workbench

A multi-step AI pipeline for operational issue triage — from intake through analysis, evidence retrieval, human review, routing, and full audit trail. This is what a managed AI workflow looks like in practice.

What This Demonstrates

Multi-step AI pipeline with human checkpoint
Structured classification with honest uncertainty
Evidence from technical docs + historical cases
Accept / modify / escalate / override review workflow
Full audit trail on every issue
Managed-ops health panel with system metrics
Safety-critical detection and auto-escalation
Scenario-agnostic architecture, industrial demo loaded
AI Triage Workbench — Issue Queue
INC-0101Closed

Compressor bearing vibration trending up

INC-0104Review

Elevator leveling inconsistent floors 3-5

INC-0105Review

Unusual smell near transformer room B

INC-0108New

AHU-7 supply fan bearing temp alarm

847 triaged · 78% accepted · 12 min avgManaged by JustInternetAI

Under the Hood

The production architecture pattern behind our AI systems — from document intelligence to operational diagnostics

1

Data Ingestion

Documents are parsed and chunked with structural awareness. Sensor telemetry is normalized into time-series records. Both are indexed for retrieval.

2

Retrieval & Analysis

Hybrid vector + keyword search for document corpora. Rolling statistics, baseline comparison, and anomaly detection for operational data.

3

Evidence-Backed AI

Every AI output cites its sources — document sections, sensor readings, cycle numbers, or fleet comparisons. No black-box answers.

4

Quality & Monitoring

Evaluation suites, interaction logging, rate limiting, and quality metrics ensure systems maintain accuracy in production.

The Same Principles, Your Data

Every system we build uses proven patterns — adapted to your specific data, workflows, and operational requirements. We build it, host it, and manage it so you don't have to.

📋

SOP & Policy Assistant

Help teams find the right procedure instantly, with citations to the exact SOP section and revision.

🔧

Equipment Diagnostics

AI copilots that analyze equipment telemetry, event logs, and fault history to rank probable causes with supporting evidence.

⚖️

Regulatory & Compliance Q&A

Answer compliance questions with cited references to specific regulations, guidance documents, and internal policies.

📊

Operational Data Platforms

Centralize fragmented data from equipment, sensors, and service records into searchable, queryable systems that support teams can act on.

📦

Internal Knowledge Base

Stop losing institutional knowledge when experienced employees leave. Make it searchable and citable.

🏥

Medical & Clinical Intelligence

Help clinical and quality teams navigate complex guidelines and cross-reference internal documentation with source-backed answers.

Have a Problem That Looks Like This?

Tell us what's taking too long — searching documents, diagnosing equipment, reviewing compliance, or making sense of operational data. We'll tell you if AI can actually help.

Describe Your Challenge