Work
Real systems.
Measurable results.
Every project follows the same pattern: understand the problem, build the system, prove it works. Here's what that looks like in practice.
AI agents deployed
industries served
pages of content generated
system uptime
Steinmetz Real Estate
Real Estate / William Raveis
18 AI agents running a 2,000+ page real estate platform.
The problem
A growing real estate practice needed technology that didn't exist — market analysis across dozens of neighborhoods, automated property research, client communication at scale, and business intelligence that kept pace with a fast-moving market.
18
AI agents deployed
2,000+
pages of content
30+
neighborhoods covered
24/7
system uptime
The process
Built a complete real estate platform from scratch using the multi-agent framework
Deployed 18 specialized AI agents across market analysis, property research, client communication, and operations
Integrated with MLS data, public records, market APIs, and communication tools
Created neighborhood-specific intelligence covering pricing, schools, demographics, and market trends
The payoff
A complete AI-powered real estate operation — from lead capture to market analysis to client communication — running autonomously 24/7. The platform that proved the framework works in production.
Blank Industries
Manufacturing / Business Intelligence
Unified intelligence from 6 disconnected systems.
The problem
Critical business data trapped in 6 disconnected systems — ERP, CRM, inventory, shipping, accounting, and HR. Leadership making decisions on gut feel instead of data. Monthly reporting took a full-time analyst 2 weeks to compile.
6→1
unified data source
90%
faster reporting
Weekly
AI-generated insights
Real-time
anomaly detection
The process
Assessed all 6 data sources, mapped dependencies, and identified the highest-value integration points
Built AI agents that pull, normalize, and cross-reference data from all systems in real time
Deployed an executive dashboard with AI-generated weekly insights and anomaly detection
Created automated alerts for inventory thresholds, cash flow projections, and operational KPIs
The payoff
Leadership went from monthly gut-feel decisions to weekly data-driven strategy. The analyst who used to compile reports now focuses on strategic analysis.
KabbalahQ.ai
Education / AI Learning Platform
An AI-powered learning platform that adapts to each student.
The problem
A complex educational domain with thousands of interconnected concepts, but no way to guide learners through it effectively. Traditional course structures didn't work — every learner needed a different path.
1,000+
interconnected concepts
Adaptive
learning paths
AI-powered
content generation
Personalized
per learner
The process
Mapped the entire knowledge domain into a structured graph of concepts and relationships
Built AI agents that assess each learner's current knowledge and generate personalized learning paths
Created an adaptive quiz system that adjusts difficulty based on demonstrated understanding
Deployed content generation agents that produce explanations tailored to each learner's background
The payoff
A learning platform where no two students have the same experience. AI agents continuously adapt content, pacing, and difficulty to match each learner's progress and style.
ButcherBox
D2C / Subscription E-Commerce
73% of subscription inquiries handled autonomously.
The problem
A rapidly growing D2C meat subscription service drowning in customer inquiries — order modifications, delivery schedules, product questions, cancellation requests. Support team scaling linearly with subscriber growth, eating into margins.
73%
inquiries handled by AI
<2min
avg response time
40%
support cost reduction
94%
customer satisfaction
The process
Analyzed 12 months of support tickets to identify the highest-volume, most automatable inquiry types
Built AI agents specialized in subscription management, delivery coordination, and product knowledge
Deployed intelligent routing that handles routine requests autonomously and escalates complex cases
Integrated with order management, shipping, and CRM systems for real-time data access
The payoff
Support costs decoupled from subscriber growth. The AI handles routine inquiries instantly while the human team focuses on complex issues and relationship building.
Rosen Media Group
Media / Content Production
2.5x content output without adding headcount.
The problem
A media company producing content across multiple formats and channels, but bottlenecked by the editorial process. Writers spending 40% of their time on research and formatting instead of actual writing. Distribution across platforms was manual and inconsistent.
2.5x
content output
60%
less research time
5
platforms auto-published
0
additional headcount
The process
Mapped the full content lifecycle from ideation to distribution across all channels
Built AI agents for research synthesis, content formatting, SEO optimization, and cross-platform distribution
Created an editorial dashboard showing content pipeline status, performance metrics, and scheduling
Deployed automated distribution agents that reformat content for each platform's requirements
The payoff
Same team, 2.5x the output. Writers focus on storytelling while AI handles research, formatting, optimization, and distribution. Content reaches every platform within hours of creation.
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