Osman Janjua
Building production ML pipelines, fine-tuning domain-specific LLMs, and architecting multi-cloud infrastructure across AWS and Azure. Deep learning field extraction, computer vision inventory systems, 55-service orchestration, and end-to-end automation — from PyTorch model training to containerized deployment.
Capture
We sit with domain experts — founders, architects, CFOs, controllers — and extract the decision patterns they can't articulate. Structured interviews. Live observation. Decision journaling. MBTI-based cognitive profiling maps each stakeholder's decision style, so the model learns how they think, not just what they decide.
Train
Fine-tune foundation models on captured instinct data. QLoRA, RLHF, domain-specific tokenization. Training data is stratified by decision archetype — we weight examples by cognitive type so the model doesn't over-index on one thinking style. We don't train on generic web data — we train on the decisions that built companies.
Deploy
Production deployment on cloud infrastructure. Real-time decision support integrated into your existing workflows. Outputs are personality-tuned per audience — investor-facing docs match analytical profiles, sales copy speaks to experiential ones. A decision engine with the instinct of your best people.
Deep Dive: The Full Pipeline
Click any stage to see the technical breakdown, why it matters, and how the pieces connect.
Decision Pattern Extraction
Why this is the foundation everything else depends onEvery model is only as good as its training signal. Generic AI trains on the internet — broad but shallow. Instinct training starts with the specific decision patterns that made your organization successful. We extract what your best people do instinctively — the judgment calls they can't explain but always get right. Each expert is behaviorally typed during extraction — an analytical CFO's risk calculus is captured differently than a visionary founder's opportunity instinct, preserving the cognitive diversity that drives real organizations.
Pattern recognition
System intuition
Financial instinct
Execution patterns
100K+ signals codified into training-ready format
Foundation Model Fine-Tuning
Turning raw instinct data into a model that thinks like your teamWe don't build models from scratch. We take proven foundation models (Qwen 8B, Claude, open-source) and surgically adapt them using QLoRA — low-rank adapters that encode your organization's instinct without losing the model's general intelligence. Training examples are tagged with cognitive decision archetypes — the model learns that an operator's supply chain call and a strategist's market read are both valid but structurally different. The result: a model that reasons like GPT-4 but decides like your best operator.
Qwen 8B / Claude / OSS
Your instinct data
Your organization's decision intelligence — encoded as weights
Production Deployment & API Layer
From trained model to live endpoints your systems can callA model sitting on a laptop is a demo. A model behind an API with auth, rate limiting, failover, and logging is infrastructure. We deploy across Cloudflare Workers, GCP Cloud Run, and Azure — multi-region, sub-200ms, with monitoring and rollback built in.
Sync queries
Stream output
Event-driven
Document stacks
UI, Automation & Document Stack Generation
Embedding intelligence into the tools your team already usesThe model doesn't live in a chat window. It's woven into dashboards, document pipelines, voice agents, and messaging channels. When a work order arrives, the model reads it, matches it, routes it, and drafts the response — in your voice, following your rules. The Personality Playbook shapes every output: investor memos use analytical structure, client proposals lead with relational warmth, and ops runbooks match the detail-first precision operators expect. Document stacks that used to take days generate in seconds.
Live KPIs
11 channels
OMs, invoices, SOWs
Continuous Query & Human-in-the-Loop
The model gets sharper with every decision your team makesThis isn't a one-time deployment. The model is queried continuously — every document it generates, every decision it recommends, every automation it triggers passes through human checkpoints. Approvals, rejections, and edits feed back as training signal, each tagged with the reviewer's cognitive profile so the model refines its understanding of which decision styles accept which framings. The model compounds institutional knowledge over time.
+1 confidence
Negative signal
Highest value signal
Experience
AI Solution Architect & Consulting Lead
- — Architect AI solutions for Fortune 500 clients across energy, healthcare, real estate, and restaurant sectors — 21 production services deployed across 4 cloud platforms
- — Pioneer instinct-training methodology with MBTI-informed personality playbook — capturing decision patterns from founders, systems architects, and financial leaders into production AI models that scale institutional knowledge with cognitive-type-aware training data and outputs
- — Built ERP-integrated document intelligence pipeline processing invoices across 14,000 vendor accounts with multi-currency GL routing, SAP F3041 template generation, and 5-tier approval workflow
- — Engineered computer vision inventory system with PyTorch — reducing manual errors 40% with real-time alerts across 11 messaging channels
- — Fine-tuned domain-specific LLMs (8 AI models integrated, 5,600+ over 10 years of ML training examples) achieving 31% eval loss improvement across healthcare and insurance verticals
Principal, Strategic Acquisitions & Asset Management
- — Lead strategic acquisitions across foreclosure, probate, and distressed asset portfolios with automated CMA and structured deal flow
- — Built AI-driven offering memorandum automation — generating institutional-quality OMs from property data, comps, and financials in minutes instead of weeks
- — Develop capital raising strategies including investor relations, fund structuring, LP/GP reporting, and automated fund administration workflows
- — Engineered DST and 1031 exchange document stack automation — compliance-ready packages with QI coordination, identification notices, and closing docs generated programmatically
- — Manage arbitration processes and dispute resolution in complex multi-party transactions involving liens, title defects, and contested ownership
Director, Strategic Solutions
- — Led initiatives supporting $200M+ in annual billing — pricing structure, commodity analysis, and operational decision support
- — Drove smart contract deployment and process modernization across commercial infrastructure
- — Supported power plant acquisitions and aligned financial structure with operational execution
Strategy / Operations Transformation Leader
- — Supported expansion to top-billing practice in Maryland through technology-first operational redesign
- — Redesigned patient throughput, billing workflows, and reporting — driving multi-year sustained growth
- — Applied analytics-driven scaling across scheduling, staffing, and financial performance
Technical & Leadership
AI & Engineering
Strategy & Leadership
Featured Work
Production systems, real results
Document Intelligence Pipeline
End-to-end invoice processing with deep learning field extraction, SAP ERP integration, multi-currency GL routing, and 5-tier approval workflow.
Franchise Inventory System
7 AI agents in one network — automated PO generation, Oracle data entry & sync, threshold alerts, supplier verification, PyTorch barcode scanning, and OCR product detection for a Fortune 500 restaurant group.
AI Lead Generation Platform
20,000+ towns mapped for SEO and ad campaigns, voice agent qualification, CRM pipeline automation.
Energy Command Center
GIS-powered lead scoring across commercial properties with automated outreach and building electrification strategy.
Instinct Model Training
Domain-specific LLMs trained on founder and operator decision patterns with archetype-stratified training data. 8 AI models across 6 industries — highest personality-playbook ROI in healthcare (31% eval lift) and real estate (2.4× faster closings).
Multi-Channel Intelligence
AI agents deployed across 11 messaging channels — WhatsApp, Telegram, Slack, Discord, Teams, and more.