Dotzlaw Consulting
We help teams adopt AI without the chaos. Production-grade agentic infrastructure, security and reliability audits, Servoy AI integration, and custom software development for teams that need AI to actually work.
What We Do
Dotzlaw Consulting audits business workflows, identifies where Claude and agentic AI deliver the highest ROI, and builds the systems ourselves. Every engagement ships against real data, and our methodology is documented across 82 technical articles in 7 series on this site so prospective clients can evaluate the depth of the work before the first conversation.
We engage in three tiers. An AI Opportunity Sprint diagnoses where AI fits your operations and produces a ranked roadmap. An AI Workflow Audit goes deeper on a target workflow and ships a working prototype against your real data. A Modernization Pilot ships the production system, with team training and the operational runbook to maintain it after we leave.
Across those tiers we build agentic AI systems, natural-language BI dashboards, agent security architecture, knowledge-management and RAG pipelines, web automation at scale, and legacy modernization, including specialized Servoy AI integration.
How We Work
Discover
Interviews with leadership and end users across the workflow, plus an Ops Canvas mapping the three engines of your business: acquisition, delivery, support. We tag every step as a Time Sink (manual effort), a Quality Risk (error-prone), both, or neither.
Map
Every candidate AI solution from the Ops Canvas is plotted on an Opportunity Matrix. Quick Wins anchor the near-term roadmap; Big Swings anchor the transformational projects. Deliberate deprioritization decisions protect you from vendor-driven overengineering.
Design
Architecture recommendations for the top-ranked opportunities, with specific technology choices, integration requirements, and ROI modeling. For Audit and Pilot engagements, a working prototype against your real data demonstrates the approach before you commit to a full build.
Build
Production deployment against your data at your scale, with a custom agent and skill library specific to your domain vocabulary. Team training on the architecture, the prompts, the guardrails, and the runbook your team needs to maintain the system after we leave.
Detailed methodology is documented in our 82 published technical articles.
The Team
Gary Dotzlaw
Founder and Principal AI Architect
Gary has shipped production software for 100+ companies across 35 years, through every paradigm shift the industry has thrown at us: desktop, client-server, web, cloud, and now agentic AI. That depth means he doesn't just use these tools, he architects the infrastructure that makes them reliable.
His current focus is the infrastructure layer that makes agentic AI reliable in production: swarm architecture, defense-in-depth security, and a migration methodology that moves legacy codebases into modern AI frameworks. The Bootstrap Framework, an agent swarm that builds agent swarms, is validated across 3 production projects, with each migration completing faster than the last.
Gary is an Anthropic Certified developer with 4 certifications earned through the Claude Partner Network application process, and co-author on the firm's 14+ published technical articles spanning RAG, GraphRAG, vector and graph databases, harness engineering, agent security, and production-grade autonomous coding agents with Claude Code.
Katrina Dotzlaw
AI Engineer and Research Lead
Katrina is a software developer, IEEE-published researcher, and Anthropic Certified developer with 4 certifications earned through the Claude Partner Network application process. She earned a B.Sc. in Computer Science from the University of Manitoba, where her studies focused on software engineering, databases, and AI, and she co-authored three peer-reviewed IEEE papers on data mining and fuzzy logic for health outcome prediction.
At Dotzlaw Consulting she co-built the firm's production AI systems: a natural-language report generator (plain English to printable Apache Velocity document in under 60 seconds), a general-purpose document assistant that ingests 51,000+ chunks across Markdown, HTML, PDF, and DOCX with hybrid vector and BM25 search returning sourced answers in under 3 seconds, and a natural-language BI platform that turns English questions into complete six-card dashboards against a 90.5-million-row production database in under 30 seconds at 100% SQL success across 10+ query categories.
She is also co-author on 14+ technical articles covering the infrastructure behind modern AI systems: vector databases, RAG, graph databases, GraphRAG, and a deep-dive series on building production-grade autonomous coding agents with Claude Code.
Personal site →
Ryan Dotzlaw
AI Engineer and Systems Lead
Ryan is a software developer, IEEE-published researcher, and Anthropic Certified developer with 4 certifications earned through the Claude Partner Network application process. He graduated from the University of Manitoba with a B.Sc. in Computer Science and a Minor in Mathematics. His studies focused on artificial intelligence, databases, and software engineering, and he co-authored three peer-reviewed IEEE papers applying data mining and machine learning to predict Long COVID cases.
At Dotzlaw Consulting he co-built the firm's production AI systems: a natural-language report generator that turns plain English into a printable Apache Velocity document in under 60 seconds, a multi-format document assistant that returns sourced answers across 51,000+ chunks in under 3 seconds, and a natural-language BI platform that ships in both Metabase-embedded and native React variants at 100% SQL success across 10+ query categories.
He is also co-author on 14+ technical articles covering RAG, GraphRAG, vector and graph databases, and production-grade autonomous coding agents with Claude Code.
Personal site →We publish our methodology in public.
82 technical articles across 7 series document our architectural patterns and methodology, from Claude Code agent teams and harness engineering to RAG pipelines and adversarial AI security testing. Prospective clients read the depth of the work before the first conversation.
Browse all insights →Interested in working together?