Overview
MyKanik is an intelligence platform created by Brenden Portolese.
While the initial application focuses on automotive repair, MyKanik is fundamentally a procedural knowledge platform — designed to retrieve, canonicalize, and present complex, multi-step instructions from multiple sources in a way that is structured, explainable, and trustworthy. (Patent Pending)
This is not a generic AI chatbot. It is an intentionally designed system built to address known failure modes in large language models when applied to step-based, safety-sensitive domains.
About MyKanik
Most AI assistants struggle with procedural tasks:
- They summarize or paraphrase critical steps
- They lose context across follow-up questions
- They merge conflicting sources without attribution
- They hallucinate missing details
- They treat safety warnings as optional text
MyKanik was built to solve those problems directly.
The system assembles responses from authoritative manuals, structured data sources, and community knowledge, determines procedural equivalence across sources, and produces a canonical, structured answer that can be safely referenced and refined through follow-up interaction.
What makes MyKanik different
Canonical procedures, not free-form answers
MyKanik constructs a structured Answer Plan for each procedure, rather than generating ad-hoc text. This plan persists across the session and anchors all follow-up questions.
Multi-source by design
OEM documentation, professional guides, and community insights are preserved with explicit provenance. Conflicts are surfaced, not hidden.
Anchored follow-up interaction
When a user asks a follow-up question ("What about step 2?"), the system resolves it against the existing procedure instead of re-querying the entire knowledge base.
Safety-aware architecture
Safety warnings, constraints, and risk-sensitive steps are treated as first-class system components, not optional annotations.
Developer-ready integration
MyKanik exposes its procedural knowledge via the Model Context Protocol (MCP), so AI assistants like Cursor and Claude Desktop can query workshop procedures directly. Developers can search manuals, retrieve steps, and list vehicles from within their tools — without leaving the IDE.
Technical focus
MyKanik is intentionally built as an intelligence platform featuring automotive repair:
- Hybrid retrieval (vector search, structured sources, web ingestion)
- Canonicalization and equivalence resolution across procedures
- Structured data modeling and serialization
- Provenance tracking and conflict handling
- Session-level state and anchored follow-up logic
- Safety enforcement at the procedural level
- MCP server — Exposes semantic search, procedure lookup, and vehicle metadata as tools and resources for any MCP-compatible client
Beyond the web app
MyKanik's procedural knowledge is not confined to the web interface. The MCP server enables AI coding assistants and other tools to query the same canonical procedures, provenance, and safety-aware structure. Whether you're in the browser or in Cursor, the system delivers the same structured, traceable repair guidance.
Technology stack
About the creator
MyKanik was designed and built by Brenden Portolese, a product leader and systems architect with over 15 years of experience building and modernizing large-scale platforms across fintech, data, and infrastructure-heavy domains.
This product reflects a personal belief that successful AI products require intentional system design, clear constraints, and respect for the underlying problem domain — especially when real-world outcomes matter.
Why this matters
MyKanik is both a working product and a living portfolio of how to design AI systems that go beyond prompt engineering.
The same architecture applies to other domains such as:
- Medical procedures
- Industrial maintenance
- Laboratory protocols
- Cooking and manufacturing workflows
The core problem — turning fragmented procedural knowledge into something reliable and interactive — is universal.