Jänichen | Software & Consulting
AI Integration & Enterprise Modernization

Practical AI integration
for enterprise software

We help organizations add AI capabilities to existing platforms and workflows—from agentic automation and intelligent tooling to full-stack modernization of legacy systems.

25+ Years Enterprise Experience .NET · Cloud · Enterprise Data AI · Agentic Workflows · MCP
Services

What
we do

Select advisory and implementation engagements for organizations navigating AI adoption and platform modernization.

01

AI Integration Assessment

Evaluate where AI fits in your existing stack. We audit workflows, identify high-impact integration points, and deliver a concrete adoption roadmap—covering LLM selection, tool architecture, and agentic automation patterns.

02

Legacy Modernization Roadmap

De-risk the migration of legacy .NET and SQL Server systems. We define modular architectures, plan incremental migration paths, and design API boundaries—so you modernize without disrupting what already works.

03

Architecture Review & Advisory

Independent technical due diligence for teams evaluating AI tools, planning cloud migrations, or navigating architectural decisions. Vendor-neutral guidance grounded in decades of enterprise delivery.

04

Agentic AI & Tooling Development

Custom tool APIs, MCP servers, and data connectors that let AI assistants work with your proprietary systems—databases, internal APIs, and existing workflows. AI that takes action in your actual environment.

Deep Specialization

Agentic AI for
enterprise systems

We connect AI to the systems your business actually runs on. That means building the full integration layer—tool APIs, data connectors, orchestration logic, safety guardrails, and governance controls—so AI assistants can work with your proprietary databases, internal APIs, and existing workflows.

Tool & API Integration
MCP, REST, internal systems
Multi-Agent Orchestration
Coordinated AI workflows
Safety & Governance
Access controls, audit trails
Enterprise Data
.NET, SQL Server, Azure
Approach

How we
work

Every engagement follows a structured methodology designed to minimize risk and maximize clarity.

01

Assess

Understand your current systems, team capabilities, and business objectives. Identify where AI integration or modernization will have the highest impact.

02

Architect

Design a concrete implementation plan with clear milestones, technology choices, and risk mitigation strategies. No black boxes.

03

Implement

Build and integrate incrementally. Deliver working prototypes early, validate against real data, and iterate based on feedback.

04

Support

Ensure your team can own and evolve what we've built. Knowledge transfer, documentation, and ongoing advisory as needed.

Work

Representative
engagements

Selected work reflecting the depth and range of our practice.

Enterprise AI · Full Case Study →

AI-Assisted Development Workflows for a Legacy Platform

Context
A 20-year-old .NET/SQL Server monolith with 1,000+ stored procedures and a 10TB+ production database needed to accelerate modernization without disrupting daily operations.
Approach
Built a custom MCP server ecosystem connecting AI assistants to the codebase, database schema, and internal documentation. Designed agentic workflows for code analysis, migration planning, and automated test generation.
Outcome
Enabled the engineering team to navigate and modernize legacy code significantly faster, with AI-assisted analysis replacing weeks of manual discovery work.
Modernization

GPU Analytics Engine & Cloud Migration

Context
A geospatial technology company needed real-time daylight and visibility simulations for urban planning—replacing analysis workflows that previously took weeks.
Approach
Architected a high-performance GPU analytics engine using NVIDIA OptiX, migrated desktop applications to Blazor WebAssembly, and introduced Azure-based CI/CD for continuous deployment.
Outcome
Analysis turnaround went from weeks to real-time. The platform scaled from desktop-only to cloud-delivered, serving engineering teams across multiple countries.
Visualization

VR Infrastructure Planning System

Context
A major port authority needed a way for 150+ engineers to visualize and plan temporal infrastructure changes in 3D, replacing static planning documents.
Approach
Led development of a Unity-based VR visualization system with temporal simulation capabilities, integrated with existing enterprise MVC systems for cost estimation and project management.
Outcome
Delivered a system used daily by engineers for infrastructure planning, reducing miscommunication and enabling spatial decision-making that was previously impossible with 2D documents.
About

About
the practice

Jänichen Software & Consulting is a Montreal-based consultancy led by Thorsten Jänichen, a Staff-level software engineer with over 25 years of experience building and modernizing enterprise systems across Europe and North America.

The practice combines deep enterprise engineering expertise—from multi-terabyte SQL Server environments and high-performance GPU analytics to cloud-native Azure architectures—with hands-on AI integration work, including Claude Code workflows, MCP server development, and agentic automation.

We take on select advisory and implementation engagements where senior technical depth makes the difference—helping organizations adopt AI that works within their existing systems, not despite them.

C# / .NET SQL Server Azure Claude / MCP Blazor Unity DevOps

Thorsten Jänichen

Founder & Principal Engineer

B.S. Computer Science
University of Applied Sciences Rapperswil, Switzerland
Microsoft AI Agents
From Foundations to Applications — Coursera Professional Certificate
25+ years across
Switzerland, Germany, UK, and Canada
Contact

Let's talk

Exploring AI integration for an existing platform? Looking for senior technical guidance on modernization? We'd welcome the conversation.

Montreal, Canada · Select advisory and implementation engagements