Cloud Migration & Modernization
Migrate, modernize and optimize your infrastructure on Google Cloud.
Tech.us helps organizations unlock the full potential of Google Cloud with AI, data, and modern applications to drive real business outcomes.
Projects Delivered
Years in Business
Industries Served
Trusted by Industry Leaders














Certified and experienced team
Across industries and complex use cases
Deep collaboration with Google Cloud
From innovation to measurable outcomes
WHAT WE WORK WITH
End-to-end services to accelerate your cloud and AI journey
Migrate, modernize and optimize your infrastructure on Google Cloud.
Build intelligent solutions with Google’s AI and Gemini models.
Turn your data into insights with BigQuery, Looker and AI-powered analytics.
Build and modernize scalable, secure and cloud-native applications.
Strengthen security, compliance and risk management on Google Cloud.
Accelerate delivery with CI/CD, automation and infrastructure as code.
BUILT FOR BUSINESS IMPACT
Tech.us combines deep engineering expertise with Google Cloud’s leading AI capabilities to help you solve today’s challenges and create tomorrow’s opportunities.
Improve efficiency and reduce costs
Create AI-powered customer and employee experiences
Make faster, smarter decisions
Empower your teams and customers
Unlock new revenue opportunities
PROVEN ACROSS SECTORS
The sectors we work in, and what teams there are usually trying to get done.
Explore All Industries
Construction
A project generates drawings, schedules, and site reports faster than anyone can reconcile them. Google Cloud is where we put that material so office and field both reach it.
Explore Construction→
Healthcare
Patient data is the most useful and most restricted asset a provider holds. We build on Google Cloud so clinical teams reach it quickly, with handling designed to your HIPAA obligations.
Explore Healthcare→
Financial Services
Every transaction has to be fast, traceable, and defensible months later. That shapes how we set up identity, encryption, and audit trails on Google Cloud from the first decision.
Explore Financial Services→
Manufacturing
Plants already produce more data than most teams use, and the lines cannot pause while anyone gets to it. We build the analysis layer on Google Cloud without touching production.
Explore Manufacturing→
Retail & Supply Chain
Demand is unpredictable and stock is never where the system says it is. Google Cloud handles the traffic peaks and carries a single current view across channels.
Explore Retail & Supply Chain→
Transportation & Logistics
Fleet, route, and shipment data usually sit in separate systems owned by separate teams. Bringing them onto Google Cloud is what lets dispatch act on a delay.
Explore Transportation & Logistics→
How We Work
A proven path from first assessment to continuous optimization on Google Cloud.
Assess and plan
Architect the solution
Migrate and transform
Develop and implement
Connect systems and data
Drive continuous improvement
CLIENT OUTCOMES
A look at the engineering work the same team delivers. These projects span different stacks and cloud environments, and they show how we scope, build, and ship.
View All Case Studies
A precast concrete manufacturer partnered with Tech.us to bring AI into the estimating workflow. The system uses OCR, computer vision, and generative AI to identify, extract, and visualize structures, pipes, and components from complex construction drawings.
Read the Case Study
SkyHawk by TELUS needed a streamlined mobile experience for its Connect Anywhere platform. Tech.us built the core experience around real-time asset tracking, fleet activity, secure configuration, and map-based operational visibility.
Read the Case Study
Tech.us helped bring Wealth Mastery to life as a digital platform that puts personalized financial planning tools directly in users' hands while supporting a large and growing audience.
Read the Case Study
WHAT WE BUILD ON
Tech.us works across the full Google Cloud ecosystem. Here are the services our team builds with most.
Agentic AI & Orchestration
Agentic AI
AI Agents
Multi-Agent Systems
Agentic Workflow Automation
Model Context Protocol (MCP)
Agent-to-Agent Protocol (A2A)
Agent Memory and Reasoning
Generative AI & Foundation Models
Large Language Models
GPT
Claude
Gemini
Llama
Generative AI
Multimodal Foundation Models
Diffusion Models
Small Language Models
Model Fine-Tuning
Prompt & Context Engineering
Machine Learning & Deep Learning
Machine Learning
Deep Learning
Predictive Analytics
Recommendation Systems
Anomaly Detection
Time-Series Analysis
Data & AI Platforms
AI-Ready Data Platforms
Data Lakes and Lakehouse
Data Engineering
AI Frameworks & Libraries
PyTorch
TensorFlow
Scikit-learn
Hugging Face Transformers
LangChain
LangGraph
MLOps, LLMOps & AgentOps
MLOps
LLMOps
AgentOps
Model Deployment and Serving
Agent Deployment
Model and Agent Observability
Prompt and Response Tracing
AI Cost Optimization
AI Evaluation, Safety & Governance
LLM Evaluations
Agent Evaluations
RAG Evaluations
AI Guardrails
Prompt-Injection Protection
Red Teaming
Responsible AI
AI Governance
Cloud AI Technologies
Google Cloud
Vertex AI
Gemini Models
Agent Studio
Vertex AI Agent Builder
Agent Development Kit
Vertex AI Vector Search
Google Cloud Document AI
Google Cloud Vision AI
Microsoft Azure
Microsoft Foundry
Microsoft Copilot Studio
Microsoft Agent Framework
Azure AI Document Intelligence
Azure AI Speech and Vision
Microsoft Fabric
Microsoft Purview
Language, Vision, Speech & Document AI
NLP, NLU and NLG
STT, TTS and ASR
Conversational AI
Document Intelligence
Computer Vision
RAG, Search & Knowledge Systems
Enterprise RAG
Agentic RAG
Multimodal RAG
Enterprise Search
Semantic & Hybrid Search
Vector Databases
Knowledge Graphs
Reranking and Retrieval Optimization
FAQ
Gemini works on what you connect it to. The useful version means grounding it in your documents, records, and systems so answers reflect your business. That grounding work is usually the larger part of the project.
Usually, yes, at least partly. Models are only as good as what they can reach, and most AI projects that stall do so because the data was never consolidated. We often scope that as the first phase.
Yes. Cross-cloud moves follow the same method as a data center migration: assess what runs today, sequence the move in waves, and validate each wave before the next begins.
Less than most teams expect. Some workloads move as they are, some are worth refactoring into Cloud Run or GKE, and some should stay where they are for now. We assess that per workload.
We build on portable, open architecture and document which parts are Google Cloud-specific. You will know what a future move would involve before you commit to anything.
We design to the obligations you tell us apply, using the identity, policy, and monitoring controls the platform provides. Tech.us does not certify your environment. We build to the controls your auditors expect.
You own the environment, built in your organization and projects, with documentation and runbooks handed over. If you want us running it afterward, that is a separate agreement rather than a condition of the build.
Let’s discuss your cloud, data, and AI transformation journey.
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