AI-infused products and applications
Agentic and GenAI capabilities built into the products your business runs on — designed, built, and taken to production on Google Cloud.

The platforms your business runs on, built faster and proven at enterprise scale.

For typical apps — a committed clock, not a rough estimate. This is how we turn ideas into working applications, fast.
AI builds the volume. Senior engineers own what ships.

Your team knows your business. Our engineer knows how to build. Put them in the same room and software ships against your real data and constraints.
✓A builder with running code, not a consultant with recommendations.
✓Custom apps and automations, built on the spot for your business teams.
✓First value in days, not a discovery phase in months.

Vanguard builds for you. Forward Deployed Engineers embed with you. AI-Enablement transforms your own team — the same senior leaders, now working inside it.
We've built the playbook — not just theorized it.
Current-state assessment: where your team stands today.
Transformation roadmap: how it gets to AI-native.
The AI-native operating model: what the destination looks like.
Trust is earned, not granted: every AI colleague starts supervised and gains autonomy only under human approval.
Custom software, applications, platforms, and AI capabilities — designed, built, and delivered across product, financial services, government, insurance, and manufacturing.
Agentic and GenAI capabilities built into the products your business runs on — designed, built, and taken to production on Google Cloud.
Production data lakes, pipelines, and analytics foundations on BigQuery and Vertex AI — built to carry real enterprise load.
RAG assistants and copilots that unify fragmented enterprise tools into a single, governed workflow.
Systems that turn documents, images, and signals into decisions — plan review, defect detection, fraud scoring.
Delivered: operations automation that cleared a bank-scale duplicate-ticket backlog inside a global bank.
An agentic-AI analytics pipeline on BigQuery, Vertex AI, and Gemini — turning billions of clickstream events into auditable, decision-ready insight.
The depth behind it
A global infrastructure-software leader. Enterprise GenAI vulnerability-remediation assistant on Vertex AI, with RAG over BigQuery — six-plus security tools unified into one analyst workflow.
Read the case study→GovernmentA US government regulatory body. Computer-vision application for building-plan review; review time cut from hours to minutes.
Read the case study→Financial servicesA top US investment bank. Investment-management data lake, designed and delivered into production.
Read the case study→InsuranceA Southeast Asian insurer. Machine-learning risk-signal models that flag fraud and automate the downstream tasks.
Read the case study→Whether the business process around it can be automated too — and what the AI itself costs and risks.
Start where it makes sense — scale from there.
Prove the idea in a working prototype.
A usable first version in your users' hands.
A full build to production — around three months for typical apps.
Embed a senior AI builder with your team.
Bring the software, product, or platform you need. Pick where to start and a senior engineer scopes it with you — what gets built, and how fast AI-native delivery gets you to production.
Part of the AI portfolio
AI for software engineering is one of SquareShift's AI accelerators. Start here when you need software, a product, or a platform built.
See the full AI portfolio→AI-native software engineering, from first spec to production.
