Capability · Retrieval copilot
A product-embedded assistant over your own data.
Retrieval, citations, and evaluation, wrapped in an interface that makes answers trustworthy enough to act on.
- LLM
- RAG
- Product
HEADQUARTERS
Vancouver, Canada.
49.28° N · 123.12° W
TEAM
Founded by engineers. A small senior team that designs, builds, and runs its own AI products.
FOCUS
AI SaaS, end to end. Product, models, data pipelines, and infrastructure, all engineered under one roof.
REACH
Built in Canada. Used anywhere. Remote-first and production-focused, shipping across time zones.
GLOBAL REACH
Built in Vancouver. Reaching users worldwide.
Our products run in production across six continents, serving users around the clock.
- 30+
- countries reached
- 6
- continents in production
- 24
- time zones covered
Canada
Vancouver · Toronto
USA
San Francisco · New York · Austin
Brazil
São Paulo
UK
London
Germany
Berlin
UAE
Dubai
Singapore
Singapore
Australia
Sydney
AIQuant exists for the gap between a promising model and software people rely on. We design the product, engineer the pipeline, and stay until it holds up in production.
WHAT WE DO
We take products from promising model to production, covering design, engineering, and the infrastructure underneath.
Index
AI SaaS development
Full products, not prototypes.
The whole application around your model: auth, billing, dashboards, and the reliability to run it.
LLM integration
Retrieval, agents, evals.
Retrieval, tool use, and agentic workflows wired into your product, with evaluation and guardrails so quality is measured rather than assumed.
Data & ML pipelines
From raw data to live inference.
Ingestion, feature stores, training, and serving that stay fast and observable.
Product design
Interfaces that make AI legible.
UX that turns model output into something users trust and act on.
WHAT WE BUILD
The kinds of products we ship.
Illustrative examples of our capabilities. Named client studies appear here as clients approve them for publication.
Capability · Real-time ML pipeline
Streaming ingestion to live inference.
Monitoring, rollback, and observability built in, with latency low enough to keep you in the loop.
- Data
- ML
- Streaming
Capability · Agentic workflow tool
Multi-step agents with human-in-the-loop review.
Tool-use and guardrails that keep an agent genuinely useful, and safe to hand a real task.
- Agents
- Evals
- Product design
THE BAR WE BUILD TO
01Evals on every AI feature
02Production-grade from commit one
03No demo-to-prod gap
04Designed to a real latency budget
HOW WE WORK
A short path from idea to production.
01
Prototype
One week to a working slice. We pin down the problem, the data, and the definition of done.
02
Product
Designed and engineered in parallel. You see it working, not just described.
03
Production
Shipped, measured, and improved against real usage and evals.