models
LLM Integration
OpenAI, Anthropic, and open-source model integrations tailored to your stack and use case.
Artificial Intelligence
Applied AI for Businesses, Built for Production.
Applied AI services for teams that need more than a demo: custom LLM integrations, AI agents, RAG systems, and production workflows designed around the business problem, the data reality, and the operating risk.
Applied AI delivery map
From prototype to production workflow
1Use-case definitionclarity
2Model and data architecturegrounding
3Agent workflow designautomation
4Evaluation and monitoringtrust
24/7
agent workflows
RAG
grounded systems
MLOps
production discipline
Trusted by clients, partners, and collaborators
Capabilities
The AI layer your product and operations can trust.
We build the AI pieces that need to be useful, measurable, and resilient after the demo is over.
agents
AI Agents
Autonomous agents that reason, plan, and orchestrate complex multi-step tasks reliably.
docs
Document Intelligence
Extract, classify, and process unstructured data from contracts, invoices, reports, and knowledge bases.
insight
Predictive Analytics
Recommendation systems and forecasting models grounded in your real business data.
retrieval
RAG Systems
Retrieval-augmented generation pipelines that keep AI responses grounded, current, and auditable.
ops
Model Ops
Fine-tuning, evaluation pipelines, and production monitoring so AI stays performant.
TowerZ
Applied AI in practice: what we built inside TowerZ.
TowerZ is our strongest proof point for applied AI because it shows the discipline required to move from model excitement to useful business workflows. We built AI into analysis, planning, and operations so the system helps people decide, act, and follow through inside real working constraints.
Explore Case StudiesAI-assisted business diagnostics that turn messy operational context into structured recommendations.
Agent workflows that support planning, task generation, and follow-through instead of stopping at one-off answers.
Production-minded safeguards, monitoring, and workflow boundaries so autonomy stays useful and accountable.
A connected product where AI works with the surrounding business system instead of living in a disconnected chat box.
Calculate your ROI
Calculate your custom software ROI before investing.
Use our free calculator to model labour savings, tax credits, and payback period in under two minutes. No sign-up required.
Build Shape
A production-minded AI engagement.
We treat AI as an operating layer, not a feature garnish. The work starts with judgment, then moves fast into proof.
Discover
We map your use case, data availability, risks, constraints, and success metrics.
Use caseData readinessRisk map
Prototype
We build a working proof-of-concept quickly enough to expose the real technical and business questions.
PromptingRetrievalWorkflow
Evaluate
We test against real-world benchmarks, edge cases, hallucination risks, and operational expectations.
BenchmarksHuman reviewQuality gates
Deploy
We roll out with observability, feedback loops, safeguards, and a plan for iteration.
MonitoringFeedbackGovernance
Verified Credentials
Certified expertise you can verify
Independent, third-party certifications behind the work.
Use Cases
Concrete AI outcomes, not vague transformation.
The best AI projects remove friction from high-value work and make the business easier to operate.
support
Automate Customer Support
Problem
Tier-1 tickets consume developer and support team time.
Solution
AI agents handle, triage, and escalate with consistent quality around the clock.
documents
Extract from Documents
Problem
Teams manually process contracts, invoices, and reports.
Solution
LLM pipelines extract structured data with stronger accuracy, reviewability, and audit trails.
product
Build AI-First Products
Problem
Competitors are shipping AI-native experiences faster than your team can scope them.
Solution
We embed AI from intelligent search to recommendations with product-grade development.
operations
Accelerate Internal Productivity
Problem
Repetitive internal tasks drain high-value team bandwidth.
Solution
Intelligent agents handle repeatable work so your team can focus on judgment and growth.
Rooted in Sherbrooke
An applied AI partner based in the Eastern Townships, with serious production standards.
From Sherbrooke, we help Quebec and Canadian businesses adopt applied AI with the same standards we bring to core software and systems work: judgment first, implementation discipline second, and measurable business value throughout.
Regional ecosystem
We're close to Université de Sherbrooke, Cégep de Sherbrooke, and Productique Québec, a pool of talent and applied AI research.
Rigor, not hype
Every deliverable goes through evaluation, monitoring, and governance before touching production. Never just a demo.
Direct access to the team
You work with the people who design and ship the system, with no middleman and no offshore subcontracting.
Applied AI, grounded in operations
We focus on AI that improves a real workflow, product, or decision loop, not novelty features that create more supervision than value.
Go Deeper
Proof and planning resources for applied AI buyers.
These links reinforce how we approach applied AI in products and operations: grounded systems, real constraints, and measurable outcomes.
See TowerZ as an applied AI case study
TowerZ shows how AI can support analysis, planning, and execution inside one connected business system.
ExploreRead our applied AI point of view
This article explains what applied AI means in practice and how businesses should judge whether a use case is worth building.
ExploreUnderstand where RAG actually fits
Our RAG guide breaks down when retrieval improves answer quality, and when it is not the right architecture.
ExploreSee how we build AI coding agent teams
This article shows how we structure an orchestrator and specialized coding agents so AI stays precise inside a real codebase.
ExploreHow We Work
Fast experiments, serious development, measured rollout.
Frame
Define the job-to-be-done and the operating constraints before choosing a model.
Build
Create a working system that uses your data, tools, and real workflow.
Measure
Evaluate quality, latency, cost, safety, and business usefulness.
Scale
Move from prototype to monitored, maintainable production AI.
Frequently Asked
Questions we hear most
We do not have an AI team. Can we still build this?
Yes. That is the most common starting point. We bring the engineering, MLOps, and integration work. You bring the domain knowledge and the data context.
How do you handle data privacy with LLMs?
We default to private-deployment patterns (AWS Bedrock, Azure OpenAI, on-prem) and add retrieval boundaries, redaction, and audit logging so sensitive data never leaves your environment.
How do you measure if the AI actually works?
Every project ships with task-level benchmarks, a human-review process, and quality gates. Traffic only ramps up once the model meets agreed accuracy and safety thresholds.
What does an AI project usually cost?
Most pilots ship in 4 to 8 weeks for $25k to $80k CAD. Ongoing operation, evaluation, and tuning is a separate monthly retainer scoped to traffic and risk.
Start With Judgment
Bring AI into the parts of the business where it can actually earn its keep.
Let us look at your workflow, data, and product context, then design the next useful AI move.