"We migrated our entire document pipeline to their AI extraction system. Processing time dropped from two days to under ninety minutes, and our error rate fell below one percent." — Nathalie Tremblay, VP operations, Citadelle Logistics
"Their predictive demand model saved us roughly $420K in overstock costs during the first fiscal year. The team understood our data landscape from the first workshop." — Derek Okafor, Chief data officer, Meridian Retail Group

Custom AI software built around your real constraints

Before we talk price, we need to know whether AI is the right tool for your problem. Not every workflow benefits from machine learning. We start by asking the hard questions so you invest only where the return is measurable.

Data readiness

Do you have at least six months of structured operational data? We assess volume, quality, and access patterns before proposing any model architecture.

Process clarity

Can your team describe the current workflow in concrete steps? AI augments clear processes — it rarely fixes ambiguous ones. We map the decision points together.

Impact threshold

Will a 15–40% efficiency gain justify the build cost? We model the expected ROI range during discovery so the investment case is transparent before any code is written.

Integration surface

Your existing stack matters. We evaluate API availability, database access, authentication layers, and deployment constraints to scope the integration effort accurately.

How we price AI software — without packages

We don't sell tiers. Every AI engagement is scoped from scratch because your data, infrastructure, and business logic are unique. Here's how the cost components break down so you can estimate before we even talk.

Cost component What it covers Typical range What drives it up or down
Discovery & data audit Workshops, data profiling, feasibility report, ROI model $4,000 – $12,000 Number of data sources, stakeholder count, regulatory complexity
Model design & prototyping Architecture selection, feature engineering, baseline model, validation $15,000 – $55,000 Problem type (classification vs. generation vs. forecasting), label availability
Integration engineering API development, pipeline orchestration, auth, monitoring hooks $10,000 – $40,000 Legacy system age, number of endpoints, real-time vs. batch requirements
Interface & UX layer Dashboard, internal tool, or end-user-facing application $8,000 – $30,000 User count, permission model, accessibility requirements
Testing & hardening Adversarial testing, bias audit, load testing, security review $5,000 – $18,000 Regulatory environment (healthcare, finance), data sensitivity
Ongoing support & retraining Monthly monitoring, model drift detection, quarterly retraining cycles $1,500 – $6,000 / month Data velocity, model complexity, SLA tier

All figures in CAD. A typical mid-complexity engagement lands between $45,000 and $120,000 for the initial build phase. We provide a binding estimate after the discovery audit, not before.

The pathway from idea to production AI

Intake conversation

A thirty-minute call where we listen to your problem, ask about data availability, and determine whether a deeper discovery is warranted. No pitch deck, no pressure.

Discovery sprint

A two-to-four-week engagement where we profile your data, interview process owners, and deliver a feasibility report with a cost model and risk assessment.

Prototype & validate

We build a working prototype against a subset of your data. You see real outputs before committing to full-scale development. If the prototype underperforms, we stop and refund the difference.

Production build

Iterative two-week cycles. Each cycle ends with a demo and a decision point — continue, pivot, or pause. You control scope at every stage.

Launch & stabilize

We deploy to your infrastructure, run parallel testing with your team, and monitor for thirty days post-launch to catch edge cases and drift.

Evolve

Quarterly retraining, performance dashboards, and a dedicated Slack channel for your team. We treat support as an ongoing engineering relationship, not a ticket queue.

What our AI software can do

We specialize in six capability domains. Each one maps to a class of business problems we've solved in production.

Predictive analytics

Demand forecasting, churn prediction, maintenance scheduling. We build models that output actionable signals, not abstract scores.

Document intelligence

Extract, classify, and route information from invoices, contracts, medical records, and regulatory filings using fine-tuned language models.

Conversational systems

Internal knowledge assistants, customer-facing chatbots, and voice interfaces grounded in your proprietary data with retrieval-augmented generation.

Workflow automation

End-to-end process automation that combines rule engines with ML decision nodes. We handle the orchestration layer so your team focuses on exceptions, not routine.

Computer vision

Quality inspection, object detection on production lines, aerial image analysis, and medical imaging support with explainable output layers.

Anomaly detection

Real-time fraud detection, network intrusion alerts, and operational anomaly flagging. We tune for low false-positive rates because alert fatigue kills adoption.

Modern server infrastructure powering AI computations

Infrastructure you can trust

Every model we deploy runs on Canadian-hosted infrastructure by default. We support AWS ca-central-1, Azure Canada Central, and private on-premise deployments for regulated industries. Your data never leaves the jurisdiction you specify.

We implement end-to-end encryption at rest and in transit, role-based access controls, and audit logging that meets SOC 2 and PIPEDA requirements out of the box.

"Their security posture satisfied our CISO review on the first pass — that almost never happens." — R. Fournier, CTO, FinBridge Capital

Why teams choose us over larger consultancies

Large firms assign junior analysts to your project and rotate them every quarter. We assign a senior engineer and a domain specialist who stay with you from discovery through production support. Continuity matters when the model needs to understand your business context, not just your data schema.

We also believe in radical transparency on cost. Our pricing table above isn't marketing — it's the same framework we use internally to scope every engagement. When we say a discovery sprint costs between four and twelve thousand dollars, that's what you'll pay. No change orders disguised as "scope refinement."

Finally, we build to transfer. Every system comes with documentation, training sessions, and a codebase your internal team can maintain. If you outgrow us, that's a success, not a loss.

What you get that others skip

  • Binding cost estimate after discovery — not a range that doubles later
  • Named senior engineer on every project, no bait-and-switch staffing
  • Prototype-first validation before full investment
  • Full code ownership and knowledge transfer at project close
  • Canadian-hosted infrastructure with PIPEDA compliance

Start with a conversation

Tell us about your challenge and we'll respond within one business day with an honest assessment of whether AI is the right fit.

Prefer a direct line?

Phone: +1 418 732-7196

Email: [email protected]

Visit us

99347 Steuber Lakes, G1R 2L3 Québec, Quebec, Canada

Response time

We aim to reply within one business day. For urgent production issues, existing clients have access to our priority Slack channel.

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This policy was last updated in January 2026. We reserve the right to modify it and will post changes on this page.

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