Frequently asked questions about our AI software

Our AI software is designed to serve a broad spectrum of industries, including financial services, healthcare, logistics, retail, and manufacturing. Small and mid-sized companies that are looking to automate repetitive tasks or extract actionable insights from their data typically see the fastest return on investment. Larger enterprises benefit from our modular architecture, which lets them integrate AI capabilities into existing technology stacks without a full platform replacement. Whether you process thousands of invoices per month or need real-time threat detection across a distributed network, we tailor solutions to match your operational reality.

Most projects move from the initial discovery workshop to a production-ready deployment in eight to sixteen weeks. The timeline depends on the complexity of the use case, the readiness of your data, and the number of integration points with existing systems. During the first two weeks we conduct a data audit and define success metrics. Weeks three through eight focus on model development, testing, and iteration. The remaining time is dedicated to production hardening, staff training, and a monitored launch phase where we fine-tune performance against real-world inputs.

No. Our platform is built to be operated by business analysts and domain experts, not just data scientists. We provide intuitive dashboards, drag-and-drop workflow builders, and pre-configured model templates that require no coding. For organisations that do have data science teams, we also expose full API access and notebook environments so they can build custom models on top of our infrastructure. In either scenario, our customer success team provides hands-on guidance during onboarding and remains available for ongoing support.

Absolutely. Data security is foundational to everything we build. All data is encrypted at rest using AES-256 and in transit using TLS 1.3. Our production infrastructure runs exclusively in SOC 2 Type II-certified Canadian data centres, which means your information never crosses international borders unless you explicitly choose an alternative deployment region. We undergo annual third-party penetration testing, maintain detailed audit logs, and support role-based access controls so you can restrict data visibility to only the people who need it. We also comply with PIPEDA and Quebec Law 25.

We offer three pricing tiers — Starter, Professional, and Enterprise — each structured as a monthly subscription with annual discounts available. The Starter plan is ideal for small teams exploring a single use case. Professional adds advanced analytics, priority support, and higher API throughput. Enterprise includes dedicated infrastructure, custom SLAs, and on-site training. We also offer project-based pricing for discrete consulting engagements such as data audits, proof-of-concept builds, and model optimisation sprints. Every plan includes a 30-day satisfaction guarantee.

Yes. We provide pre-built connectors for popular platforms such as Salesforce, SAP, Microsoft Dynamics 365, HubSpot, and Oracle NetSuite. For proprietary or legacy systems, our REST and GraphQL APIs allow bi-directional data exchange with minimal custom development. Our integration engineers work alongside your IT team during the setup phase to ensure data flows are reliable, secure, and compliant with your internal governance policies. We also support webhook-based event triggers so your AI models can react to changes in real time rather than relying on batch imports.

Every model deployed on our platform is continuously monitored for performance degradation through automated drift-detection pipelines. When statistical tests indicate that incoming data distributions have shifted beyond configurable thresholds, the system alerts your team and can trigger an automated retraining cycle using the most recent data. We also maintain shadow models — candidate versions trained on newer data — that are evaluated in parallel before being promoted to production. This approach ensures that your AI remains accurate and relevant without requiring constant manual oversight from your staff.

We design every workflow with configurable confidence thresholds and human-in-the-loop checkpoints. When a model prediction falls below your defined confidence level, the decision is routed to a human reviewer instead of being executed automatically. All predictions are logged with full explainability data — feature importance scores, input snapshots, and reasoning chains — so your team can audit any decision after the fact. This combination of guardrails and transparency ensures that AI augments human judgement rather than replacing it recklessly.

Yes. While our cloud-hosted option is the most popular choice, we fully support on-premises and hybrid deployments for organisations with strict data residency or air-gapped network requirements. Our platform is containerised using Kubernetes, which makes it portable across cloud providers and private data centres alike. The on-premises option includes the same dashboards, APIs, and monitoring tools available in the cloud version, and our engineering team provides installation support, upgrade management, and performance tuning tailored to your hardware environment.