AI development in Regina — machine learning and intelligent products
Applied AI in production: decision-intelligence platforms, NLP, computer vision, search, and workflow automation. Peradeo ships models and integrations behind real products — for example Equilo’s gender-equality analytics used by governments and impact investors — not slide-deck demos.
What is included
- Problem definition and AI opportunity mapping
- Data engineering, cleaning, and feature pipelines
- Custom model development or hosted-model integration (including OpenAI APIs)
- Evaluation, monitoring, and retraining
- Dashboards and APIs so non-data teams can use the output
Our process
- Problem definition & strategy — typical timeline: 1–2 weeks: Business problem, success metrics, data access, and a go/no-go before training spend.
- Data engineering — typical timeline: 2–6 weeks: Pipelines, quality checks, and training/validation splits with security and compliance in mind.
- Model development — typical timeline: 4–8 weeks typical proof of value: Iterative training, NLP/CV/classical ML as appropriate, and honest evaluation against the metric you named.
- Production & optimization — typical timeline: ongoing: Deployment, A/B tests, monitoring, versioning, and retraining as data drifts.
Typical outcomes
- Equilo: AI decision-intelligence platform aggregating 200+ sources and 600+ KPIs; SOC 2 Type I; used by Fortune 500s and DFIs
- Dummies.com: intelligent search and location-based content recommendations at publishing scale
Frequently asked questions
What AI work does Peradeo actually deliver?
Applied AI in production products: NLP and decision-intelligence dashboards (Equilo’s gender-equality analytics platform), search ranking and recommendations, document and workflow automation, and custom model integration (including OpenAI APIs) behind authenticated business apps — not slide-deck prototypes.
Do you train custom models or integrate existing ones?
Both. We start with problem definition and data readiness. If a hosted model or existing library solves it, we integrate that. If you have proprietary data and a clear success metric, we design training, evaluation, and a monitored production deployment with retraining in the loop.
How long does an AI project take?
A focused proof of value is often 4–8 weeks. Productionizing data pipelines, evaluation, and monitoring typically follows in another 2–4 months. We do not start model work until the business problem, data access, and success metrics are written down.
Related pages
Request a free consultation · Email hello@peradeo.com · Phone (Canada) +1 (306) 216-9934