1. AI & Data Strategy
Before we train a model, we figure out whether you need one. Our discovery sprint maps your data pipelines, interviews stakeholders and inventories the analytics dashboards that go unopened. We produce an AI strategy with a prioritized roadmap: where machine learning earns its keep, where generative AI and large language models (LLMs) add value versus noise, and where workflow automation should wait until the data is trustworthy. You receive a plain-language project scope with CAD project fees, timeline and measurable outcomes — never guaranteed ROI, always honest about gaps. Typical engagement: C$7,500–C$16,000 over one to three weeks.
2. Machine Learning Models & Forecasting
Forecasting demand, inventory, staffing or risk — when your history supports it, we train machine-learning models that respect seasonality and regime change. We are candid when your data is too sparse or too dirty to predict reliably; sometimes the right answer is better monitoring, not a model. Where models earn their place, we deliver feature engineering pipelines, model evaluation harnesses and accuracy limits stated upfront. Responsible AI review covers bias checks where applicable. Production deployment typically C$50,000–C$130,000 depending on complexity.
Forecasting outputs surfaced in a dashboard your team can interrogate.
3. Analytics, Dashboards & Reporting
A dashboard nobody opens is just expensive wallpaper. We build analytics and reporting layers that earn trust — wired to live data, annotated with context, and designed for the decisions your team actually makes on a Tuesday afternoon. We integrate with your warehouse, ERP or custom API endpoints and document every metric definition so arguments happen in the data, not in Slack. Human-in-the-loop review is built into any metric that triggers action. Ideal for SMEs and enterprise teams tired of tab sprawl. Proof of concept from C$25,000; full deployment C$55,000–C$110,000.
4. Data Pipelines & Engineering
No ML model survives bad plumbing. We design and ship data pipelines that ingest from your sources — normalized, deduplicated and model-ready. Data engineering includes schema design, incremental loads, quality checks and monitoring on the pipeline itself. We document transforms, set up alerting when upstream feeds break, and hand over runbooks your team can maintain. Senior AI engineers pair with your data team; retainer support available post-launch. Most client engagements land between C$38,000 and C$90,000.
Pipeline architecture sketched before a line of code is written.
5. LLM Apps on Your Data (RAG & Assistants)
General-purpose chatbots hallucinate; yours should not. We build AI assistants and AI agents grounded in your documents, warehouse tables and knowledge base via retrieval-augmented generation (RAG). Guardrails enforce citation of source data; model evaluation runs on every release. API integration connects to the tools your staff already use. Human-in-the-loop review is mandatory for any action beyond read-only insight. Built for Canadian market compliance including PIPEDA-compliant data handling. Projects from C$40,000; enterprise deployments C$80,000–C$175,000.
6. MLOps, Monitoring & Responsible AI
Shipping is the beginning. We implement MLOps practices — versioned models, automated model evaluation, model drift monitoring and rollback paths — so your systems do not silently rot. Monitoring dashboards show precision, recall and business-relevant metrics your leadership can read. We document guardrails, audit logs and human override procedures. For Toronto and Canadian clients, we align with data privacy expectations and your internal security policies. Retainer packages from C$5,500/month; audit-only engagements from C$11,000.
Evening workshop — monitoring runbooks reviewed before go-live.
AI & results disclaimer: Our studio provides AI and data design, development and consulting services, including strategy, machine-learning and generative-AI applications, analytics, data engineering, AI assistants, workflow automation and monitoring for client organizations. AI systems can produce errors, biased or inaccurate outputs and require human review and oversight; we design for humans-in-the-loop. We do not guarantee specific business results, predictions, cost savings, revenue, accuracy or return on investment. Outcomes depend on data quality, scope, budget and adoption. Any case studies or metrics shown reflect past client work and are not a promise of future performance. This is a professional AI services firm, not legal, financial, investment or medical advice, and not a course or income opportunity.