FAQ
Questions before the first data assessment
Direct answers about Data Forge — a Vancouver data-engineering and applied-AI studio that forges pipelines, warehouses, dashboards and retrieval foundations for Canadian organizations.
Architecture review · Howe Street studio
We prefer clarity over hype. The sections below cover how engagements run, indicative CAD budgets, discovery duration, stack choices, PIPEDA-aligned data handling, intellectual property, drift monitoring, reporting cadence, contract structure — and what we explicitly do not do.
Is Data Forge a data broker, a lifestyle app (because of .life), or do you guarantee the results?
No on all counts. Data Forge is a data-engineering and analytics studio that builds pipelines, warehouses, dashboards and AI-ready data foundations for client organizations. The .life TLD is branding only — not a lifestyle, wellness or "data about your life" service. We do not buy or sell data; we engineer your own data under contract.
We deliver data strategy, pipeline engineering, warehouse modelling, analytics dashboards, retrieval-augmented generation (RAG) foundations, DataOps and responsible-AI governance as professional services. Humans remain accountable. We do not guarantee pipeline uptime, zero data drift, cost savings, revenue, ROI or that our systems will replace your staff. Outcomes depend on data quality, project scope, infrastructure and how your team adopts the tooling.
How do engagements work — project, discovery or retainer?
Most relationships begin with a fixed-scope data assessment or discovery sprint. You receive a written roadmap, working pipelines or warehouse models depending on scope. When systems are live, many clients move to a retainer for DataOps, drift monitoring and governance updates. Retainers are monthly with defined hours — not open-ended feature factories without change control.
We quote CAD project fees before work starts. Scope changes are discussed transparently in writing. We are an AI consultancy focused on custom delivery, not generic staff augmentation unless explicitly agreed.
What are typical CAD budgets?
Indicative ranges only — not binding quotes: data assessments C$18,000–C$32,000; warehouse and pipeline builds C$75,000–C$220,000; AI-ready retrieval foundations from C$55,000; analytics dashboard programmes from C$45,000. Retainers often start around C$6,500/month for DataOps support.
Budget depends on source complexity, number of integrations, historical data cleanliness and security tier. If preprocessing will dominate cost, we say so early — that honesty saves everyone time.
How long does discovery take?
A focused discovery loop — stakeholder interviews, source-system audit, architecture options, data quality assessment — typically runs two to four weeks after kickoff, assuming system access and decision-maker availability. A warehouse foundation with core pipelines and one decision dashboard often lands in eight to fourteen weeks. Full enterprise rollout with streaming ingest, semantic layers and MLOps takes longer.
Timelines are fixed in the statement of work. We do not promise instant delivery or guaranteed measurable outcomes by an arbitrary date.
Which stacks and platforms do you work with?
We are stack-agnostic within reason — Snowflake, BigQuery, Databricks, Redshift, Postgres, Kafka, Airflow, dbt, Fivetran and cloud-native services on AWS, Azure and GCP are common in our work. For AI-ready layers we integrate with your chosen large language models (LLMs) — cloud APIs or open-weight models on your infrastructure.
We recommend based on your team's skills, existing licences and latency requirements — not vendor kickbacks. API integration patterns are documented for your internal team to maintain.
Where is client data stored? How do you handle PIPEDA?
Client data is processed in Canadian or client-approved regions with access controls and encryption in transit and at rest. We follow PIPEDA principles and, for BC clients, relevant obligations under the Personal Information Protection Act (PIPA BC). Cross-border transfers require documented consent and safeguards.
We do not use your data to train models for other clients, sell datasets or retain data beyond agreed retention periods. A Data Processing Agreement is provided for enterprise engagements. Contact [email protected] for privacy requests.
Who owns the pipelines, models and dashboards we build?
Custom code, pipeline definitions, warehouse models and dashboard configurations built for you are yours upon final payment — as specified in the contract. We retain rights to general know-how, reusable internal libraries and pre-existing tools. Third-party platform licences remain with the vendor.
For retrieval indexes and embedding pipelines, ownership of the index and configuration transfers to you; underlying model weights from third-party providers remain subject to their terms.
How do you handle data drift, pipeline failures and model mistakes?
Production systems include monitoring — freshness alerts, schema drift detection, data quality check failures and inference latency thresholds. Incident playbooks define who gets paged and what rollback options exist. For generative AI layers we maintain evaluation harnesses and human review queues for high-stakes outputs.
We do not guarantee zero errors. We guarantee we will document failure modes honestly and build governance that catches problems before they reach your board deck.
What is your reporting cadence during a project?
Weekly written status during active build phases: completed work, blockers, decisions needed and next-week plan. Bi-weekly stakeholder demos for dashboard and pipeline milestones. Retainer clients receive monthly summary reports with incident log, monitoring trends and hours consumed.
We do not hide behind vanity metrics. If a milestone slips because source data is worse than disclosed, you hear that in plain language.
What are contract and notice terms?
Project engagements use a statement of work with fixed scope, milestones and payment schedule tied to deliverables. Retainers run month-to-month with thirty days' written notice to cancel. Intellectual property, confidentiality and liability limits are in our Terms of Service.
We do not lock clients into multi-year contracts without explicit mutual agreement and exit clauses.
What do you explicitly NOT do?
We do not sell personal data or operate a data brokerage. We do not offer AI courses, bootcamps or passive-income schemes. We do not run AI trading bots, crypto mining or GPU rental marketplaces. We do not provide wellness, meditation or lifestyle tracking products. We do not guarantee accuracy, ROI, cost savings or job replacement. We do not fabricate client logos, partner badges or performance awards.