FAQ

No, you don't need a perfect PRD. But we do need enough clarity to build something that delivers an outcome.

• The problem: what are you trying to solve, and who feels the pain today?
• The outcome: how will you measure benefits (time saved, errors reduced, faster decisions, better customer experience, revenue impact)?
• What you tried: what tools or methods have you already used, and why didn't they work?
• Constraints: what must we respect—security/compliance, timeline, budget, deployment environment, and who owns the project internally?

If it's a fit, we'll recommend the smallest high-ROI wedge to ship first. If it's not a fit, we'll tell you quickly and point you to a better path.

What we need to give you a real plan:

• The problem and desired outcome: what you want to change, and how you'll measure it.
• What you've tried already: tools, vendors, internal attempts—and why they didn't work.
• Data reality: where the data lives, how we access it, and whether it's unified/stored in a usable way.
• Constraints: security/compliance requirements, deployment environment (your cloud/VPC), timeline, and budget range.
• Ownership: a single owner who can make decisions and unblock access.
• Support: whether there's an internal technical team who will operate it after handoff.

With that, we can recommend the smallest high-ROI wedge to ship first—and what it will take to get it into production.

It's a paid, engineering-first sprint to reduce risk fast. In five days, you'll see a prototype and a clear plan to ship.

You leave with:

• A prototype your team can evaluate (to visualize how the solution may work)
• A basic architecture/approach for the production system
• Delivery milestones (what we'll ship, in what order, and how we'll measure progress)

The goal is clarity and an executable plan—so you can decide what to build next with confidence.

Usually, you'll see something tangible quickly—either through the 5-day AI Prototype Sprint or through the first thin slice of a build. Timing depends on data access, security/compliance constraints, and integration complexity.

A typical pattern:

• Days: a prototype your team can evaluate
• ~2 weeks: a first working service/API demo for the narrow wedge
• ~12 weeks: a full production delivery for the agreed scope and edge cases

Yes. If you have an internal team to implement, we can support with consultation only.

We'll help you clarify the problem, define success metrics, evaluate feasibility, and design an implementation plan your team can execute. Our goal is outcomes—if your team is best positioned to build, we'll get out of the way and support as needed.

Yes. In many cases, we're brought in after an internal prototype, a vendor pilot, or a first attempt that didn't hold up in production.

We can assess what's already there (what's usable vs what's fragile), keep what works, and rebuild the parts that block reliability, evaluation, security, or ownership. The goal isn't to start over—it's to get to an outcome faster.

We focus on AI engineering and the systems around it. That often includes building the application layer required to ship AI features—APIs, internal tools, integrations, and monitoring—but we're not trying to be a general web/app development shop.

If you need broader product work (web/mobile development, UI/UX, etc.), we can bring in well-regarded partner firms we've worked with—ranging from startup-focused teams to enterprise-grade agencies—so you still get a cohesive delivery without us pretending to be everything.

We can support UX/UI as part of shipping an AI feature—especially for internal tools and review workflows—but it's not our core focus. If the project needs dedicated design work, we'll bring in a trusted UX/UI partner so the experience is clean and usable.

We start with the outcome you're expecting and the value the system must deliver—then translate that into measurable success criteria.

For correctness, we may use metrics like accuracy, precision/recall, and F1 score (depending on the task). The key is choosing metrics that match the real-world outcome—not a vanity number.

For reliability, we validate on real examples (an evaluation set) and then keep it stable in production with ongoing monitoring for drift and failures, audit logs/traceability where needed, and human review gates when risk is high.

We design for the reality that no system is perfect. When something is wrong, it should fail safely and be easy to inspect.

Depending on the workflow, we include:

• Human review/approval gates where risk is high
• Audit logs and evidence links
• Monitoring and alerts
• Rollback paths when automation touches production workflows

The goal is simple: mistakes shouldn't become incidents.

Yes—absolutely. We also want to respect our clients' time and privacy, so we typically provide references for larger projects and formal evaluation/RFP processes, once we've confirmed mutual fit.

We'll aim to connect you with a reference that's relevant to your use case and constraints.

Yes. Ownership is part of the job. We can train your team during handoff and also provide ongoing support if needed.

Typical enablement includes architecture walkthroughs, how to deploy and monitor, how to evaluate quality and handle edge cases, plus runbooks and operational playbooks. We tailor training to your team's technical level and what you plan to own internally.

We're based in Vancouver, BC and have employees across Canada. For larger projects, key workshops, or important milestones, we can travel on-site when it's useful and efficient.

Yes—we're happy to sign an NDA early in the process. IP ownership depends on the engagement, but our default for client work is: you own what we build for you, and we retain our pre-existing know-how, reusable tools, and general methodologies.

You absolutely can—and for small projects we encourage teams to do it.

Where things get hard is when you need the system to be reliable, predictable, reusable, secure, and compliant, and to hold up over time with monitoring and clear ownership. If that's the bar you need to hit, we can help you engineer and ship it properly.

If you already built something, we can also review it, keep what works, and harden the rest so it's safe to run in production.