Choose the Right Operating Model

Quick guide: if you need senior technical leadership without a full-time hire (architecture, roadmap, hiring), pick Fractional CTO. If you need a discrete AI product shipped to production (RAG, agents, ML pipeline, eval harness), pick AI Product Engineering. If your bottleneck is engineering capacity on a known stack, pick Engineering Teams. If your data isn't AI-ready (warehousing, pipelines, governance), pick Data Platform. Unsure? Book a 45-minute discovery call.

Yes — most engagements blend at least two. Common pattern: Fractional CTO (1–2 days/week) paired with an AI Product Engineering team to ship the first AI feature, or Data Platform work feeding into an embedded Engineering Team. We scope the blend during discovery so timelines and budget are explicit, not implied.

Staff aug fills seats; KYFEX ships outcomes. Full-time hires take 4–6 months to onboard and commit you to 12+ months of payroll. KYFEX engages within 1–2 weeks, is contractually scoped to specific deliverables (or a fixed monthly cadence for fractional roles), and exits cleanly once outcomes are met. Trade-off: full-time hires accumulate institutional knowledge; KYFEX transfers it explicitly via documentation, code reviews, and runbooks.

Discovery: 45 minutes (free). Pilot / proof-of-concept: 4–8 weeks. AI product engineering build: 8–16 weeks per shipped feature. Fractional CTO: typically 6–12 months (extendable). Engineering Teams: typically 3–12 months. Data Platform builds: 8–24 weeks depending on scope. Every engagement has a written scope with success criteria, not a rolling time-and-materials contract.

Both. About a third of our work is rescue: pilots that didn't survive contact with real users, models that work in notebooks but not in production, data pipelines pulling 80% of engineering attention. We do a written 1-week diagnostic up front before committing to a rescue plan, so the scope (and feasibility) is explicit, not optimistic.

Yes — current and past clients span the US, EU, and APAC. We hold core overlap hours in your timezone, work on-site when the engagement requires it (security-sensitive workloads, regulated industries), and bill in USD against an annual MSA. Public-sector and procurement-driven processes are familiar territory.