AI Deployment Sprint
A founding engineer embeds with your team and ships one real AI system to production in 2–3 weeks — secure-by-default, evaluated, and handed back maintainable. Forward-deployed engineering, productized.
Overview
Most AI pilots die between demo and production — MIT found ~95% show no P&L impact, and it's an integration and adoption gap, not a model gap. The AI Deployment Sprint closes it the way the best AI companies now do: a founding engineer embeds directly with your team, learns your systems and constraints, and ships one concrete AI system into production — not a slide, not a prototype. It's Forward Deployed Engineering, productized into a fixed-scope, fixed-price sprint so you can start without a procurement cycle. Security and evals are built in from day one, and you keep maintainable code, documentation, and a runbook. When the sprint proves value, it converts cleanly into a retained embedded engineer or a managed engagement.
What's included
- Embedded senior (forward-deployed) engineer
- One scoped production AI outcome — agent, RAG, or workflow
- Integration with your data, APIs, and auth
- Evals, guardrails & observability wired in
- Secure-by-default build (prompt-injection, secrets, IAM)
- Maintainable handoff — code, docs, and a runbook
Engagement tiers
Start at the entry tier and scale into deeper coverage and SLAs as it earns it.
One founding engineer, one scoped production AI outcome, shipped in 2–3 weeks.
- Embedded senior forward-deployed engineer
- One production outcome — agent, RAG, or workflow
- Integration with your data, APIs & auth
- Evals, guardrails & observability
- Secure-by-default build + handoff runbook
A small senior pod for a larger, multi-system deployment under a hard deadline.
- 2–3 founding engineers, forward-deployed
- Multiple integrated systems or a complex agent platform
- Architecture, evals, and load/hardening in scope
- Security review + compliance-aware build
- Enablement for your engineers alongside delivery
The sprint converts to an ongoing embedded founding engineer on your roadmap.
- Dedicated founding engineer embedded with your team
- Continuous production delivery & iteration
- Reusable accelerators (evals, agent-ops, MCP) retained
- Path into managed operations & fractional leadership
- Monthly, cancel anytime
Click a tier to compare. All tiers are senior-led with no outsourcing — start where you are and scale up without re-contracting. Larger or multi-cloud scopes are quoted on the call.
Frequently asked
What exactly is a Forward Deployed Engineer?
A founding engineer who embeds with your team and builds the working system inside your environment — part engineer, part solutions architect. It's the model Palantir invented and that OpenAI, Anthropic, and the leading AI companies now use to get AI adopted in production, not just demoed.
How is this different from staff augmentation?
Staff-aug rents you a pair of hands against your backlog. The Deployment Sprint is outcome-shaped: a fixed scope, a fixed price, and one production system shipped in 2–3 weeks by a founding engineer who owns the result end to end.
What happens after the sprint?
You own everything — code, docs, and a runbook. Many clients convert the sprint into a retained embedded engineer or a managed engagement so we keep shipping and then operate what we built.
Is my resulting system secure and compliant?
Yes. Security is built in, not bolted on — prompt-injection defense, secrets, IAM, and evals from day one — and the build is compliance-aware so it holds up when you pursue SOC 2 or ISO 42001.
Ready to scope AI Deployment Sprint?
A 30-minute call with a senior engineer — we'll map your environment, risks, and the fastest path to value. No obligation.