Services
Choose the engagement shape that fits the business problem: a fixed implementation sprint, ongoing fractional AI engineering, or governance work that makes AI safe to operate.
Four to eight week fixed-scope builds for one high-value workflow with evaluation, integration, launch criteria, and handoff.
Embedded senior AI engineering capacity for teams that need production velocity without hiring a full internal group first.
Practical governance systems for model risk, escalation, auditability, access control, and compliance-sensitive deployment.
Which engagement fits
The same facts from the three service pages, in one view. If you're still unsure, the free discovery call exists to answer exactly this question. Full price bands live on pricing, and the questions buyers ask most are answered in the FAQ.
| Dimension | AI implementation sprint | Fractional AI engineering | Enterprise AI governance |
|---|---|---|---|
| Shape | Fixed scope, one system, one launch | Ongoing retainer, flexes month to month | Fixed-fee governance program |
| Timeline | 4–8 weeks | Monthly, 20–80 hrs/month | 4–6 weeks |
| Price band | $40K–$120K by complexity | $8K–$30K/month by hours | $25K–$60K by scope |
| Best for | One high-value workflow that needs to be scoped, built, and launched properly | Teams that need senior AI capacity and production velocity without hiring a full internal group first | Making AI safe to operate — security review, compliance, and audit readiness before or while you scale |
| Key deliverables | Scope document, architecture, build and integration, eval suite, production launch, runbook, 30 days post-launch support | Dedicated engineer hours, monthly evals, quarterly reviews, on-call coverage for production incidents | AI policy framework, risk register, eval infrastructure, operations manual, vendor evaluation matrix, executive briefing |
| Starts with | Free 30-min discovery call, then a free 1-week scoping phase | Alignment call, then your engineer joins the team | Week-1 assessment of systems, data flows, and compliance requirements |
Process
We start with business impact, data access, operational risk, and the human workflow around the AI system.
Representative examples, failure modes, and acceptance criteria shape implementation before launch.
Escalation paths, logs, monitoring, and rollback criteria are included before production traffic ramps.