Production AI implementation
We design, build, and operate the AI systems that move your business — not demos that don't survive a Monday.
Delivery standards we build into every engagement — not client claims.
Case Studies
These are anonymized and representative case-study patterns. Named customer stories are published only after customers approve disclosure.
A B2B support workflow that answers repeat questions from approved knowledge, customer account state, and policy constraints while escalating low-confidence cases to humans.
Target result: faster first response with fewer tier-1 tickets reaching senior agents.
A document pipeline that extracts key clauses, compares them against a company playbook, and routes exceptions to legal with source-page provenance.
Target result: reduce manual review hours while preserving legal control over final decisions.
A post-call workflow that turns transcripts into buyer signals, CRM updates, and sales follow-up drafts while keeping reps in charge of what gets sent.
Target result: cleaner CRM data and faster follow-up without risky automated sending.
"The useful proof is not a flashy demo. It is a working workflow with evals, escalation, and a runbook."
Production launch principle"Governance belongs in the build, not in a cleanup meeting after the prototype already spread."
Governance principle"The model is one component. The operating system around it decides whether the AI work holds up in production."
Operating principleServices
4–8 weeks · Fixed scope
A single AI system, fully scoped, designed, built, and shipped on a fixed timeline and budget. We bring engineering, evals, and production discipline; you bring workflow knowledge.
Examples: support agents, document review, internal Q&A, sales call analysis, workflow automation.
Scope a sprintOngoing retainer · 20–80 hrs/mo
Dedicated senior AI engineering bandwidth on retainer. We become your AI team — building new systems, optimizing existing ones, running evals, and handling production incidents.
Includes: engineering hours, monthly evals, quarterly reviews, on-call coverage.
Discuss a retainer4–6 weeks · Fixed fee
AI governance, security, and operating-model readiness. We design policies, audits, and infrastructure so your AI work survives security review and scales without surprises.
Includes: governance design, security review, vendor policy, eval infrastructure, executive briefing.
Review your readinessOur Process
01
One call to map the use case, technical constraints, and success metrics.
02
A detailed scope document: architecture, milestones, pricing, team.
03
Architecture, eval plan, and production criteria locked in.
04
Weekly stakeholder checkpoints; live demo at every milestone.
05
System live with monitoring, runbook, and 30 days of post-launch support.
06
Knowledge transfer to your team, or transition to a fractional engagement.
Why Us
Through our partnership with ProductExec, you can move from "what should we build" to "build it" without re-briefing.
Every system ships with evals, monitoring, fallback paths, and runbooks. No magic prompts that break next week.
Designed for thousands of repeated runs, not impressive single demos.
Audit trails, security review, escalation, and compliance from day one.
Claude, OpenAI, open-weight; routed by task criticality, not vendor loyalty.
We've run the systems we ship. We know what production really means.
About
Enterprise AI Studio is led by Kevin Owens, a product and transformation executive with CPO-level experience across B2B SaaS, productivity, healthcare workflow, and AI-enabled operating-model work. We work alongside ProductExec and bring in specialist engineers for each engagement.
FAQ
ProductExec helps you decide what AI to build and how it fits your operating model. Enterprise AI Studio is the team that builds it. Many clients work with both — strategy first, then implementation.
No. We augment your team. We typically build the AI core, integrate it with your systems, and hand off to your team or stay on retainer for continued AI work.
We're model-agnostic. We pick the right model for each task — frontier models for judgment-heavy work, cheaper long-context options for synthesis, open-weight where appropriate.
Implementation sprints range from $40K-$120K. Retainers from $8K-$30K/month. Governance projects from $25K-$60K.
Yes. We sign mutual NDAs before any scoping conversation.
Governance is baked into everything we build. We include audit trails, security reviews, role-based access control, and escalation protocols from day one. If your organization has compliance requirements (SOC 2, HIPAA, etc.), we design the AI system to support them, not work around them.
Yes. We typically own the entire integration — APIs, webhooks, database connections, CRM/ERP linking, whatever your stack requires. We ensure the AI system fits seamlessly into your workflows without requiring your team to rewire their operations.
That's common. Our discovery call is free and specifically designed to map your constraints and uncover high-leverage use cases. We help you prioritize what to build first, then scope the work you want to move forward on.
Get in Touch
Tell us about your use case. We'll map the constraints and the fastest path to production — no sales deck, just a direct conversation.