How We Work
A focused, transparent process for shipping AI that actually holds up in production.
Four steps to reliable AI.
Every engagement follows the same proven framework — fast enough to ship in weeks, rigorous enough to hold up at scale.
Discovery Call
We start with a 30-minute call focused on one thing: understanding where your AI is breaking and why. No pitch — just an honest technical conversation.
- Current AI stack & architecture
- Where production failures occur
- Cost and latency pain points
- What you've already tried
AI Audit & Architecture
We audit your existing system, identify the failure modes, and design the right solution — choosing models, architecture, and guardrails based on your actual needs, not trends.
- Production failure diagnosis
- Model & pipeline architecture
- Cost optimisation plan
- Delivery timeline & milestones
Build & Ship
We build production-grade AI systems, not prototypes. Daily updates, fast iterations, and a relentless focus on reliability before anything goes live.
- AI system development
- Integration & load testing
- Guardrails & fallback handling
- Staging → production deployment
Stabilise & Optimise
Production is where most AI fails. We monitor, tune, and continuously cut costs — keeping your system reliable as usage grows and models evolve.
- Performance & anomaly monitoring
- Model cost optimisation
- System health reviews
- Proactive incident response
AI specialists vs. the alternatives.
In-house hires take months and generalist agencies bolt AI on. We've been building production AI systems from day one.
| Aspect | In-House AI Hire | General Agency | Plenvo |
|---|---|---|---|
| Time to Production | 6–12 months | 3–6 months | 3–4 weeks |
| AI Depth | Single hire | Generalist | Specialist |
| Production Reliability | Unpredictable | Low | Battle-tested |
| Cost Optimisation | Rarely | Never | Systematic |
Ship in weeks. Improve continuously.
We move fast to get you to production, then stay on as a retainer — because production AI needs continuous tuning, not a handoff.
Discovery & Audit
- Goals & success criteria
- AI stack audit
- Failure mode mapping
Architecture
- Solution design & model selection
- Guardrails & fallback strategy
- Cost & latency targets defined
Build & Test
- AI system development
- Integration & load testing
- Staging validation
Life in Production
- AI outputs drift — models update, prompts degrade
- Costs grow silently as usage scales
- New edge cases surface that tests never caught
We stay in the system after launch.
Production AI degrades silently. We monitor, tune, and cut costs continuously — so you don't have to.
- Performance monitoring
- Anomaly & cost alerts
- Incident triage
- System health review
- Cost optimisation pass
- Model evaluation & updates
- Architecture review
- Scaling & reliability planning
- Roadmap session
Let's make your AI actually work.
Book a discovery call. No pitch — just an honest conversation about where your AI is breaking and how to fix it.
Book a Call